November 12th - 13th, 2014 – City of Xi’An, China “PIARC International Seminar on Disaster...

November 12th - 13th, 2014 – City of Xi’An, China“PIARC International Seminar on Disaster Prevention and Mitigation

Technologies and Inputs from ITS in Network Operations”

Probe vehicle: a low cost innovative and promising solution for road networks monitoring

J. Ehrlich, IFSTTAR, FranceA. Bacelar, CEREMA, France

PIARC TC21 “Road Network Operation”

12-13 nov 14 1Probe vehicles

Infrastructure monitoring : a major issue

• High level objectives : to make road always available, efficient and safe– Need to increase road network efficiency and road safety– Need for real time information such as to make good decision

• Objectives of infrastructure monitoring : to provide up to date information that characterize the road network state– Traffic information : travel time, congestion, accident, hazard– Weather and environmental condition– Road condition : state, usage

• Targets– Public authorities– Road network operators– Road users (drivers, passengers, pedestrians etc.)


12-13 nov 14 Probe vehicles 3

12-13 nov 14 Probe vehicles 4

ECU ECU ECU

ECU

ECUPasserelleDIAG

OBD

Bus CAN

A new paradigm

• Classical approach for road network monitoring– The infrastructure plays the role of event detector

• Magnetic loops under road surface, camera, sensors (T°, H% etc) on roadside

– Advantage/drawback• No dependence to vehicle technology• Expensive : investment, maintenance cost

• A breakdown : connected vehicle and in-vehicle sensors• New approach

– The vehicle plays the role of event detector• Probe Data Vehicle/Floating Car Data (FCD)

– Advantage/drawback• Dependence to vehicle technology (old vehicles are offside)• Low investment on infrastructure


Principles

• Collect data from different sources– Sources are the probe vehicles (without excluding information from

road equipment or other sources)

• Aggregate data– According to their location (road segment, area)– According to their type (speed, acceleration etc)– An possibly other criteria …

• Analyze data– Filtering, fusion, statistic etc to extract/estimate the required

information

• Provide the end user with the information– Must be accurate, reliable, trustworthy and on time (not obsolete)– Must be adapted to the target (road operator, driver, pedestrian etc)


Overall system architecture• Three main entities

– Probe vehicles– Road Side Units (not mandatory)– Backoffice centers

• Upward/downward link– Direct link from FCD to backoffice– Indirect link via Road Side Unit

(beacon)Backoffice

Road side equipement

Floating car data

VehiclesVMS

Radio set


• Communication technologies– Long distance (cellular) : 2G, 2,5G, 3G, 4G

– Short distance : DSRC, WAVE (mobile Wifi :802.11p)– Broadcasted : Radio RDS, DAB (for downsteam link only)


Key technologies

• Vehicles– Sensors, Actuators– Electronic Control Unit (ECU)– Digital Network (CAN bus)– Communication plateform– Human man Interface (HMI)

• Infrastructure– Road side unit– VMS

• Backoffice center– Medium Power Computer

} … or Smartphone

} … or nothing

… or the Cloud}12-13 nov 14 8Probe vehicles

Key technologies : high cost vs. low cost architectures

Backoffice


Floating car data

VehiclesVMS

Radio set


Backoffice

SmartphoneIn car

Smartphone in car

• High cost– Expensive for the driver

(recent vehicles only)– Expensive for the road

operator (need for roadside unit, VMS, radio services)

– Compliant with standard– Powerful

• Low cost– Cheap for the driver (based

on Smartphone)– Cheaper for the road

operator (no needs for roadside unit)

– Based most often on proprietary solutions

– Less powerful12-13 nov 14 9Probe vehicles

Application to Road Network Monitoring

• USA Classification– Mobility– Reducing the environmental impact– Management of wheather condition

• EU classification– Traffic Management Measures Estimation– Dynamic Speed Harmonization, and– Operational Maintenance Decision Support Systems

• JP classification– 17 Applications classified according their degree of maturity

