In depth MINISTERIO DEL INTERIOR MINISTERIO DEL ...approximately 4% in the number of fatal accidents...
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26 Second quarter 2011 MINISTERIO DEL INTERIOR www.dgt.es from the Observatory In depth National Road Safety Observatory 1. Introduction The impact of traffic speed on safety is the focus of intense debate between scientists, road users and policy-makers. The goal of this brief report is to summarise the most important scien- tific literature in this field of research. Increasing traffic speed may have several positive effects, the most important one being the reduction in travel times. The enor- mous technical advances achieved in the past decades in the design of roads, vehicles and traffic management, along with the improvement in the behaviour of users, have made it possible to increase traffic speeds while, at the same time, reducing the risk of accident and injury. The decrease in travel times has important benefits to productivity and provides users with more spare time for other activities. Speed has also important negative consequences, such as energy consumption, environmental impact and road accidents and injuries. This brief report focuses solely on the relationship between speed and safety. There are several reasons why speed affects safety. Many of them are of a physical nature: the distance required for fully stop- ping a vehicle increases with speed; therefore, the probability of avoiding a collision with another vehicle or obstacle in an emer- gency situation decreases with speed. On the other hand, inju- ries and property damage in a crash increase with impact speed, which, at the same time, increases with the speeds of vehicles before the collision. As will be summarised in section 3, empirical research pro- vides clear evidence of the negative impact of speed: greater speed increases the risk of accidents and injuries, both at the individual level —relationship between the speed of a given driver and his risk— and at the aggregated level —relationship between the average speed of traffic flow and the total number of accidents and injuries—. Reports from national and international road safety organisa- tions concur that speed is, together with alcohol consumption and failure to wear seat belt, the main risk factor of accident and injury [Ref. 1]. According to the European Road Safety Observatory’s re- ports, speed is an essential contributory factor in around 10% of all accidents and 30% of fatal accidents [Ref. 2]. Similar figures are cited in the World Health Organization’s world report [Ref. 3]. In Spain, speed, whether excessive or inappropriate, was cited as a contributory factor in 13% of the injury accidents registered by traffic police officers in 2009; this percentage rose to 31% in fatal accidents [Ref. 4]. Speed management plays a key role in road safety strategies based on the so-called Safety System approach, such as the Swedish Vision Zero or the Dutch Sustainable Safety [Ref. 5]. One of the fundamental principles of this approach is that the traffic system should be able to tolerate human errors and limitations, without them resulting in deaths or serious injuries. In order to achieve this goal, it is necessary to manage crash energy, so that no user is exposed to forces greater than those determined by physical vulnerability. Thus, the concept of safe speed emerges, defined as the value of traffic speed that can ensure the protection of users. Safe speed depends on the characteristics of road in- frastructure and traffic flow; for example, it is lower on rural roads than on motorways, and it is also lower on pedestrian areas than on wide avenues where flows of pedestrians are segregated from motor vehicles. This brief report also includes a discussion about the impact of speed limits, as the basic tool to manage speed (section 4). 2. Factors affected by speed The precise relationship between speed and the number of accidents and victims is affected by many factors related to the road, the vehicles and the drivers. This affirmation is easy to check when one compares the performance of modern motorways with that of rural two-lane, two-way roads. On motorways, average speeds are far higher, but the number of fatalities, for the same amount of distance travelled, is about three times lower. One should not conclude from this observation that higher speeds contribute to reducing accidents, but rather that there are many other factors —in our example, mainly related to road design— that affect the precise number of accidents and victims that is expected at a given value of speed. Active safety systems in vehicles, such as anti-lock braking system (ABS) and electronic stability control (ESC), also affect the relationship between speed and safety. Assuming that a driver’s behaviour remains the same —in particular, that his choice of speed is independent from the characteristics and safety systems of his car—, these devices reduce the risk of being involved in a crash. In order to study the impact of speed, independently from the influence of other factors, we must suppose that a given driver, driving a fixed car through a fixed road segment, increases his speed. What changes should we expect then? The most important changes have to do with vehicle dyna- mics: [Ref. 6]. Firstly, the stopping distance increases with speed, due to the increase of both the distance travelled during the time of perception and reaction, and the distance travelled during braking. Secondly, as speed increases, the gap between travelling speed and the maximum speed determined by tyre-road friction is narrowed, thus increasing the risk of veering off road on a bend and the risk of hydroplaning in rain conditions. Speed also influences accident severity, i.e. the probability that someone involved in a collision will be injured. At the moment of the collision, the amount of energy to be dissipated depends on the squares of the impact velocities of the vehicles involved (kinectic energy). An increase in this energy leads to an increase in the prob- ability of injuries among the people involved in the accident —as ve- hicle occupants or pedestrians—. The relationship between impact speed and injury risk has been amply proven in scientific literature (see e.g. [Ref. 7]).
Transcript of In depth MINISTERIO DEL INTERIOR MINISTERIO DEL ...approximately 4% in the number of fatal accidents...
26Second quarter 2011
MINISTERIODEL INTERIOR
www.dgt.es
MINISTERIODEL INTERIOR
Nacional Road Safety Observatory from the Observatory
In depth National Road Safety ObservatoryJosefa Valcárcel, 2828071 Madridwww.dgt.es Nipo: 128-11-027-3
National Road Safety Observatory
1. Introduction
The impact of traffic speed on safety is the focus of intense debate between scientists, road users and policy-makers. The goal of this brief report is to summarise the most important scien-tific literature in this field of research.
Increasing traffic speed may have several positive effects, the most important one being the reduction in travel times. The enor-mous technical advances achieved in the past decades in the design of roads, vehicles and traffic management, along with the improvement in the behaviour of users, have made it possible to increase traffic speeds while, at the same time, reducing the risk of accident and injury. The decrease in travel times has important benefits to productivity and provides users with more spare time for other activities.
Speed has also important negative consequences, such as energy consumption, environmental impact and road accidents and injuries. This brief report focuses solely on the relationship between speed and safety.
There are several reasons why speed affects safety. Many of them are of a physical nature: the distance required for fully stop-ping a vehicle increases with speed; therefore, the probability of avoiding a collision with another vehicle or obstacle in an emer-gency situation decreases with speed. On the other hand, inju-ries and property damage in a crash increase with impact speed, which, at the same time, increases with the speeds of vehicles before the collision.
As will be summarised in section 3, empirical research pro-vides clear evidence of the negative impact of speed: greater speed increases the risk of accidents and injuries, both at the individual level —relationship between the speed of a given driver and his risk— and at the aggregated level —relationship between the average speed of traffic flow and the total number of accidents and injuries—.
Reports from national and international road safety organisa-tions concur that speed is, together with alcohol consumption and failure to wear seat belt, the main risk factor of accident and injury [Ref. 1]. According to the European Road Safety Observatory’s re-ports, speed is an essential contributory factor in around 10% of all accidents and 30% of fatal accidents [Ref. 2]. Similar figures are cited in the World Health Organization’s world report [Ref. 3]. In Spain, speed, whether excessive or inappropriate, was cited as a contributory factor in 13% of the injury accidents registered by traffic police officers in 2009; this percentage rose to 31% in fatal accidents [Ref. 4].
Speed management plays a key role in road safety strategies based on the so-called Safety System approach, such as the Swedish Vision Zero or the Dutch Sustainable Safety [Ref. 5]. One of the fundamental principles of this approach is that the traffic system should be able to tolerate human errors and limitations, without them resulting in deaths or serious injuries. In order to achieve this goal, it is necessary to manage crash energy, so that no user is exposed to forces greater than those determined by
physical vulnerability. Thus, the concept of safe speed emerges, defined as the value of traffic speed that can ensure the protection of users. Safe speed depends on the characteristics of road in-frastructure and traffic flow; for example, it is lower on rural roads than on motorways, and it is also lower on pedestrian areas than on wide avenues where flows of pedestrians are segregated from motor vehicles.
This brief report also includes a discussion about the impact of speed limits, as the basic tool to manage speed (section 4).
2. Factors affected by speed
The precise relationship between speed and the number of accidents and victims is affected by many factors related to the road, the vehicles and the drivers. This affirmation is easy to check when one compares the performance of modern motorways with that of rural two-lane, two-way roads. On motorways, average speeds are far higher, but the number of fatalities, for the same amount of distance travelled, is about three times lower. One should not conclude from this observation that higher speeds contribute to reducing accidents, but rather that there are many other factors —in our example, mainly related to road design— that affect the precise number of accidents and victims that is expected at a given value of speed.
Active safety systems in vehicles, such as anti-lock braking system (ABS) and electronic stability control (ESC), also affect the relationship between speed and safety. Assuming that a driver’s behaviour remains the same —in particular, that his choice of speed is independent from the characteristics and safety systems of his car—, these devices reduce the risk of being involved in a crash.
In order to study the impact of speed, independently from the influence of other factors, we must suppose that a given driver, driving a fixed car through a fixed road segment, increases his speed. What changes should we expect then?
The most important changes have to do with vehicle dyna-mics: [Ref. 6]. Firstly, the stopping distance increases with speed, due to the increase of both the distance travelled during the time of perception and reaction, and the distance travelled during braking. Secondly, as speed increases, the gap between travelling speed and the maximum speed determined by tyre-road friction is narrowed, thus increasing the risk of veering off road on a bend and the risk of hydroplaning in rain conditions.
Speed also influences accident severity, i.e. the probability that someone involved in a collision will be injured. At the moment of the collision, the amount of energy to be dissipated depends on the squares of the impact velocities of the vehicles involved (kinectic energy). An increase in this energy leads to an increase in the prob-ability of injuries among the people involved in the accident —as ve-hicle occupants or pedestrians—. The relationship between impact speed and injury risk has been amply proven in scientific literature (see e.g. [Ref. 7]).
that an increase in the speed limit on high-capacity roads could indeed lead to an increase in the number of casualties on these roads, but at the same time, to a shift of journeys from rural roads - more dangerous roads - so that the system-wide net balance is positive. This argument comes mainly from some studies con-ducted in the U.S., such as [Ref. 27]. However, the latest research has not found these effects. Grabowski and Morrisey [Ref. 28] examined the overall impacts of the two speed limit changes in the U.S. in 1987 and 1995; the following effects were found:
• Increase in the speed limit from 55 mph to 65mph (year 1987): 16-17% increase in the number of fatalities on the roads affected; non-significant effect on the interurban roads that were not affected.
• Increase in the speed limit to 70-75 mph or higher (year 1995): 36-37% increase in the number of fatalities on the roads affected; 7-11% increase on the interurban roads that were not affected.
Therefore, the authors did not find a reduction of fatalities in those roads where the speed limit was not changed. In fact, the second result above shows an increase in fatalities, a result that may be linked to the speed spillover or generalization theory, ac-cording to which the changes in average speeds on certain roads may extend their effect to other parts of the road network.
5. Driving speeds in Spain
Drivers’ behaviour towards speed is usually studied in free-flow situations, where the prevailing conditions are such that the driver can choose any speed: lack of roadside checks, low tra-ffic density, favourable road design, road surface in good condi-tion and good weather conditions. The available data in Spain show that, under free-flow conditions, between 38% and 59% of the drivers travel above the maximum speed limit; in between 17% and 37% of the cases, the scale of the offence is more than 10km/h.
Table 2. Average speeds of light vehicles in Spain under free-flow conditions. 2010.
ROAD TYPEAverage speed (km/h)
% over the limit
% more than
10km/h over the
limit
Motorway 117.7 52% 27%
Dual carriage-way 113.9 38% 17%
Trunk road. Speed limit 90 km/h
96.3 51% 32%
Trunk road. Speed limit 100 km/h
98.4 59% 37%
Source: National Road Safety Observatory, study carried out by The Univer-sity Institute for Automobile Research (INSIA) [Ref. 29].
The recent evolution has been clearly positive. Free-flow indi-cators are currently only available for the years 2009 and 2010. To carry out a time analysis, we must use other two indica-tors concerning all traffic conditions, and not just traffic-calmed situations under favourable conditions. For instance, the Ministry of Public Works performs measurements of average speeds at a sample of locations in the road network of its ownership. These measurements show that the percentage of light vehicles trave-lling over 120 km/h on motorways has fallen from 27.99% in 2003 to 17.08% in 2010. On trunk roads, the percentage of vehicles travelling over 100 km/h has fallen from 17.35% to 12.30% over the same period.
