The Bikesim model was in Copenhagen connected to realtime data streams from mobile camera based bicycle volume sensors and from traffic lights on a bicycle corridor. A stable and accurate travel time could be predicted using Monte Carlo simulation using these data. It facilitated traffic management of the flow of cyclists on a busy corridor in the city.
How does the system collect/generate data: Images that are collected by camera’s are combined with data from loops and processed in a simulation that predicts the flow of cyclists.
Lessons learned / factor of success: Other data collection technologies were tested for the purpose of traffic management. In many cases, data quality falls short. Information of a large number of cyclists is needed to get accurate and stable measurements. Data collection from radar, cellphones (apps), wifi/Bluetooth identification aren’t rich enough for traffic management purposes.
Impacts assessment / results: Users appreciated the efforts to develop traffic management for cyclists. Whether the traffic management was actually effective was not measured. Whether it contributed to an increased number of cyclists is too early to determine.