• Towards an unified vision …– US-JP-EU task force on Probe Data (US DOT, MLIT, ERTICO)


Application classification : a proposal from TC21

• Type of application– Mobility– Road safety– Weather condition monitoring– Road distress monitoring– Environmental application– Advanced knowledge survey

• Maturity– 1 = deployed now– 2 = possible deployment within 5 years– 3 = possible deployment past 5 years

• Cost– Low: requires Smartphone with integrated sensors (GPS, accelerometer)– Medium : requires in-vehicle sensors, actuators, communication platform– High : Medium + external sources and possibly Road Side Unit


Mobility applications

Applications Maturity

Travel time estimation on a route by aggregating the times achieved by the probes vehicles on road segments

1Low cost

WorldwideDetection and characterization of congestion (position, length, average speed congestion) by aggregating low speed or zero speed in a given area.

1Low cost

Worldwide

Information on the availability of a route: in emergency situations (natural disaster, etc.), vehicle sensors help to characterize the availability of a route to provide first aid or any other emergency services

1Low cost

JP


Road safety applicationApplications MaturityDynamic harmonization of speeds and headways: the objective is to provide speed and distance headway recommendations in response to situations of congestion, incidents or adverse traffic situations.

1,2Low cost

World wideQueue alert: vehicles which detect that they are located in a queue (or traffic jam) transmit alerts to upstream vehicles so they can reduce their speed to avoid an accident (collision).

2Low cost

JaponStationary Vehicles alert: a vehicle stopped in the road transmits alerts to prevent upstream vehicles to avoid an accident. Alerts can also be transmitted by witness vehicles.

2Medium cost

US, JP, EUDetection of potentially hazardous areas: recurrent abnormal behavior of vehicles approaching a curve such as longitudinal, transversal acceleration yaw rate, speeds outside of normal values could be interpreted as warning signs for the road network operator. Then a thorough analysis of the situation could make it possible to conclude that the geometry of the road is intrinsically dangerous or that speed limit is unsuited and thus allow the road network operator to apply necessary countermeasures.

2,3Medium cost

EU, JP


Wheather condition monitoring

7-nov-13 Connected Vehicle 14

Applications MaturityRain detection: observation in a given area of vehicles that operates simultaneously their windscreen wipers can interpreted as warning signs of rain.

2Medium cost

Ice detection: observation on a given area of vehicles that repetitively and unexpectedly trigger their ESP/ABS or ASR is information that can interpreted as be the warning signs of ice.

2Medium cost

Fog detection : the presence in a given area that vehicles turn on their headlights and fog lights simultaneously is an information that can characterize the presence of fog

2Medium cost

Distance of visibility in the fog: thanks to computer-vision techniques using on-board cameras it is possible to estimate the distance of visibility in fog in front of the vehicle. Then the aggregation of information from multiple vehicles allows to calculate an estimate of the distance of visibility on a given area or itinerary. This information could also be merged with information automatically downloaded from weather stations located in some airfields (e.g. METAR messages).

3High cost

Road distress monitoring

7-nov-13 Connected Vehicle 15

Application MaturityRoad surface diagnosis: the information to detect zones of reduced skid resistance are the same as those mentioned above for the detection of ice. Recurring triggering of ABS, ESP and ASR systems on a given location are indicators that could be interpreted to detect area with reduced skid resistance. However their fusion with meteorological data is necessary to discriminate the causes: rain, snow, ice or degradation of the road pavement or combination of both causes.

2High cost

Detection of degradation of the road surface: the presence in a given location of vehicles subject to outsized vertical accelerations may indicate road surface degradation like ruts, potholes, ruptures, cracks causing vertical movements of the car body. The probe vehicle must be equipped with sensors sensitive enough to detect these movements. Recent studies shows that sensors (accelerometers) integrated into some Smartphones have the required sensitivity.