• With regard to the individual risk, the most comprehen-sive study is the one conducted by the University of Adelaide, which shows that the risk of involvement in a serious crash increases steadily with speed, both on urban and interurban roads.
• From the perspective of the collective risk, Göran Nilsson’s power model is the most commonly used model. The power model is based on the following qualitative principles:
• A change in speed leads to a change in the same di-rection in crash/casualties frequency.
• The greater the change in speed, the greater the change in crash/casualties frequency.
The available evidence confirms the aforementioned prin-ciples. It has been found that the relationship between speed and safety is very consistent: if average speed in-creases (or decreases), the number of fatal accidents al-most always increases (or decreases). From a quantitative point of view, the validations carried out have confirmed that, on interurban roads, the predictions of the power model are valid; in this way, the rule according to which
a 1% increase in average speed leads to an increase of approximately 4% in the number of fatal accidents can be accepted. On urban roads, evidence suggests that the im-pact of speed could be lower than the one predicted by the power model, but it is in any case significant.
Evidence showed, moreover, that the relationship between speed and accidents does not significantly depend on the country or region concerned.
• With regard to the impact of the speed limit, most evidence indicates that the mean speed of traffic changes in the same direction as the speed limit, however, the magnitude of the change is smaller (around 25%). The available evidence shows that an increase in the speed limit leads to an increase in accidents and casualties.
• Spain has seen significant decreases in speed across the entire interurban road network and not just in controlled sec-tions. Taking into account all scientific evidence available, it is plausible to assume that this decline in speed must have made a major contribution to the recent reduction in the number of accidents.
• (Ref. 1) European Transport Safety Council (2010) Tackling the three main killers on the roads. A priority for the forthcoming EU Road Safety Action Programme. PIN Flash N.16. Brussels.
• (Ref. 2) European Road Safety Observatory (2006) Speeding. Re-trieved January 20, 2007 from www.erso.eu.
• (Ref. 3) World Health Organization (2004) Informe mundial sobre pre-vención de los traumatismos causados por el tránsito.
• (Ref. 4) Dirección General de Tráfico, Observatorio Nacional de Seguri-dad Vial (2010) Las principales cifras de la siniestralidad vial. Spain 2009.
• (Ref. 5) OECD (2008) Towards Zero: Achieving Ambitious Road Safe-ty Targets through a Safe System Approach. OECD, Paris.
• (Ref. 6) Aparicio Izquierdo, F. (2010) Velocidad: factor de riesgo en accidentes de tráfico. XV Jornada de la Cátedra ADA de Seguridad de los Vehículos y del Tráfico. ETS de Ingenieros Industriales de Madrid. 30 November 2010. Available on: http://www.insia-upm.es/xv--jorna-da-de-la-catedra-ada-ntc40.asp?vuelta=1 (visited on 04/05/2010).
• (Ref. 7) NHTSA (2001) Tire pressure monitoring system FMVSS No.138. Preliminary economic assessment. Office of regulatory analy-sis and evaluation. Plans and policy. National Highway Traffic Safety Administration.
• (Ref. 8) Shinar, D. (1998) Speed and crashes: a controversial topic and an elusive relationship. En Transportation Research Board (1998). Managing speed: a review of current practice for setting and enforcing speed limits. Special Report 254.
• (Ref. 9) Törnros, J. (1995) Effect of driving speed on reaction time during motorway driving. Accident Analysis and Prevention, Vol. 27, No.4, pp. 435-442.
• (Ref. 10) Solomon, D. R. (1964). Accidents on main rural highways related to speed, driver and vehicle. Federal Highway Administration, Washington, DC.
• (Ref. 11) Hauer, E. (2009) Speed and safety. Transportation Research Record 2103, pp. 10-17.
• (Ref. 12) Kloeden, C. N.; Ponte, G.; McLean, A. J. (2001) Travelling speed and the rate of crash involvement on rural roads.
• (Ref. 13) Kloeden, C. N., McLean, A. J. & Glonek, G. (2002) Reanaly-sis of travelling speed and the rate of crash involvement in Adelaide South Australia.
• (Ref. 14) Aarts, L.; Van Schagen (2006) Driving speed and the risk of road crashes: A review. Accident Analysis and Prevention 38 (2006) 215–224.
• (Ref. 15) Nilsson, G. (2004). Traffic safety dimensions and the Power Model to describe the effect of speed on safety. Bulletin 221. Lund Institute of Technology, Department of Technology and Society, Traffic Enginering, Lund.
• (Ref. 16) European Road Safety Observatory (2006) Speeding.
• (Ref. 17) OCDE, ITF, ECMT (2006) Speed management.
• (Ref. 18) ETSC (2008), “Managing speed: Towards safe and sustain-able road transport”.
• (Ref. 19) World Health Organisation, FIA Foundation, Global Road Safety Partnership, The World Bank (2008) Speed management. A road safety manual for decision-makers and practitioners.
• (Ref. 20) Elvik, R.; Christensen, P.; Amundsen, A. (2004) Speed and road accidents. An evaluation of the Power Model. TOI Report 740/2004.
• (Ref. 21) Elvik, R. (2009) The Power Model of the relationship be-tween speed and road safety. Update and new analyses. TOI Report 1034/2009.
• (Ref. 22) Cameron, M.; Elvik, R. (2010) Nilsson’s Power Model con-necting speed and road trauma: Applicability by road type and alter-native models for urban roads. Accident Analysis and Prevention 42 (2010) 1908–1915.
• (Ref. 23) Hauer, E.; Boneson, J.A. (2008) An empirical examination of the relationship between speed and road accidents. Harkey, D.L. et al (2008) Accident Modification Factors for Traffic Engineering and ITS improvements. National Cooperative Highway Research Programme, Report NCHRP-617. Transportation Research Board.
• (Ref. 24) Harkey, D.L.; Srinivasan, R.; Back, J.; Council, F.M.; Eccles, K.; Lefler, N.; Gross, F.; Persaud, B.; Lyon, C.; Hauer, E.; Boneson, J.A. (2008) Accident Modification Factors for Traffic Engineering and ITS improvements. Transportation Research Board. NCHRP Report 617.
• (Ref. 25) American Association of State Highway and Transportation Officials (2010) Highway Safety Manual. 1st edition.
• (Ref. 26) Reiff, L. K.; Foldager, I; Hels, T.; Hemdorff, S.; Lund, H. (2008). 130 km/t på motorveje. Virkning på faktisk hastighed, uheld og miljøbelastning. Rapport 337. Vejdirektoratet, København.
• (Ref. 27) Lave, C.; Elias, P. (1993) Did the 65 mph speed limit save lives? Accident Analysis and Prevention, 26, pp. 49-62.
• (Ref. 28) Grabowski, D.C.; Morrisey, M.A. (2007) Systemwide impli-cations of the repeal of the national maximum speed limit. Accident Analysis and Prevention 39, pp. 180–189.
• (Ref. 29) Instituto Universitario de Investigación del Automóvil (2010) Medición de velocidad de flujo libre en la red vial española. Study car-ried out for the Observatorio Nacional de Seguridad Vial.
• (Ref. 30) Ministerio de Fomento (2011) http://www.fomen-to.gob.es/NR/rdonlyres/FBD5E4E5-D096-41A5-8F29-DD-0FA3501C44/105162/serie_20022010.pdf.
Table 3. Evolution of speeds in points of measurement of the Ministry of Public Works. Period 2003-2010.
Indicator 2003 2004 2005 2006 2007 2008 2009 2010
% Light vehicles travelling over 120km/h on dual carriageways 27.99% 25.16% 26.17% 19.68% 20.60% 18.92% 15.71% 17.08%
% Light vehicles travelling over 100km/h on trunk roads 17.35% 15.25% 16.73% 12.00% 12.45% 9.54% 12.23% 12.30%
Source: Ministry of Public Works [Ref. 30].
Another available indicator is the average speed on sections controlled by fixed speed cameras, in which, according to the information collected by the National Road Safety Observatory, the percentage of vehicles travelling over the speed limit fell from 28-29% in 2006 to 9-13% in 2010, with a very similar evolution on dual carriageways and trunk roads.
The two types of data above —speeds on a sample of sec-tions of the network and speeds on sections controlled by speed cameras— suggest the following two conclusions: firstly, the policies of recent years, such as the point system for driving li-cences and the plan for installation of speed cameras, have been successful in reducing speeds; secondly, this reduction seems to have taken place across the entire network, and not just in controlled sections.
Although a precise assessment has not yet been made, it is plausible to assume, on the basis of all the scientific pieces of evi-
dence cited in previous sections, that the fall of the driving speed which has occurred over the last few years must have played a very significant role in the reduction of the accident rate in Spain since 2003 (down by 54% for road accident fatalities over 2003-2010).
6. Conclusions
This report has presented a general overview of the current knowledge about the relationship between speed and safety. The following is a summary of the main conclusions:
• The relationship between speed and safety can be analysed from the perspective of the individual risk —relationship be-tween the speed of a driver and his risk— or of the collec-tive risk —relationship between the average speed of the vehicles as a whole and the total number of accidents—.
References
In depth l 26
En Profundidad l 26
Table 1. Predictions of the effect of variations in average speed on the number of fatal accidents, according to initial average speed.Figure 1. Relationship between speed and risk of involvement in an accident with at least a person hospitalised.
0
5
10
15
20
25
30
35
-15 -10 -5 0 5 10 15 20 25
Difference with respect to average speed (km/h)
Rel
ativ
e ris
k(a
vera
ge s
peed
=1)
Urban roads (limit 60km/h) Interurban roads (limit 80-120 km/h)
Source: [Ref. 12] [Ref. 13].
3.4. Relationship between average speed and accident frequency on a stretch of road or road network
The vast majority of scientific evidence available relates to the relationship between the total number of accidents and casualties and the average speed on a stretch of road, road or road network. Among all the models proposed in the scientific literature, the most popular one is certainly the so-called ‘po-wer model’, proposed by the Swedish researcher Göran Nils-son [Ref. 15]. This model has been cited as scientific evidence by, inter alia, the European Road Safety Observatory [Ref. 16], the OECD [Ref. 17], the European Transport Safety Council [Ref. 18] and the World Health Organisation [Ref. 19].
In its complete formulation, the power model comprises six equations that relate variations in the number of accidents and in the number of road users killed or injured, to variations in the average speed of traffic. If we focus on the three ac-cident equations, the model can be summarised as follows: an increase of 1% in the average speed, all other influencing factors (including traffic flow) being kept constant, results in, approximately:
• An increase of 4% in fatal accidents.
• An increase of 3% in fatal and serious accidents.
• An increase of 2% in accidents with casualties of any severity.
The following discussion will be primarily focused on the effect of speed on the number of fatal accidents. Figure 2 shows the prediction of the model for this kind of accident.
Figure 2. Change in the number of fatal accidents (%) as a result of changes in average speed (km/h), according
to the initial average speed.
-60%
-40%
-20%
0%
20%
40%
60%
80%
-15 -10 -5 0 5 10 15
Change in average speed (km/h)
Cha
nge
in th
e nu
mbe
r of f
atal
acc
iden
ts
(%)
80km/h
90km/h
100km/h
120km/h
Source: Power Model [Ref. 15].
The power model stems from the observation of the ef-fects produced by the different speed limit changes that took place in Sweden in the late 1960s and at the beginning of the following decade. A detailed discussion of the model is outside the scope of this report. The main issue here is the validity of its predictions. Two key validations have been car-ried out so far:
• The validation by Rune Elvik et al [Ref. 20] [Ref. 21] [Ref. 22].
• The validation by Hauer and Boneson [Ref. 23], for the American association AASHTO’s Highway Safety Manual [Ref. 25].
The input data are the same in both cases: the collec-tion of 526 speed-accident estimates obtained by Elvik et al from 115 scientific studies. Each of these 526 estimates is expressed in terms of the percentage change in accidents or casualties of a certain severity produced by a certain speed change.
The conclusions of the above two validations of the power model can be summarised as follows.
