Simulating Bicycle

Traffic in Salzburg

- Background Information

Martin Loidl

Department of Geoinformatics, Z_GIS

University of Salzburg

martin.loidl@sbg.ac.at | http://gicycle.wordpress.com

Bicycle Promotion

Urban agglomerations suffer from negative effects of -

still growing! - car traffic

Environmental impact

Financial/economic impact (externalities!)

Social impact

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reuters.com salzburg24.at salzburg.orf.at

Bicycle Promotion

Bicycle as efficient, urban mode of transport

Cheap

Accessible

Environmentally friendly

Healthy

Flexible

Fast within 5-10km

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Investments

Infrastructure, events, information

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stadt-salzburg.com

salzburg24.at

radlkarte.info

Benchmarking?

Accidents

Accidents reported by police are geocoded

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Statistical Population?

Lack of Data

“Such a lack of reliable and high-resolution data

about bicycle-specific factors is hence one of the most

central issues in research into cycling, as it often

hampers to get in-depth knowledge on the factors that

significantly influence both bicycle use and cycling

accidents.” (Vandenbulcke-Plasschaert 2011: 20)

“Without information about how much cycling is being

done, statements about how many cycle crashes occur

are of limited use.” (OECD 2013: 63)

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VANDENBULCKE-PLASSCHAERT, G. 2011. Spatial analysis of bicycle use and accident risks for cyclists. PhD, Université catholique de Louvain.OECD 2013. Cycling, Health and Safety. In: TØRSLØV, N. (ed.). Paris: ITF-OECD Working Group on Cycling Safety.

Data needed

To know [estimate] when + where + how many

Benchmarking („What effect do my initiatives have?“)

Demand-based planning („Where is infrastructure most

needed?“)

Traffic management („How can I guide bicyclists to

efficiently distribute all traffic participants in the network?“)

Routing information („At which point of time are certain

connections suitable/to be avoided?“)

Accident analysis („What is the risk to be involved in an

accident?“)

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What we have so far I

Epidemiological analysis (prevalence, risk) based on

mostly weak, highly aggregated data

Study from 2012 (ISI-indexed) uses data from study from

2008

Study from 2008 refers to data from the European

Comission, published in 2002

This publication is an annual report for 2000

The annual report uses data which where nationally

collected between 1970 and 1997

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https://gicycle.wordpress.com/2014/02/11/where-do-the-data-come-from

What we have so far II

Traffic models for motorized individual

traffic and partly for public transport

Obligation to register cars (know exact

number of vehicles)

Large intrest in data telematic systems

No traffic models for bicyclists and

pedestrians

No registration

Lower demand (better: direct economic

pressure)

Many influental variables

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Passenger car

Public transport

mvv-muenchen.de

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http://www.mtreiber.de/MicroApplet_html5

What we have so far III

Traffic flow simulation

What we have so far IV

Single counting systems along major routes

Don‘t necessarily allow for global information

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Stadt Salzburg

What we want to have

Estimation of flows per segment per time interval

Different scenarios for environment and agents

We provide the following data:

Road network as routeable graph with all available

attributes

Socio-demographic data in 1.000/250m grid

LULC data (digital cadastral map)

POIs

Data from 6 counters

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