3Low/Medium

cost

Road geometry unsuited to speed limits: see the section «Detection of potentially hazardous areas ". The same information can be used to diagnose an inappropriate speed limit or dangerous road geometry (radius of curvature, cant).

2,3Medium cost

Environnemental application

Applications MaturityEnvironmental assessment: the ability of newer vehicles to measure their own emissions (CO2 or other GHG sensor) and calculate their own fuel consumption should provide global environmental assessments across a network, a city or geographic area.

3Medium

Cost

Eco driving recommendations: from information from probe vehicles as mentioned above, recommendations can be provided to improve both driving safety (section 1.4.5.2) and fuel consumption. These eco driving advises concern mainly gear ratios, speed profiles (acceleration, deceleration) etc.

2Medium

Cost


Advanced knowledge survey

Applications MaturitySurvey on O/D : Tracking itineraries of vehicles cohort on specified areas help to get better knowledge of the flow (O / D) and refine predictive models of traffic. The Anonymization of the information is a crucial issue but techniques are now available to preserve privacy.

1Low Cost


Accuracy

• An open issue … accuracy of provided information depends on– Location accuracy

• Accuracy provided by GSM seems too low, GPS recommended

– Probe vehicle data frequency– Proportion of vehicle in the traffic

• Literature : 1 to 5% ? 2 to 20 vehicles/15 minutes/road segment

– Possible bias due to the type of FCD (taxis, trucks etc).• Behavior dependent

• Expectations– A relative error of 10 % could be a reasonable goal (?)


Exemple : FCD for travel time

• FCD travel time are raw measurements, which have to be smoothed• Compared to classical sensors, FCD have a good road coverage with small

cost, but low penetration rate for the present time• Travel time with FCD have the same evolution than reference ; anyway we

can observe a shift in the curves due to difference between FCD segments and the reference segments


Example : V-TRAFIC the trafic information service from Mediamobile

• Mediamobile : a private company based in France– specialized in aggregating travel related information from different

sources• Data sources (Europe)

– Data collected from public or private operators (sensors measurement)– Floating car data from one million vehicles and 20 million mobile phone user

• Services provided (depending on the countries)– Actual travel speed on all major roads,– Alert for accidents, roadwork and road closures,– Dynamic routing and estimated travel times,– Road weather events: slippery roads, heavy rain and snow alert,– Animals warnings where wild animals are likely to cross,– Touristic events that may impact on traffic and parking availability,


V-TRAFIC (con’t) : broadcasting protocols and media

• TMC (Trafic Message Channel) via RDS (Radio Data System)

• Connected data link with embedded navigation system (make use of a SIM card)

• Digital Radio DAB – Already deployed in

Northern Europe

• Internet12-13 nov 14 21Probe vehicles

V-TRAFIC main challenge : Collecting and merging data from a wide variety of sources

• Translation of data into a common geographic reference– Beside the fact that each provider use its own geographic

reference

• Data synchronization– Beside the fact that each data provider has its own

frequency and information update

• Aggregation of real-time data but also calendar data and statistics – to provide estimates of changes in the short term (H + n)

and the long term (J + n)


Conclusion• Floating car data is a very promising concept for Road

Operation Network• Low cost solution can be deployed in emerging countries

– But only for application that don’t requires in-vehicle sensors data and road side equipement

• Some research question are still open– Link between accuracy, latency time and probe vehicle penetration

rate : a great research field for researchers

• Some legal issues are not yet clearly solved– Data ownership.

• We are still at the “stone age” of FCD– Now : application are mainly dedicated to traffic information– In the near future : FCD application will cover all domain of Road

Network Operation12-13 nov 14 23Probe vehicles

November 12th - 13th, 2014 – City of Xi’An, China“PIARC International Seminar on Disaster Prevention and Mitigation

Technologies and Inputs from ITS in Network Operations”

Thank you for your [email protected]

More information in the final TC21 report and V-TRAFFIC case study

(to be published by end 2015)


November 12th - 13th, 2014 – City of Xi’An, China “PIARC International Seminar on Disaster...

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