• On interurban roads, the validations in general provide consistent results with the power model. Table 1 pre-sents an overview of the predictions of the power model and the two validations for two initial average speeds (80 km/h and 120 km/h), and different changes in speed. The validation by Elvik et al leads to values very close to those of the power model in all cases, while the valida-tion by Hauer and Boneson is in line with it for an initial speed of 120 km/h, and predicts larger effects when the initial speed is 80 km/h. As can be seen in the table, even very small increases in speed may lead to signifi-cant changes in fatal accidents; thus, a change from 120 to 121 km/h is expected to increase the number of fatal accidents by 3-4%.
• There are fewer studies in urban areas. Elvik et al have found a smaller effect in these cases: a 1% increase in the average speed would result in an increase of ap-proximately 2.6% in fatal accidents, instead of 4% as predicted by the power model.
• Another interesting finding of both validations is that the effects of speed seem not to depend on the coun-try where the study was conducted. In this sense, El-vik et al point out that “there is no support for the idea of de-veloping separate versions of the model for each country. This shows that the effects of speed on road safety are likely to be universal and not strongly influenced by conditions that are specific to a certain country” ([Ref. 21], page 23). The validation by Hauer and Boneson, on the other hand, concluded that “the speed-versus-crash relationship in the foreign stud-ies was similar to that in the U.S. studies” ([Ref. 24], page 26).
To conclude this discussion, it is important to note that the average speed is not the only parameter of the speed distri-bution that influences safety. In particular, there is consensus that the dispersion of speeds between vehicles is a risk fac-tor, although there are no reliable estimates of this effect. The European Road Safety Observatory summarises it as follows: “If on a particular road, the speed variance is high, this will result in less predictability, more encounters, more overtaking ma-neuvres, etc. Therefore, when the speed differences in-crease, the accident risk increases as well. […] But no reliable quantified relationship has been established for this linkage”. ([Ref. 2], page 6).
One of the most controversial effects of speed has to do with drivers’ behaviour. Many drivers claim that driving slowly becomes monotonous and that, as they increase their driving speed, their level of attention rises, with a net improvement in safety. However, it should be borne in mind that at higher speeds, the rate at which the driver must process informa-tion about the highway and its environment increases directly, demanding an extra effort that may cause fatigue. As the re-searcher Shinar points out [Ref. 8], «the act of paying attention is an effort» (p. 233), so the increase in the level of attention with increasing speed, if any, would occur in any case at the expense of an increase in the fatigue caused by driving.
To our knowledge, the only research carried out so far on the relationship between speed and the level of driver’s atten-tion was an experiment conducted in Sweden in the 1990s [Ref. 9]. Twenty-four drivers participated in the experiment, each of whom did 200km of motorway driving three times at speeds of 70km/h, 90km/h and 110km/h, respectively. The level of attention was measured through the reaction time. Despite the large differences between the three speeds test-ed, the changes observed in the reaction times were small: a 40km/h increase in speed was found to produce a reduction of 4% in the reaction time. The author concluded that «the present findings indicate that the possibility of counteracting these consequences [the increase in stopping distance due to higher speeds] by being somewhat more alert at higher speeds are not great» (p. 441).
3. Relationship between driving speed and the number and seriousness of the accidents
3.1. Introduction
We have already discussed that the precise relationship between speed and the number of accidents and victims is affected by many factors. Most past research has not sought to determine relationships between exact values of speed and accidents, but between variations of speed and variations of ac-cidents. Let us consider a particular kind of road, through which vehicles and drivers of known characteristics drive. At present, it is not possible for us to estimate the expected number of acci-dents at different given values of speed: 60, 80, 100, 120 km/h. However, research evidence does allow us to estimate the per-cent variation of accidents that should be expected when speed increases from, say, 60 to 80 km/h, or 100 to 120 km/h, while the remaining factors of influence remain constant.
There is another usual way to describe and analyse the speed problem, consisting in determining the proportion of accidents in which excessive speed (speed over the maximum permitted speed) or inappropriate speed (unsuitable for the prevailing con-ditions) appear as the main cause or a contributory factor. The main drawback of this approach is that it cannot be used to estimate the variation of accidents that should be expected from an increase or decrease in speed. Let us assume that excessive speed has been identified as the main cause of 10% of acci-dents. This does not imply that perfect compliance with speed limits would reduce accidents only by 10%. Even when the main cause of an accident is different from speed (for example, veer-ing into oncoming traffic due to a distraction), speed still influ-ences the probability of the accident occurring and of it resulting in injuries.
3.2. Individual and collective risk
Once established our goal of estimating relationships be-tween variations of average speed and variations of accidents, two basic approaches are possible:
• [Approach 1] To analyse the relationship between the driv-ing speed of a given driver and his risk of accident involve-ment.
• [Approach 2] To analyse the relationship between the average speed of the vehicles as a whole and the total number of accidents occurring on a stretch of road, road or road network.
These approaches are discussed in sections 3.3 and 3.4 respectively.
3.3. Relationship between speed and individual risk
In order to obtain representative relationships between the speed of a driver and his accident risk, we should ideally be able to count the number of accidents in which a given driver is involved when travelling at different speeds. By doing so, driver’s characteristics would remain constant, and thus have no influ-ence on the results. However, this method is not feasible, due to practical difficulties and also to the fact that accidents are rare events in most drivers’ lives.
The practical solution consists in comparing the speeds of two different populations of drivers: the population of drivers in-volved in accidents and a sample of the population of drivers travelling on the road network at a certain moment. If drivers involved in accidents travelled, on average, at higher speeds than those of drivers not involved in accidents, we would con-clude that speed significantly increase the risk of accident. If the speeds of both populations of drivers are the same, we would conclude that it does not affect risk.
The initial speeds of the vehicles involved in accidents can only be obtained by means of reconstruction procedures, which are expensive and may be prone to error. Another drawback of the method is that, since we are observing two different popula-tions of drivers, there may be characteristics of the drivers, other than speed, which may vary between both populations and bias the estimates of risks. For instance, age and sex are two fac-tors that influence accident risk and that, at the same time, may determine speed. Under these conditions, if it is found that the vehicles moving faster than the others are involved in more ac-cidents, it is not clear to what extent the result can be due to the fact that such vehicles are typically driven by younger drivers, who have a higher risk at any speed.
The first studies of the relationship between speed and indi-vidual risk were published in the U.S. in the 1960s. Among them, the best known and most frequently cited is certainly Solomon’s study [Ref. 10], in which a U-shaped curve was obtained, ac-cording to which the risk was minimal for drivers who travelled at a speed slightly above the average speed of the traffic flow, and it increased both for faster and slower drivers.
According to various authors (see e.g. [Ref. 11]), Solomon’s study has methodological inadequacies that could significantly bias its risk estimations. On the other hand, the most recent studies have not replicated the U-shaped curve. The latest avail-able study was conducted by the University of Adelaide [Ref. 12][Ref. 13] and researched the relationship between a vehicle’s speed and the likelihood of involvement in an accident with at least one person hospitalised. According to a review published by researchers Aarts and Van Schagen [Ref. 14], the results of the Adelaide study “for now […] best describe the relationship between individual vehicle speed and crash rate” (page 222). These results are shown in Figure 1; as can be seen, both risk curves —for urban and interurban roads— are monotonically in-creasing in the whole speed range.
If the initial average speed is…
And the average speed…
The number of fatal accidents varies…
According to the power model
According to the validation
by Elvik et al
According to the validation by Hauer and Boneson for the
Highway Safety Manual
80 km/h
Increases by 8 km/h +46% +48% +58%
Increases by 4 km/h +22% +22% +28%
Increases by 1 km/h +5% +5% +7%
Decreases by 1 km/h -5% -5% -7%
Decreases by 4 km/h -19% -19% -26%
Decreases by 8 km/h -34% -35% -52%
120 km/h
Increases by 8 km/h +29% +30% +32%
Increases by 4 km/h +14% +14% +15%
Increases by 1 km/h +3% +3% +4%
Decreases by 1 km/h -3% -3% -4%
Decreases by 4 km/h -13% -13% -15%
Decreases by 8 km/h -24% -25% -29%
Methodology for drawing up the table:
Power model: the equation (5.2) on page 56 of [Ref. 15] has been used. Validation by Elvik et al: a power model with exponent 4.13 is used, according to table 10 of [Ref. 21] and table 7 of [Ref. 22]. Validation by Hauer and Boneson: table 3E-2 on page 3-57 of [Ref. 25] is used, converting mph to km/h and using linear interpolation when the value
ranges diverse from those in table 2 in this report.
4. Influence of speed limits
The speed limit is certainly the most important of all the speed management tools. A speed limit change will influence safety to the extent that it leads to a change in actual driving speeds. The causal sequence would be the following: an in-crease (or decrease) in the speed limit leads to an increase (or decrease) in the mean speed of traffic, which in turn leads to an increase (or decrease) in the number of accidents and casual-ties. If we have empirical relationships between the speed limit change and the change in the mean speed, we may apply the power model - or the validations presented in the previous sec-tion - to estimate the expected impact on accidents.
Evidence show that a speed limit change leads to a change in the same direction in the actual driving speed. For example:
• The researchers Elvik, R. et al concluded that “on the average, the change in the mean speed of traffic induced by a change in speed limit appears to be around 25% of the change in speed limit” ([Ref. 20], page 93); i.e. a change in the speed limit of, for example, ±10km/h produces on the average a change in the mean speed of traffic of ±2.5km/h.
• The OECD mentiones in its report on speed management that “meta-analyses show that lowering the speed limit by 10 km/h leads to a decrease in speed of 3-4 km/h. A simi-lar effect can be expected from an increase in the speed limit” ([Ref. 17], page 100).
Thus the mean speed of traffic increases to a lesser extent than the increase in the speed limit. But this does not mean that the effect on accidents will be small. For example, the power model states that an increase from 120 to 122.5 km/h
in the mean speed would lead to a 9% increase in fatal acci-dents.
Most of the experiences in raising the speed limit confirm the negative impact on accidents. We will cite only a few relevant cases. More case studies can be found in [Ref. 19].
In Denmark, the speed limit was raised on half of the mo-torway network from 110km/h to 130km/h on 30 April 2004. On the other half, the speed limit was maintained at 110km/h. The Danish Road Directorate carried out an assessment of its impact during the 16 months after the entry into force of the change [Ref. 26]. In August 2005 the Danish Government in-troduced the point system for driving licences; as from that date it is not possible to separate the effect of both measures. On motorways where the speed limit was maintained at 110 km/h, the average speed decreased from 118.9 to 116.0km/h (by approximately 2.4%). This reduction was presumably the consequence of the measures that follow the increase in speed limit, such as: increased traffic surveillance, stricter penal-ties, awareness campaigns and speed limit signposting at the 110km/h motorways. To the contrary, on roads where the speed limit was raised, speed increased from 120.4 to 121.2km/h (by approximately 0.7%). The changes observed in the number of casualties were as follows: on motorways where the speed limit was raised: increase of 9%; on motorways where the speed limit was not changed, decrease of 40%; on all other interurban roads: decrease of 18%. According to the regression model ad-justed by the authors of the report, a change in mean speed of +/-1km/h results in about 10% increase/decrease in personal injuries. This relation is much more pronounced than the one predicted by Nilsson’s power model.
A speed limit change can have overall effects that go beyond the impact on the roads affected. It has sometimes been argued
In depth l 26
En Profundidad l 26
Table 1. Predictions of the effect of variations in average speed on the number of fatal accidents, according to initial average speed.Figure 1. Relationship between speed and risk of involvement in an accident with at least a person hospitalised.
0
5
10
15
20
25
30
35
-15 -10 -5 0 5 10 15 20 25
Difference with respect to average speed (km/h)
Rel
ativ
e ris
k(a
vera
ge s
peed
=1)
Urban roads (limit 60km/h) Interurban roads (limit 80-120 km/h)
Source: [Ref. 12] [Ref. 13].
3.4. Relationship between average speed and accident frequency on a stretch of road or road network
The vast majority of scientific evidence available relates to the relationship between the total number of accidents and casualties and the average speed on a stretch of road, road or road network. Among all the models proposed in the scientific literature, the most popular one is certainly the so-called ‘po-wer model’, proposed by the Swedish researcher Göran Nils-son [Ref. 15]. This model has been cited as scientific evidence by, inter alia, the European Road Safety Observatory [Ref. 16], the OECD [Ref. 17], the European Transport Safety Council [Ref. 18] and the World Health Organisation [Ref. 19].
