BIKEPRINT – IN DEPTH ANALYSIS OF CYCLIST BEHAVIOUR AND CYCLE NETWORK PERFORMANCE USING GPS-TRACKING TECHNOLOGY



BIKEPRINT – IN DEPTH ANALYSIS OF CYCLIST BEHAVIOUR AND CYCLE NETWORK PERFORMANCE USING GPS-TRACKING TECHNOLOGY

Authors

Dirk Bussche, DAT.Mobility and NHTV University of Applied Science, Paul Van De Coevering, TU Delft and NHTV University of Applied Science

Description

The BikePRINT framework translates GPS-tracks of cyclists into relevant policy indicators such as: delays for cyclists at junctions, routes and detours, average speeds and behavioural change as response to improvements of bicycle infrastructure.

Abstract

Bicycle use is on the rise in most western cities. For reasons of sustainability, liveability, health and accessibility many local governments support this trend and need thorough insight into bicycle behaviour and network performance.

To make this information available, we developed an analysis framework which is based on extensive GPS-tracking. The EU-sponsored BikePRINT application, provides policy information about network performances such as: heat maps, delays at junctions, route choice (and detours), average speeds and the number of cyclists per day. By analysing detours, we also gained insight in preferred (and avoided) links which helps to understand abstract route choice parameters and also supports the traffic planner in getting information about the attractiveness of cycle infrastructure in his or her city.

These kinds of indicators can make bicycle planning and policy more targeted and efficient. When developing BikePRINT, we learned that many current (car-) road network performance Indicators make no sense for cyclists. To reduce this knowledge gap, dedicated indicators for cycling have been developed.
Final part of the BikePRINT research is to understand how people react to improvements of cycle infrastructure. How does accessibility increase? What is the impact on present cyclists? How many car drivers would change to cycle mode? This insight is directly accessible for policy makers in a quick scan model and can later be used to improve multi-modal traffic models.

Although analysing GPS tracks provides a rich additional source of information, it is neither intended nor suitable to replace traffic models or count data. We consider both sources of information as complementary.
We hope that BikePRINT contributes to better bicycle planning and policy and will be used to increase cycle use in many cities.

Publisher

Association for European Transport