In its complete formulation, the power model comprises six equations that relate variations in the number of accidents and in the number of road users killed or injured, to variations in the average speed of traffic. If we focus on the three ac-cident equations, the model can be summarised as follows: an increase of 1% in the average speed, all other influencing factors (including traffic flow) being kept constant, results in, approximately:
• An increase of 4% in fatal accidents.
• An increase of 3% in fatal and serious accidents.
• An increase of 2% in accidents with casualties of any severity.
The following discussion will be primarily focused on the effect of speed on the number of fatal accidents. Figure 2 shows the prediction of the model for this kind of accident.
Figure 2. Change in the number of fatal accidents (%) as a result of changes in average speed (km/h), according
to the initial average speed.
-60%
-40%
-20%
0%
20%
40%
60%
80%
-15 -10 -5 0 5 10 15
Change in average speed (km/h)
Cha
nge
in th
e nu
mbe
r of f
atal
acc
iden
ts
(%)
80km/h
90km/h
100km/h
120km/h
Source: Power Model [Ref. 15].
The power model stems from the observation of the ef-fects produced by the different speed limit changes that took place in Sweden in the late 1960s and at the beginning of the following decade. A detailed discussion of the model is outside the scope of this report. The main issue here is the validity of its predictions. Two key validations have been car-ried out so far:
• The validation by Rune Elvik et al [Ref. 20] [Ref. 21] [Ref. 22].
• The validation by Hauer and Boneson [Ref. 23], for the American association AASHTO’s Highway Safety Manual [Ref. 25].
The input data are the same in both cases: the collec-tion of 526 speed-accident estimates obtained by Elvik et al from 115 scientific studies. Each of these 526 estimates is expressed in terms of the percentage change in accidents or casualties of a certain severity produced by a certain speed change.
The conclusions of the above two validations of the power model can be summarised as follows.
• On interurban roads, the validations in general provide consistent results with the power model. Table 1 pre-sents an overview of the predictions of the power model and the two validations for two initial average speeds (80 km/h and 120 km/h), and different changes in speed. The validation by Elvik et al leads to values very close to those of the power model in all cases, while the valida-tion by Hauer and Boneson is in line with it for an initial speed of 120 km/h, and predicts larger effects when the initial speed is 80 km/h. As can be seen in the table, even very small increases in speed may lead to signifi-cant changes in fatal accidents; thus, a change from 120 to 121 km/h is expected to increase the number of fatal accidents by 3-4%.
• There are fewer studies in urban areas. Elvik et al have found a smaller effect in these cases: a 1% increase in the average speed would result in an increase of ap-proximately 2.6% in fatal accidents, instead of 4% as predicted by the power model.
• Another interesting finding of both validations is that the effects of speed seem not to depend on the coun-try where the study was conducted. In this sense, El-vik et al point out that “there is no support for the idea of de-veloping separate versions of the model for each country. This shows that the effects of speed on road safety are likely to be universal and not strongly influenced by conditions that are specific to a certain country” ([Ref. 21], page 23). The validation by Hauer and Boneson, on the other hand, concluded that “the speed-versus-crash relationship in the foreign stud-ies was similar to that in the U.S. studies” ([Ref. 24], page 26).
To conclude this discussion, it is important to note that the average speed is not the only parameter of the speed distri-bution that influences safety. In particular, there is consensus that the dispersion of speeds between vehicles is a risk fac-tor, although there are no reliable estimates of this effect. The European Road Safety Observatory summarises it as follows: “If on a particular road, the speed variance is high, this will result in less predictability, more encounters, more overtaking ma-neuvres, etc. Therefore, when the speed differences in-crease, the accident risk increases as well. […] But no reliable quantified relationship has been established for this linkage”. ([Ref. 2], page 6).
One of the most controversial effects of speed has to do with drivers’ behaviour. Many drivers claim that driving slowly becomes monotonous and that, as they increase their driving speed, their level of attention rises, with a net improvement in safety. However, it should be borne in mind that at higher speeds, the rate at which the driver must process informa-tion about the highway and its environment increases directly, demanding an extra effort that may cause fatigue. As the re-searcher Shinar points out [Ref. 8], «the act of paying attention is an effort» (p. 233), so the increase in the level of attention with increasing speed, if any, would occur in any case at the expense of an increase in the fatigue caused by driving.
To our knowledge, the only research carried out so far on the relationship between speed and the level of driver’s atten-tion was an experiment conducted in Sweden in the 1990s [Ref. 9]. Twenty-four drivers participated in the experiment, each of whom did 200km of motorway driving three times at speeds of 70km/h, 90km/h and 110km/h, respectively. The level of attention was measured through the reaction time. Despite the large differences between the three speeds test-ed, the changes observed in the reaction times were small: a 40km/h increase in speed was found to produce a reduction of 4% in the reaction time. The author concluded that «the present findings indicate that the possibility of counteracting these consequences [the increase in stopping distance due to higher speeds] by being somewhat more alert at higher speeds are not great» (p. 441).
3. Relationship between driving speed and the number and seriousness of the accidents
3.1. Introduction
We have already discussed that the precise relationship between speed and the number of accidents and victims is affected by many factors. Most past research has not sought to determine relationships between exact values of speed and accidents, but between variations of speed and variations of ac-cidents. Let us consider a particular kind of road, through which vehicles and drivers of known characteristics drive. At present, it is not possible for us to estimate the expected number of acci-dents at different given values of speed: 60, 80, 100, 120 km/h. However, research evidence does allow us to estimate the per-cent variation of accidents that should be expected when speed increases from, say, 60 to 80 km/h, or 100 to 120 km/h, while the remaining factors of influence remain constant.
There is another usual way to describe and analyse the speed problem, consisting in determining the proportion of accidents in which excessive speed (speed over the maximum permitted speed) or inappropriate speed (unsuitable for the prevailing con-ditions) appear as the main cause or a contributory factor. The main drawback of this approach is that it cannot be used to estimate the variation of accidents that should be expected from an increase or decrease in speed. Let us assume that excessive speed has been identified as the main cause of 10% of acci-dents. This does not imply that perfect compliance with speed limits would reduce accidents only by 10%. Even when the main cause of an accident is different from speed (for example, veer-ing into oncoming traffic due to a distraction), speed still influ-ences the probability of the accident occurring and of it resulting in injuries.
3.2. Individual and collective risk
Once established our goal of estimating relationships be-tween variations of average speed and variations of accidents, two basic approaches are possible:
• [Approach 1] To analyse the relationship between the driv-ing speed of a given driver and his risk of accident involve-ment.
• [Approach 2] To analyse the relationship between the average speed of the vehicles as a whole and the total number of accidents occurring on a stretch of road, road or road network.
These approaches are discussed in sections 3.3 and 3.4 respectively.
3.3. Relationship between speed and individual risk
In order to obtain representative relationships between the speed of a driver and his accident risk, we should ideally be able to count the number of accidents in which a given driver is involved when travelling at different speeds. By doing so, driver’s characteristics would remain constant, and thus have no influ-ence on the results. However, this method is not feasible, due to practical difficulties and also to the fact that accidents are rare events in most drivers’ lives.
The practical solution consists in comparing the speeds of two different populations of drivers: the population of drivers in-volved in accidents and a sample of the population of drivers travelling on the road network at a certain moment. If drivers involved in accidents travelled, on average, at higher speeds than those of drivers not involved in accidents, we would con-clude that speed significantly increase the risk of accident. If the speeds of both populations of drivers are the same, we would conclude that it does not affect risk.
The initial speeds of the vehicles involved in accidents can only be obtained by means of reconstruction procedures, which are expensive and may be prone to error. Another drawback of the method is that, since we are observing two different popula-tions of drivers, there may be characteristics of the drivers, other than speed, which may vary between both populations and bias the estimates of risks. For instance, age and sex are two fac-tors that influence accident risk and that, at the same time, may determine speed. Under these conditions, if it is found that the vehicles moving faster than the others are involved in more ac-cidents, it is not clear to what extent the result can be due to the fact that such vehicles are typically driven by younger drivers, who have a higher risk at any speed.
The first studies of the relationship between speed and indi-vidual risk were published in the U.S. in the 1960s. Among them, the best known and most frequently cited is certainly Solomon’s study [Ref. 10], in which a U-shaped curve was obtained, ac-cording to which the risk was minimal for drivers who travelled at a speed slightly above the average speed of the traffic flow, and it increased both for faster and slower drivers.
According to various authors (see e.g. [Ref. 11]), Solomon’s study has methodological inadequacies that could significantly bias its risk estimations. On the other hand, the most recent studies have not replicated the U-shaped curve. The latest avail-able study was conducted by the University of Adelaide [Ref. 12][Ref. 13] and researched the relationship between a vehicle’s speed and the likelihood of involvement in an accident with at least one person hospitalised. According to a review published by researchers Aarts and Van Schagen [Ref. 14], the results of the Adelaide study “for now […] best describe the relationship between individual vehicle speed and crash rate” (page 222). These results are shown in Figure 1; as can be seen, both risk curves —for urban and interurban roads— are monotonically in-creasing in the whole speed range.
If the initial average speed is…
And the average speed…
The number of fatal accidents varies…
According to the power model
According to the validation
by Elvik et al
According to the validation by Hauer and Boneson for the
Highway Safety Manual
80 km/h
Increases by 8 km/h +46% +48% +58%
Increases by 4 km/h +22% +22% +28%
Increases by 1 km/h +5% +5% +7%
Decreases by 1 km/h -5% -5% -7%
Decreases by 4 km/h -19% -19% -26%
Decreases by 8 km/h -34% -35% -52%
120 km/h
Increases by 8 km/h +29% +30% +32%
Increases by 4 km/h +14% +14% +15%
Increases by 1 km/h +3% +3% +4%
Decreases by 1 km/h -3% -3% -4%
Decreases by 4 km/h -13% -13% -15%
Decreases by 8 km/h -24% -25% -29%
Methodology for drawing up the table:
Power model: the equation (5.2) on page 56 of [Ref. 15] has been used. Validation by Elvik et al: a power model with exponent 4.13 is used, according to table 10 of [Ref. 21] and table 7 of [Ref. 22]. Validation by Hauer and Boneson: table 3E-2 on page 3-57 of [Ref. 25] is used, converting mph to km/h and using linear interpolation when the value
ranges diverse from those in table 2 in this report.
4. Influence of speed limits
The speed limit is certainly the most important of all the speed management tools. A speed limit change will influence safety to the extent that it leads to a change in actual driving speeds. The causal sequence would be the following: an in-crease (or decrease) in the speed limit leads to an increase (or decrease) in the mean speed of traffic, which in turn leads to an increase (or decrease) in the number of accidents and casual-ties. If we have empirical relationships between the speed limit change and the change in the mean speed, we may apply the power model - or the validations presented in the previous sec-tion - to estimate the expected impact on accidents.
Evidence show that a speed limit change leads to a change in the same direction in the actual driving speed. For example:
• The researchers Elvik, R. et al concluded that “on the average, the change in the mean speed of traffic induced by a change in speed limit appears to be around 25% of the change in speed limit” ([Ref. 20], page 93); i.e. a change in the speed limit of, for example, ±10km/h produces on the average a change in the mean speed of traffic of ±2.5km/h.
• The OECD mentiones in its report on speed management that “meta-analyses show that lowering the speed limit by 10 km/h leads to a decrease in speed of 3-4 km/h. A simi-lar effect can be expected from an increase in the speed limit” ([Ref. 17], page 100).
Thus the mean speed of traffic increases to a lesser extent than the increase in the speed limit. But this does not mean that the effect on accidents will be small. For example, the power model states that an increase from 120 to 122.5 km/h
in the mean speed would lead to a 9% increase in fatal acci-dents.
Most of the experiences in raising the speed limit confirm the negative impact on accidents. We will cite only a few relevant cases. More case studies can be found in [Ref. 19].
In Denmark, the speed limit was raised on half of the mo-torway network from 110km/h to 130km/h on 30 April 2004. On the other half, the speed limit was maintained at 110km/h. The Danish Road Directorate carried out an assessment of its impact during the 16 months after the entry into force of the change [Ref. 26]. In August 2005 the Danish Government in-troduced the point system for driving licences; as from that date it is not possible to separate the effect of both measures. On motorways where the speed limit was maintained at 110 km/h, the average speed decreased from 118.9 to 116.0km/h (by approximately 2.4%). This reduction was presumably the consequence of the measures that follow the increase in speed limit, such as: increased traffic surveillance, stricter penal-ties, awareness campaigns and speed limit signposting at the 110km/h motorways. To the contrary, on roads where the speed limit was raised, speed increased from 120.4 to 121.2km/h (by approximately 0.7%). The changes observed in the number of casualties were as follows: on motorways where the speed limit was raised: increase of 9%; on motorways where the speed limit was not changed, decrease of 40%; on all other interurban roads: decrease of 18%. According to the regression model ad-justed by the authors of the report, a change in mean speed of +/-1km/h results in about 10% increase/decrease in personal injuries. This relation is much more pronounced than the one predicted by Nilsson’s power model.
A speed limit change can have overall effects that go beyond the impact on the roads affected. It has sometimes been argued
In depth l 26
En Profundidad l 26
Table 1. Predictions of the effect of variations in average speed on the number of fatal accidents, according to initial average speed.Figure 1. Relationship between speed and risk of involvement in an accident with at least a person hospitalised.
0
5
10
15
20
25
30
35
-15 -10 -5 0 5 10 15 20 25
Difference with respect to average speed (km/h)
Rel
ativ
e ris
k(a
vera
ge s
peed
=1)
Urban roads (limit 60km/h) Interurban roads (limit 80-120 km/h)
Source: [Ref. 12] [Ref. 13].
3.4. Relationship between average speed and accident frequency on a stretch of road or road network
The vast majority of scientific evidence available relates to the relationship between the total number of accidents and casualties and the average speed on a stretch of road, road or road network. Among all the models proposed in the scientific literature, the most popular one is certainly the so-called ‘po-wer model’, proposed by the Swedish researcher Göran Nils-son [Ref. 15]. This model has been cited as scientific evidence by, inter alia, the European Road Safety Observatory [Ref. 16], the OECD [Ref. 17], the European Transport Safety Council [Ref. 18] and the World Health Organisation [Ref. 19].
In its complete formulation, the power model comprises six equations that relate variations in the number of accidents and in the number of road users killed or injured, to variations in the average speed of traffic. If we focus on the three ac-cident equations, the model can be summarised as follows: an increase of 1% in the average speed, all other influencing factors (including traffic flow) being kept constant, results in, approximately:
• An increase of 4% in fatal accidents.
• An increase of 3% in fatal and serious accidents.
• An increase of 2% in accidents with casualties of any severity.
The following discussion will be primarily focused on the effect of speed on the number of fatal accidents. Figure 2 shows the prediction of the model for this kind of accident.
Figure 2. Change in the number of fatal accidents (%) as a result of changes in average speed (km/h), according
to the initial average speed.
-60%
-40%
-20%
0%
20%
40%
60%
80%
-15 -10 -5 0 5 10 15
Change in average speed (km/h)
Cha
nge
in th
e nu
mbe
r of f
atal
acc
iden
ts
(%)
80km/h
90km/h
100km/h
120km/h
Source: Power Model [Ref. 15].
The power model stems from the observation of the ef-fects produced by the different speed limit changes that took place in Sweden in the late 1960s and at the beginning of the following decade. A detailed discussion of the model is outside the scope of this report. The main issue here is the validity of its predictions. Two key validations have been car-ried out so far:
• The validation by Rune Elvik et al [Ref. 20] [Ref. 21] [Ref. 22].
• The validation by Hauer and Boneson [Ref. 23], for the American association AASHTO’s Highway Safety Manual [Ref. 25].
The input data are the same in both cases: the collec-tion of 526 speed-accident estimates obtained by Elvik et al from 115 scientific studies. Each of these 526 estimates is expressed in terms of the percentage change in accidents or casualties of a certain severity produced by a certain speed change.
The conclusions of the above two validations of the power model can be summarised as follows.
• On interurban roads, the validations in general provide consistent results with the power model. Table 1 pre-sents an overview of the predictions of the power model and the two validations for two initial average speeds (80 km/h and 120 km/h), and different changes in speed. The validation by Elvik et al leads to values very close to those of the power model in all cases, while the valida-tion by Hauer and Boneson is in line with it for an initial speed of 120 km/h, and predicts larger effects when the initial speed is 80 km/h. As can be seen in the table, even very small increases in speed may lead to signifi-cant changes in fatal accidents; thus, a change from 120 to 121 km/h is expected to increase the number of fatal accidents by 3-4%.
• There are fewer studies in urban areas. Elvik et al have found a smaller effect in these cases: a 1% increase in the average speed would result in an increase of ap-proximately 2.6% in fatal accidents, instead of 4% as predicted by the power model.
• Another interesting finding of both validations is that the effects of speed seem not to depend on the coun-try where the study was conducted. In this sense, El-vik et al point out that “there is no support for the idea of de-veloping separate versions of the model for each country. This shows that the effects of speed on road safety are likely to be universal and not strongly influenced by conditions that are specific to a certain country” ([Ref. 21], page 23). The validation by Hauer and Boneson, on the other hand, concluded that “the speed-versus-crash relationship in the foreign stud-ies was similar to that in the U.S. studies” ([Ref. 24], page 26).
To conclude this discussion, it is important to note that the average speed is not the only parameter of the speed distri-bution that influences safety. In particular, there is consensus that the dispersion of speeds between vehicles is a risk fac-tor, although there are no reliable estimates of this effect. The European Road Safety Observatory summarises it as follows: “If on a particular road, the speed variance is high, this will result in less predictability, more encounters, more overtaking ma-neuvres, etc. Therefore, when the speed differences in-crease, the accident risk increases as well. […] But no reliable quantified relationship has been established for this linkage”. ([Ref. 2], page 6).
One of the most controversial effects of speed has to do with drivers’ behaviour. Many drivers claim that driving slowly becomes monotonous and that, as they increase their driving speed, their level of attention rises, with a net improvement in safety. However, it should be borne in mind that at higher speeds, the rate at which the driver must process informa-tion about the highway and its environment increases directly, demanding an extra effort that may cause fatigue. As the re-searcher Shinar points out [Ref. 8], «the act of paying attention is an effort» (p. 233), so the increase in the level of attention with increasing speed, if any, would occur in any case at the expense of an increase in the fatigue caused by driving.
To our knowledge, the only research carried out so far on the relationship between speed and the level of driver’s atten-tion was an experiment conducted in Sweden in the 1990s [Ref. 9]. Twenty-four drivers participated in the experiment, each of whom did 200km of motorway driving three times at speeds of 70km/h, 90km/h and 110km/h, respectively. The level of attention was measured through the reaction time. Despite the large differences between the three speeds test-ed, the changes observed in the reaction times were small: a 40km/h increase in speed was found to produce a reduction of 4% in the reaction time. The author concluded that «the present findings indicate that the possibility of counteracting these consequences [the increase in stopping distance due to higher speeds] by being somewhat more alert at higher speeds are not great» (p. 441).
3. Relationship between driving speed and the number and seriousness of the accidents
3.1. Introduction
We have already discussed that the precise relationship between speed and the number of accidents and victims is affected by many factors. Most past research has not sought to determine relationships between exact values of speed and accidents, but between variations of speed and variations of ac-cidents. Let us consider a particular kind of road, through which vehicles and drivers of known characteristics drive. At present, it is not possible for us to estimate the expected number of acci-dents at different given values of speed: 60, 80, 100, 120 km/h. However, research evidence does allow us to estimate the per-cent variation of accidents that should be expected when speed increases from, say, 60 to 80 km/h, or 100 to 120 km/h, while the remaining factors of influence remain constant.
There is another usual way to describe and analyse the speed problem, consisting in determining the proportion of accidents in which excessive speed (speed over the maximum permitted speed) or inappropriate speed (unsuitable for the prevailing con-ditions) appear as the main cause or a contributory factor. The main drawback of this approach is that it cannot be used to estimate the variation of accidents that should be expected from an increase or decrease in speed. Let us assume that excessive speed has been identified as the main cause of 10% of acci-dents. This does not imply that perfect compliance with speed limits would reduce accidents only by 10%. Even when the main cause of an accident is different from speed (for example, veer-ing into oncoming traffic due to a distraction), speed still influ-ences the probability of the accident occurring and of it resulting in injuries.
3.2. Individual and collective risk
Once established our goal of estimating relationships be-tween variations of average speed and variations of accidents, two basic approaches are possible:
• [Approach 1] To analyse the relationship between the driv-ing speed of a given driver and his risk of accident involve-ment.
• [Approach 2] To analyse the relationship between the average speed of the vehicles as a whole and the total number of accidents occurring on a stretch of road, road or road network.
These approaches are discussed in sections 3.3 and 3.4 respectively.
3.3. Relationship between speed and individual risk
In order to obtain representative relationships between the speed of a driver and his accident risk, we should ideally be able to count the number of accidents in which a given driver is involved when travelling at different speeds. By doing so, driver’s characteristics would remain constant, and thus have no influ-ence on the results. However, this method is not feasible, due to practical difficulties and also to the fact that accidents are rare events in most drivers’ lives.
The practical solution consists in comparing the speeds of two different populations of drivers: the population of drivers in-volved in accidents and a sample of the population of drivers travelling on the road network at a certain moment. If drivers involved in accidents travelled, on average, at higher speeds than those of drivers not involved in accidents, we would con-clude that speed significantly increase the risk of accident. If the speeds of both populations of drivers are the same, we would conclude that it does not affect risk.
The initial speeds of the vehicles involved in accidents can only be obtained by means of reconstruction procedures, which are expensive and may be prone to error. Another drawback of the method is that, since we are observing two different popula-tions of drivers, there may be characteristics of the drivers, other than speed, which may vary between both populations and bias the estimates of risks. For instance, age and sex are two fac-tors that influence accident risk and that, at the same time, may determine speed. Under these conditions, if it is found that the vehicles moving faster than the others are involved in more ac-cidents, it is not clear to what extent the result can be due to the fact that such vehicles are typically driven by younger drivers, who have a higher risk at any speed.
The first studies of the relationship between speed and indi-vidual risk were published in the U.S. in the 1960s. Among them, the best known and most frequently cited is certainly Solomon’s study [Ref. 10], in which a U-shaped curve was obtained, ac-cording to which the risk was minimal for drivers who travelled at a speed slightly above the average speed of the traffic flow, and it increased both for faster and slower drivers.
According to various authors (see e.g. [Ref. 11]), Solomon’s study has methodological inadequacies that could significantly bias its risk estimations. On the other hand, the most recent studies have not replicated the U-shaped curve. The latest avail-able study was conducted by the University of Adelaide [Ref. 12][Ref. 13] and researched the relationship between a vehicle’s speed and the likelihood of involvement in an accident with at least one person hospitalised. According to a review published by researchers Aarts and Van Schagen [Ref. 14], the results of the Adelaide study “for now […] best describe the relationship between individual vehicle speed and crash rate” (page 222). These results are shown in Figure 1; as can be seen, both risk curves —for urban and interurban roads— are monotonically in-creasing in the whole speed range.
If the initial average speed is…
And the average speed…
The number of fatal accidents varies…
According to the power model
According to the validation
by Elvik et al
According to the validation by Hauer and Boneson for the
Highway Safety Manual
80 km/h
Increases by 8 km/h +46% +48% +58%
Increases by 4 km/h +22% +22% +28%
Increases by 1 km/h +5% +5% +7%
Decreases by 1 km/h -5% -5% -7%
Decreases by 4 km/h -19% -19% -26%
Decreases by 8 km/h -34% -35% -52%
120 km/h
Increases by 8 km/h +29% +30% +32%
Increases by 4 km/h +14% +14% +15%
Increases by 1 km/h +3% +3% +4%
Decreases by 1 km/h -3% -3% -4%
Decreases by 4 km/h -13% -13% -15%
Decreases by 8 km/h -24% -25% -29%
Methodology for drawing up the table:
Power model: the equation (5.2) on page 56 of [Ref. 15] has been used. Validation by Elvik et al: a power model with exponent 4.13 is used, according to table 10 of [Ref. 21] and table 7 of [Ref. 22]. Validation by Hauer and Boneson: table 3E-2 on page 3-57 of [Ref. 25] is used, converting mph to km/h and using linear interpolation when the value
ranges diverse from those in table 2 in this report.
4. Influence of speed limits
The speed limit is certainly the most important of all the speed management tools. A speed limit change will influence safety to the extent that it leads to a change in actual driving speeds. The causal sequence would be the following: an in-crease (or decrease) in the speed limit leads to an increase (or decrease) in the mean speed of traffic, which in turn leads to an increase (or decrease) in the number of accidents and casual-ties. If we have empirical relationships between the speed limit change and the change in the mean speed, we may apply the power model - or the validations presented in the previous sec-tion - to estimate the expected impact on accidents.
Evidence show that a speed limit change leads to a change in the same direction in the actual driving speed. For example:
• The researchers Elvik, R. et al concluded that “on the average, the change in the mean speed of traffic induced by a change in speed limit appears to be around 25% of the change in speed limit” ([Ref. 20], page 93); i.e. a change in the speed limit of, for example, ±10km/h produces on the average a change in the mean speed of traffic of ±2.5km/h.
• The OECD mentiones in its report on speed management that “meta-analyses show that lowering the speed limit by 10 km/h leads to a decrease in speed of 3-4 km/h. A simi-lar effect can be expected from an increase in the speed limit” ([Ref. 17], page 100).
Thus the mean speed of traffic increases to a lesser extent than the increase in the speed limit. But this does not mean that the effect on accidents will be small. For example, the power model states that an increase from 120 to 122.5 km/h
in the mean speed would lead to a 9% increase in fatal acci-dents.
Most of the experiences in raising the speed limit confirm the negative impact on accidents. We will cite only a few relevant cases. More case studies can be found in [Ref. 19].
In Denmark, the speed limit was raised on half of the mo-torway network from 110km/h to 130km/h on 30 April 2004. On the other half, the speed limit was maintained at 110km/h. The Danish Road Directorate carried out an assessment of its impact during the 16 months after the entry into force of the change [Ref. 26]. In August 2005 the Danish Government in-troduced the point system for driving licences; as from that date it is not possible to separate the effect of both measures. On motorways where the speed limit was maintained at 110 km/h, the average speed decreased from 118.9 to 116.0km/h (by approximately 2.4%). This reduction was presumably the consequence of the measures that follow the increase in speed limit, such as: increased traffic surveillance, stricter penal-ties, awareness campaigns and speed limit signposting at the 110km/h motorways. To the contrary, on roads where the speed limit was raised, speed increased from 120.4 to 121.2km/h (by approximately 0.7%). The changes observed in the number of casualties were as follows: on motorways where the speed limit was raised: increase of 9%; on motorways where the speed limit was not changed, decrease of 40%; on all other interurban roads: decrease of 18%. According to the regression model ad-justed by the authors of the report, a change in mean speed of +/-1km/h results in about 10% increase/decrease in personal injuries. This relation is much more pronounced than the one predicted by Nilsson’s power model.
A speed limit change can have overall effects that go beyond the impact on the roads affected. It has sometimes been argued
26Second quarter 2011
MINISTERIODEL INTERIOR
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MINISTERIODEL INTERIOR
Nacional Road Safety Observatory from the Observatory
In depth National Road Safety ObservatoryJosefa Valcárcel, 2828071 Madridwww.dgt.es Nipo: 128-11-027-3
National Road Safety Observatory
Current state of knowledge on the relationship between speed and road safety.
Evolution of traffic speeds in spain
1. Introduction
The impact of traffic speed on safety is the focus of intense debate between scientists, road users and policy-makers. The goal of this brief report is to summarise the most important scien-tific literature in this field of research.
Increasing traffic speed may have several positive effects, the most important one being the reduction in travel times. The enor-mous technical advances achieved in the past decades in the design of roads, vehicles and traffic management, along with the improvement in the behaviour of users, have made it possible to increase traffic speeds while, at the same time, reducing the risk of accident and injury. The decrease in travel times has important benefits to productivity and provides users with more spare time for other activities.
Speed has also important negative consequences, such as energy consumption, environmental impact and road accidents and injuries. This brief report focuses solely on the relationship between speed and safety.
There are several reasons why speed affects safety. Many of them are of a physical nature: the distance required for fully stop-ping a vehicle increases with speed; therefore, the probability of avoiding a collision with another vehicle or obstacle in an emer-gency situation decreases with speed. On the other hand, inju-ries and property damage in a crash increase with impact speed, which, at the same time, increases with the speeds of vehicles before the collision.
As will be summarised in section 3, empirical research pro-vides clear evidence of the negative impact of speed: greater speed increases the risk of accidents and injuries, both at the individual level —relationship between the speed of a given driver and his risk— and at the aggregated level —relationship between the average speed of traffic flow and the total number of accidents and injuries—.
Reports from national and international road safety organisa-tions concur that speed is, together with alcohol consumption and failure to wear seat belt, the main risk factor of accident and injury [Ref. 1]. According to the European Road Safety Observatory’s re-ports, speed is an essential contributory factor in around 10% of all accidents and 30% of fatal accidents [Ref. 2]. Similar figures are cited in the World Health Organization’s world report [Ref. 3]. In Spain, speed, whether excessive or inappropriate, was cited as a contributory factor in 13% of the injury accidents registered by traffic police officers in 2009; this percentage rose to 31% in fatal accidents [Ref. 4].
Speed management plays a key role in road safety strategies based on the so-called Safety System approach, such as the Swedish Vision Zero or the Dutch Sustainable Safety [Ref. 5]. One of the fundamental principles of this approach is that the traffic system should be able to tolerate human errors and limitations, without them resulting in deaths or serious injuries. In order to achieve this goal, it is necessary to manage crash energy, so that no user is exposed to forces greater than those determined by
physical vulnerability. Thus, the concept of safe speed emerges, defined as the value of traffic speed that can ensure the protection of users. Safe speed depends on the characteristics of road in-frastructure and traffic flow; for example, it is lower on rural roads than on motorways, and it is also lower on pedestrian areas than on wide avenues where flows of pedestrians are segregated from motor vehicles.
This brief report also includes a discussion about the impact of speed limits, as the basic tool to manage speed (section 4).
2. Factors affected by speed
The precise relationship between speed and the number of accidents and victims is affected by many factors related to the road, the vehicles and the drivers. This affirmation is easy to check when one compares the performance of modern motorways with that of rural two-lane, two-way roads. On motorways, average speeds are far higher, but the number of fatalities, for the same amount of distance travelled, is about three times lower. One should not conclude from this observation that higher speeds contribute to reducing accidents, but rather that there are many other factors —in our example, mainly related to road design— that affect the precise number of accidents and victims that is expected at a given value of speed.
Active safety systems in vehicles, such as anti-lock braking system (ABS) and electronic stability control (ESC), also affect the relationship between speed and safety. Assuming that a driver’s behaviour remains the same —in particular, that his choice of speed is independent from the characteristics and safety systems of his car—, these devices reduce the risk of being involved in a crash.
In order to study the impact of speed, independently from the influence of other factors, we must suppose that a given driver, driving a fixed car through a fixed road segment, increases his speed. What changes should we expect then?
The most important changes have to do with vehicle dyna-mics: [Ref. 6]. Firstly, the stopping distance increases with speed, due to the increase of both the distance travelled during the time of perception and reaction, and the distance travelled during braking. Secondly, as speed increases, the gap between travelling speed and the maximum speed determined by tyre-road friction is narrowed, thus increasing the risk of veering off road on a bend and the risk of hydroplaning in rain conditions.
Speed also influences accident severity, i.e. the probability that someone involved in a collision will be injured. At the moment of the collision, the amount of energy to be dissipated depends on the squares of the impact velocities of the vehicles involved (kinectic energy). An increase in this energy leads to an increase in the prob-ability of injuries among the people involved in the accident —as ve-hicle occupants or pedestrians—. The relationship between impact speed and injury risk has been amply proven in scientific literature (see e.g. [Ref. 7]).
that an increase in the speed limit on high-capacity roads could indeed lead to an increase in the number of casualties on these roads, but at the same time, to a shift of journeys from rural roads - more dangerous roads - so that the system-wide net balance is positive. This argument comes mainly from some studies con-ducted in the U.S., such as [Ref. 27]. However, the latest research has not found these effects. Grabowski and Morrisey [Ref. 28] examined the overall impacts of the two speed limit changes in the U.S. in 1987 and 1995; the following effects were found:
• Increase in the speed limit from 55 mph to 65mph (year 1987): 16-17% increase in the number of fatalities on the roads affected; non-significant effect on the interurban roads that were not affected.
• Increase in the speed limit to 70-75 mph or higher (year 1995): 36-37% increase in the number of fatalities on the roads affected; 7-11% increase on the interurban roads that were not affected.
Therefore, the authors did not find a reduction of fatalities in those roads where the speed limit was not changed. In fact, the second result above shows an increase in fatalities, a result that may be linked to the speed spillover or generalization theory, ac-cording to which the changes in average speeds on certain roads may extend their effect to other parts of the road network.
5. Driving speeds in Spain
Drivers’ behaviour towards speed is usually studied in free-flow situations, where the prevailing conditions are such that the driver can choose any speed: lack of roadside checks, low tra-ffic density, favourable road design, road surface in good condi-tion and good weather conditions. The available data in Spain show that, under free-flow conditions, between 38% and 59% of the drivers travel above the maximum speed limit; in between 17% and 37% of the cases, the scale of the offence is more than 10km/h.
Table 2. Average speeds of light vehicles in Spain under free-flow conditions. 2010.
ROAD TYPEAverage speed (km/h)
% over the limit
% more than
10km/h over the
limit
Motorway 117.7 52% 27%
Dual carriage-way 113.9 38% 17%
Trunk road. Speed limit 90 km/h
96.3 51% 32%
Trunk road. Speed limit 100 km/h
98.4 59% 37%
Source: National Road Safety Observatory, study carried out by The Univer-sity Institute for Automobile Research (INSIA) [Ref. 29].
The recent evolution has been clearly positive. Free-flow indi-cators are currently only available for the years 2009 and 2010. To carry out a time analysis, we must use other two indica-tors concerning all traffic conditions, and not just traffic-calmed situations under favourable conditions. For instance, the Ministry of Public Works performs measurements of average speeds at a sample of locations in the road network of its ownership. These measurements show that the percentage of light vehicles trave-lling over 120 km/h on motorways has fallen from 27.99% in 2003 to 17.08% in 2010. On trunk roads, the percentage of vehicles travelling over 100 km/h has fallen from 17.35% to 12.30% over the same period.
• With regard to the individual risk, the most comprehen-sive study is the one conducted by the University of Adelaide, which shows that the risk of involvement in a serious crash increases steadily with speed, both on urban and interurban roads.
• From the perspective of the collective risk, Göran Nilsson’s power model is the most commonly used model. The power model is based on the following qualitative principles:
• A change in speed leads to a change in the same di-rection in crash/casualties frequency.
• The greater the change in speed, the greater the change in crash/casualties frequency.
The available evidence confirms the aforementioned prin-ciples. It has been found that the relationship between speed and safety is very consistent: if average speed in-creases (or decreases), the number of fatal accidents al-most always increases (or decreases). From a quantitative point of view, the validations carried out have confirmed that, on interurban roads, the predictions of the power model are valid; in this way, the rule according to which
a 1% increase in average speed leads to an increase of approximately 4% in the number of fatal accidents can be accepted. On urban roads, evidence suggests that the im-pact of speed could be lower than the one predicted by the power model, but it is in any case significant.
Evidence showed, moreover, that the relationship between speed and accidents does not significantly depend on the country or region concerned.
• With regard to the impact of the speed limit, most evidence indicates that the mean speed of traffic changes in the same direction as the speed limit, however, the magnitude of the change is smaller (around 25%). The available evidence shows that an increase in the speed limit leads to an increase in accidents and casualties.
• Spain has seen significant decreases in speed across the entire interurban road network and not just in controlled sec-tions. Taking into account all scientific evidence available, it is plausible to assume that this decline in speed must have made a major contribution to the recent reduction in the number of accidents.
• (Ref. 1) European Transport Safety Council (2010) Tackling the three main killers on the roads. A priority for the forthcoming EU Road Safety Action Programme. PIN Flash N.16. Brussels.
• (Ref. 2) European Road Safety Observatory (2006) Speeding. Re-trieved January 20, 2007 from www.erso.eu.
• (Ref. 3) World Health Organization (2004) Informe mundial sobre pre-vención de los traumatismos causados por el tránsito.
• (Ref. 4) Dirección General de Tráfico, Observatorio Nacional de Seguri-dad Vial (2010) Las principales cifras de la siniestralidad vial. Spain 2009.
• (Ref. 5) OECD (2008) Towards Zero: Achieving Ambitious Road Safe-ty Targets through a Safe System Approach. OECD, Paris.
• (Ref. 6) Aparicio Izquierdo, F. (2010) Velocidad: factor de riesgo en accidentes de tráfico. XV Jornada de la Cátedra ADA de Seguridad de los Vehículos y del Tráfico. ETS de Ingenieros Industriales de Madrid. 30 November 2010. Available on: http://www.insia-upm.es/xv--jorna-da-de-la-catedra-ada-ntc40.asp?vuelta=1 (visited on 04/05/2010).
• (Ref. 7) NHTSA (2001) Tire pressure monitoring system FMVSS No.138. Preliminary economic assessment. Office of regulatory analy-sis and evaluation. Plans and policy. National Highway Traffic Safety Administration.
• (Ref. 8) Shinar, D. (1998) Speed and crashes: a controversial topic and an elusive relationship. En Transportation Research Board (1998). Managing speed: a review of current practice for setting and enforcing speed limits. Special Report 254.
• (Ref. 9) Törnros, J. (1995) Effect of driving speed on reaction time during motorway driving. Accident Analysis and Prevention, Vol. 27, No.4, pp. 435-442.
• (Ref. 10) Solomon, D. R. (1964). Accidents on main rural highways related to speed, driver and vehicle. Federal Highway Administration, Washington, DC.
• (Ref. 11) Hauer, E. (2009) Speed and safety. Transportation Research Record 2103, pp. 10-17.
• (Ref. 12) Kloeden, C. N.; Ponte, G.; McLean, A. J. (2001) Travelling speed and the rate of crash involvement on rural roads.
• (Ref. 13) Kloeden, C. N., McLean, A. J. & Glonek, G. (2002) Reanaly-sis of travelling speed and the rate of crash involvement in Adelaide South Australia.
• (Ref. 14) Aarts, L.; Van Schagen (2006) Driving speed and the risk of road crashes: A review. Accident Analysis and Prevention 38 (2006) 215–224.
• (Ref. 15) Nilsson, G. (2004). Traffic safety dimensions and the Power Model to describe the effect of speed on safety. Bulletin 221. Lund Institute of Technology, Department of Technology and Society, Traffic Enginering, Lund.
• (Ref. 16) European Road Safety Observatory (2006) Speeding.
• (Ref. 17) OCDE, ITF, ECMT (2006) Speed management.
• (Ref. 18) ETSC (2008), “Managing speed: Towards safe and sustain-able road transport”.
• (Ref. 19) World Health Organisation, FIA Foundation, Global Road Safety Partnership, The World Bank (2008) Speed management. A road safety manual for decision-makers and practitioners.
• (Ref. 20) Elvik, R.; Christensen, P.; Amundsen, A. (2004) Speed and road accidents. An evaluation of the Power Model. TOI Report 740/2004.
• (Ref. 21) Elvik, R. (2009) The Power Model of the relationship be-tween speed and road safety. Update and new analyses. TOI Report 1034/2009.
• (Ref. 22) Cameron, M.; Elvik, R. (2010) Nilsson’s Power Model con-necting speed and road trauma: Applicability by road type and alter-native models for urban roads. Accident Analysis and Prevention 42 (2010) 1908–1915.
• (Ref. 23) Hauer, E.; Boneson, J.A. (2008) An empirical examination of the relationship between speed and road accidents. Harkey, D.L. et al (2008) Accident Modification Factors for Traffic Engineering and ITS improvements. National Cooperative Highway Research Programme, Report NCHRP-617. Transportation Research Board.
• (Ref. 24) Harkey, D.L.; Srinivasan, R.; Back, J.; Council, F.M.; Eccles, K.; Lefler, N.; Gross, F.; Persaud, B.; Lyon, C.; Hauer, E.; Boneson, J.A. (2008) Accident Modification Factors for Traffic Engineering and ITS improvements. Transportation Research Board. NCHRP Report 617.
• (Ref. 25) American Association of State Highway and Transportation Officials (2010) Highway Safety Manual. 1st edition.
• (Ref. 26) Reiff, L. K.; Foldager, I; Hels, T.; Hemdorff, S.; Lund, H. (2008). 130 km/t på motorveje. Virkning på faktisk hastighed, uheld og miljøbelastning. Rapport 337. Vejdirektoratet, København.
• (Ref. 27) Lave, C.; Elias, P. (1993) Did the 65 mph speed limit save lives? Accident Analysis and Prevention, 26, pp. 49-62.
• (Ref. 28) Grabowski, D.C.; Morrisey, M.A. (2007) Systemwide impli-cations of the repeal of the national maximum speed limit. Accident Analysis and Prevention 39, pp. 180–189.
• (Ref. 29) Instituto Universitario de Investigación del Automóvil (2010) Medición de velocidad de flujo libre en la red vial española. Study car-ried out for the Observatorio Nacional de Seguridad Vial.
• (Ref. 30) Ministerio de Fomento (2011) http://www.fomen-to.gob.es/NR/rdonlyres/FBD5E4E5-D096-41A5-8F29-DD-0FA3501C44/105162/serie_20022010.pdf.
Table 3. Evolution of speeds in points of measurement of the Ministry of Public Works. Period 2003-2010.
Indicator 2003 2004 2005 2006 2007 2008 2009 2010
% Light vehicles travelling over 120km/h on dual carriageways 27.99% 25.16% 26.17% 19.68% 20.60% 18.92% 15.71% 17.08%
% Light vehicles travelling over 100km/h on trunk roads 17.35% 15.25% 16.73% 12.00% 12.45% 9.54% 12.23% 12.30%
Source: Ministry of Public Works [Ref. 30].
Another available indicator is the average speed on sections controlled by fixed speed cameras, in which, according to the information collected by the National Road Safety Observatory, the percentage of vehicles travelling over the speed limit fell from 28-29% in 2006 to 9-13% in 2010, with a very similar evolution on dual carriageways and trunk roads.
The two types of data above —speeds on a sample of sec-tions of the network and speeds on sections controlled by speed cameras— suggest the following two conclusions: firstly, the policies of recent years, such as the point system for driving li-cences and the plan for installation of speed cameras, have been successful in reducing speeds; secondly, this reduction seems to have taken place across the entire network, and not just in controlled sections.
Although a precise assessment has not yet been made, it is plausible to assume, on the basis of all the scientific pieces of evi-
dence cited in previous sections, that the fall of the driving speed which has occurred over the last few years must have played a very significant role in the reduction of the accident rate in Spain since 2003 (down by 54% for road accident fatalities over 2003-2010).
6. Conclusions
This report has presented a general overview of the current knowledge about the relationship between speed and safety. The following is a summary of the main conclusions:
• The relationship between speed and safety can be analysed from the perspective of the individual risk —relationship be-tween the speed of a driver and his risk— or of the collec-tive risk —relationship between the average speed of the vehicles as a whole and the total number of accidents—.
References
26Second quarter 2011
MINISTERIODEL INTERIOR
www.dgt.es
MINISTERIODEL INTERIOR
Nacional Road Safety Observatory from the Observatory
In depth National Road Safety ObservatoryJosefa Valcárcel, 2828071 Madridwww.dgt.es Nipo: 128-11-027-3
National Road Safety Observatory
Current state of knowledge on the relationship between speed and road safety.
Evolution of traffic speeds in spain
1. Introduction
The impact of traffic speed on safety is the focus of intense debate between scientists, road users and policy-makers. The goal of this brief report is to summarise the most important scien-tific literature in this field of research.
Increasing traffic speed may have several positive effects, the most important one being the reduction in travel times. The enor-mous technical advances achieved in the past decades in the design of roads, vehicles and traffic management, along with the improvement in the behaviour of users, have made it possible to increase traffic speeds while, at the same time, reducing the risk of accident and injury. The decrease in travel times has important benefits to productivity and provides users with more spare time for other activities.
Speed has also important negative consequences, such as energy consumption, environmental impact and road accidents and injuries. This brief report focuses solely on the relationship between speed and safety.
There are several reasons why speed affects safety. Many of them are of a physical nature: the distance required for fully stop-ping a vehicle increases with speed; therefore, the probability of avoiding a collision with another vehicle or obstacle in an emer-gency situation decreases with speed. On the other hand, inju-ries and property damage in a crash increase with impact speed, which, at the same time, increases with the speeds of vehicles before the collision.
As will be summarised in section 3, empirical research pro-vides clear evidence of the negative impact of speed: greater speed increases the risk of accidents and injuries, both at the individual level —relationship between the speed of a given driver and his risk— and at the aggregated level —relationship between the average speed of traffic flow and the total number of accidents and injuries—.
Reports from national and international road safety organisa-tions concur that speed is, together with alcohol consumption and failure to wear seat belt, the main risk factor of accident and injury [Ref. 1]. According to the European Road Safety Observatory’s re-ports, speed is an essential contributory factor in around 10% of all accidents and 30% of fatal accidents [Ref. 2]. Similar figures are cited in the World Health Organization’s world report [Ref. 3]. In Spain, speed, whether excessive or inappropriate, was cited as a contributory factor in 13% of the injury accidents registered by traffic police officers in 2009; this percentage rose to 31% in fatal accidents [Ref. 4].
Speed management plays a key role in road safety strategies based on the so-called Safety System approach, such as the Swedish Vision Zero or the Dutch Sustainable Safety [Ref. 5]. One of the fundamental principles of this approach is that the traffic system should be able to tolerate human errors and limitations, without them resulting in deaths or serious injuries. In order to achieve this goal, it is necessary to manage crash energy, so that no user is exposed to forces greater than those determined by
physical vulnerability. Thus, the concept of safe speed emerges, defined as the value of traffic speed that can ensure the protection of users. Safe speed depends on the characteristics of road in-frastructure and traffic flow; for example, it is lower on rural roads than on motorways, and it is also lower on pedestrian areas than on wide avenues where flows of pedestrians are segregated from motor vehicles.
This brief report also includes a discussion about the impact of speed limits, as the basic tool to manage speed (section 4).
2. Factors affected by speed
The precise relationship between speed and the number of accidents and victims is affected by many factors related to the road, the vehicles and the drivers. This affirmation is easy to check when one compares the performance of modern motorways with that of rural two-lane, two-way roads. On motorways, average speeds are far higher, but the number of fatalities, for the same amount of distance travelled, is about three times lower. One should not conclude from this observation that higher speeds contribute to reducing accidents, but rather that there are many other factors —in our example, mainly related to road design— that affect the precise number of accidents and victims that is expected at a given value of speed.
Active safety systems in vehicles, such as anti-lock braking system (ABS) and electronic stability control (ESC), also affect the relationship between speed and safety. Assuming that a driver’s behaviour remains the same —in particular, that his choice of speed is independent from the characteristics and safety systems of his car—, these devices reduce the risk of being involved in a crash.
In order to study the impact of speed, independently from the influence of other factors, we must suppose that a given driver, driving a fixed car through a fixed road segment, increases his speed. What changes should we expect then?
The most important changes have to do with vehicle dyna-mics: [Ref. 6]. Firstly, the stopping distance increases with speed, due to the increase of both the distance travelled during the time of perception and reaction, and the distance travelled during braking. Secondly, as speed increases, the gap between travelling speed and the maximum speed determined by tyre-road friction is narrowed, thus increasing the risk of veering off road on a bend and the risk of hydroplaning in rain conditions.
Speed also influences accident severity, i.e. the probability that someone involved in a collision will be injured. At the moment of the collision, the amount of energy to be dissipated depends on the squares of the impact velocities of the vehicles involved (kinectic energy). An increase in this energy leads to an increase in the prob-ability of injuries among the people involved in the accident —as ve-hicle occupants or pedestrians—. The relationship between impact speed and injury risk has been amply proven in scientific literature (see e.g. [Ref. 7]).
that an increase in the speed limit on high-capacity roads could indeed lead to an increase in the number of casualties on these roads, but at the same time, to a shift of journeys from rural roads - more dangerous roads - so that the system-wide net balance is positive. This argument comes mainly from some studies con-ducted in the U.S., such as [Ref. 27]. However, the latest research has not found these effects. Grabowski and Morrisey [Ref. 28] examined the overall impacts of the two speed limit changes in the U.S. in 1987 and 1995; the following effects were found:
• Increase in the speed limit from 55 mph to 65mph (year 1987): 16-17% increase in the number of fatalities on the roads affected; non-significant effect on the interurban roads that were not affected.
• Increase in the speed limit to 70-75 mph or higher (year 1995): 36-37% increase in the number of fatalities on the roads affected; 7-11% increase on the interurban roads that were not affected.
Therefore, the authors did not find a reduction of fatalities in those roads where the speed limit was not changed. In fact, the second result above shows an increase in fatalities, a result that may be linked to the speed spillover or generalization theory, ac-cording to which the changes in average speeds on certain roads may extend their effect to other parts of the road network.
5. Driving speeds in Spain
Drivers’ behaviour towards speed is usually studied in free-flow situations, where the prevailing conditions are such that the driver can choose any speed: lack of roadside checks, low tra-ffic density, favourable road design, road surface in good condi-tion and good weather conditions. The available data in Spain show that, under free-flow conditions, between 38% and 59% of the drivers travel above the maximum speed limit; in between 17% and 37% of the cases, the scale of the offence is more than 10km/h.
Table 2. Average speeds of light vehicles in Spain under free-flow conditions. 2010.
ROAD TYPEAverage speed (km/h)
% over the limit
% more than
10km/h over the
limit
Motorway 117.7 52% 27%
Dual carriage-way 113.9 38% 17%
Trunk road. Speed limit 90 km/h
96.3 51% 32%
Trunk road. Speed limit 100 km/h
98.4 59% 37%
Source: National Road Safety Observatory, study carried out by The Univer-sity Institute for Automobile Research (INSIA) [Ref. 29].
The recent evolution has been clearly positive. Free-flow indi-cators are currently only available for the years 2009 and 2010. To carry out a time analysis, we must use other two indica-tors concerning all traffic conditions, and not just traffic-calmed situations under favourable conditions. For instance, the Ministry of Public Works performs measurements of average speeds at a sample of locations in the road network of its ownership. These measurements show that the percentage of light vehicles trave-lling over 120 km/h on motorways has fallen from 27.99% in 2003 to 17.08% in 2010. On trunk roads, the percentage of vehicles travelling over 100 km/h has fallen from 17.35% to 12.30% over the same period.
• With regard to the individual risk, the most comprehen-sive study is the one conducted by the University of Adelaide, which shows that the risk of involvement in a serious crash increases steadily with speed, both on urban and interurban roads.
• From the perspective of the collective risk, Göran Nilsson’s power model is the most commonly used model. The power model is based on the following qualitative principles:
• A change in speed leads to a change in the same di-rection in crash/casualties frequency.
• The greater the change in speed, the greater the change in crash/casualties frequency.
The available evidence confirms the aforementioned prin-ciples. It has been found that the relationship between speed and safety is very consistent: if average speed in-creases (or decreases), the number of fatal accidents al-most always increases (or decreases). From a quantitative point of view, the validations carried out have confirmed that, on interurban roads, the predictions of the power model are valid; in this way, the rule according to which
a 1% increase in average speed leads to an increase of approximately 4% in the number of fatal accidents can be accepted. On urban roads, evidence suggests that the im-pact of speed could be lower than the one predicted by the power model, but it is in any case significant.
Evidence showed, moreover, that the relationship between speed and accidents does not significantly depend on the country or region concerned.
• With regard to the impact of the speed limit, most evidence indicates that the mean speed of traffic changes in the same direction as the speed limit, however, the magnitude of the change is smaller (around 25%). The available evidence shows that an increase in the speed limit leads to an increase in accidents and casualties.
• Spain has seen significant decreases in speed across the entire interurban road network and not just in controlled sec-tions. Taking into account all scientific evidence available, it is plausible to assume that this decline in speed must have made a major contribution to the recent reduction in the number of accidents.
• (Ref. 1) European Transport Safety Council (2010) Tackling the three main killers on the roads. A priority for the forthcoming EU Road Safety Action Programme. PIN Flash N.16. Brussels.
• (Ref. 2) European Road Safety Observatory (2006) Speeding. Re-trieved January 20, 2007 from www.erso.eu.
• (Ref. 3) World Health Organization (2004) Informe mundial sobre pre-vención de los traumatismos causados por el tránsito.
• (Ref. 4) Dirección General de Tráfico, Observatorio Nacional de Seguri-dad Vial (2010) Las principales cifras de la siniestralidad vial. Spain 2009.
• (Ref. 5) OECD (2008) Towards Zero: Achieving Ambitious Road Safe-ty Targets through a Safe System Approach. OECD, Paris.
• (Ref. 6) Aparicio Izquierdo, F. (2010) Velocidad: factor de riesgo en accidentes de tráfico. XV Jornada de la Cátedra ADA de Seguridad de los Vehículos y del Tráfico. ETS de Ingenieros Industriales de Madrid. 30 November 2010. Available on: http://www.insia-upm.es/xv--jorna-da-de-la-catedra-ada-ntc40.asp?vuelta=1 (visited on 04/05/2010).
• (Ref. 7) NHTSA (2001) Tire pressure monitoring system FMVSS No.138. Preliminary economic assessment. Office of regulatory analy-sis and evaluation. Plans and policy. National Highway Traffic Safety Administration.
• (Ref. 8) Shinar, D. (1998) Speed and crashes: a controversial topic and an elusive relationship. En Transportation Research Board (1998). Managing speed: a review of current practice for setting and enforcing speed limits. Special Report 254.
• (Ref. 9) Törnros, J. (1995) Effect of driving speed on reaction time during motorway driving. Accident Analysis and Prevention, Vol. 27, No.4, pp. 435-442.
• (Ref. 10) Solomon, D. R. (1964). Accidents on main rural highways related to speed, driver and vehicle. Federal Highway Administration, Washington, DC.
• (Ref. 11) Hauer, E. (2009) Speed and safety. Transportation Research Record 2103, pp. 10-17.
• (Ref. 12) Kloeden, C. N.; Ponte, G.; McLean, A. J. (2001) Travelling speed and the rate of crash involvement on rural roads.
• (Ref. 13) Kloeden, C. N., McLean, A. J. & Glonek, G. (2002) Reanaly-sis of travelling speed and the rate of crash involvement in Adelaide South Australia.
• (Ref. 14) Aarts, L.; Van Schagen (2006) Driving speed and the risk of road crashes: A review. Accident Analysis and Prevention 38 (2006) 215–224.
• (Ref. 15) Nilsson, G. (2004). Traffic safety dimensions and the Power Model to describe the effect of speed on safety. Bulletin 221. Lund Institute of Technology, Department of Technology and Society, Traffic Enginering, Lund.
• (Ref. 16) European Road Safety Observatory (2006) Speeding.
• (Ref. 17) OCDE, ITF, ECMT (2006) Speed management.
• (Ref. 18) ETSC (2008), “Managing speed: Towards safe and sustain-able road transport”.
• (Ref. 19) World Health Organisation, FIA Foundation, Global Road Safety Partnership, The World Bank (2008) Speed management. A road safety manual for decision-makers and practitioners.
• (Ref. 20) Elvik, R.; Christensen, P.; Amundsen, A. (2004) Speed and road accidents. An evaluation of the Power Model. TOI Report 740/2004.
• (Ref. 21) Elvik, R. (2009) The Power Model of the relationship be-tween speed and road safety. Update and new analyses. TOI Report 1034/2009.
• (Ref. 22) Cameron, M.; Elvik, R. (2010) Nilsson’s Power Model con-necting speed and road trauma: Applicability by road type and alter-native models for urban roads. Accident Analysis and Prevention 42 (2010) 1908–1915.
• (Ref. 23) Hauer, E.; Boneson, J.A. (2008) An empirical examination of the relationship between speed and road accidents. Harkey, D.L. et al (2008) Accident Modification Factors for Traffic Engineering and ITS improvements. National Cooperative Highway Research Programme, Report NCHRP-617. Transportation Research Board.
• (Ref. 24) Harkey, D.L.; Srinivasan, R.; Back, J.; Council, F.M.; Eccles, K.; Lefler, N.; Gross, F.; Persaud, B.; Lyon, C.; Hauer, E.; Boneson, J.A. (2008) Accident Modification Factors for Traffic Engineering and ITS improvements. Transportation Research Board. NCHRP Report 617.
• (Ref. 25) American Association of State Highway and Transportation Officials (2010) Highway Safety Manual. 1st edition.
• (Ref. 26) Reiff, L. K.; Foldager, I; Hels, T.; Hemdorff, S.; Lund, H. (2008). 130 km/t på motorveje. Virkning på faktisk hastighed, uheld og miljøbelastning. Rapport 337. Vejdirektoratet, København.
• (Ref. 27) Lave, C.; Elias, P. (1993) Did the 65 mph speed limit save lives? Accident Analysis and Prevention, 26, pp. 49-62.
• (Ref. 28) Grabowski, D.C.; Morrisey, M.A. (2007) Systemwide impli-cations of the repeal of the national maximum speed limit. Accident Analysis and Prevention 39, pp. 180–189.
• (Ref. 29) Instituto Universitario de Investigación del Automóvil (2010) Medición de velocidad de flujo libre en la red vial española. Study car-ried out for the Observatorio Nacional de Seguridad Vial.
• (Ref. 30) Ministerio de Fomento (2011) http://www.fomen-to.gob.es/NR/rdonlyres/FBD5E4E5-D096-41A5-8F29-DD-0FA3501C44/105162/serie_20022010.pdf.
Table 3. Evolution of speeds in points of measurement of the Ministry of Public Works. Period 2003-2010.
Indicator 2003 2004 2005 2006 2007 2008 2009 2010
% Light vehicles travelling over 120km/h on dual carriageways 27.99% 25.16% 26.17% 19.68% 20.60% 18.92% 15.71% 17.08%
% Light vehicles travelling over 100km/h on trunk roads 17.35% 15.25% 16.73% 12.00% 12.45% 9.54% 12.23% 12.30%
Source: Ministry of Public Works [Ref. 30].
Another available indicator is the average speed on sections controlled by fixed speed cameras, in which, according to the information collected by the National Road Safety Observatory, the percentage of vehicles travelling over the speed limit fell from 28-29% in 2006 to 9-13% in 2010, with a very similar evolution on dual carriageways and trunk roads.
The two types of data above —speeds on a sample of sec-tions of the network and speeds on sections controlled by speed cameras— suggest the following two conclusions: firstly, the policies of recent years, such as the point system for driving li-cences and the plan for installation of speed cameras, have been successful in reducing speeds; secondly, this reduction seems to have taken place across the entire network, and not just in controlled sections.
Although a precise assessment has not yet been made, it is plausible to assume, on the basis of all the scientific pieces of evi-
dence cited in previous sections, that the fall of the driving speed which has occurred over the last few years must have played a very significant role in the reduction of the accident rate in Spain since 2003 (down by 54% for road accident fatalities over 2003-2010).
6. Conclusions
This report has presented a general overview of the current knowledge about the relationship between speed and safety. The following is a summary of the main conclusions:
• The relationship between speed and safety can be analysed from the perspective of the individual risk —relationship be-tween the speed of a driver and his risk— or of the collec-tive risk —relationship between the average speed of the vehicles as a whole and the total number of accidents—.
References
