Improving GIS-based Models for Bicycling Speed Estimations
Artikel i vetenskaplig tidskrift, 2019
This work combines tools and measures from two recent bikeability modelling studies. One is an urban form based study of bicycle route networks, grasping issues related to geometrical directness of routes and various measures of accessibility and density. The other calculates likely speeds based on horizontal and vertical geometry of routes. The latter model uses an advanced statistical model to grasp dependence between adjacent road segments. The new combined model is estimated using GPS tracking of real bicycle trips in combination with GIS-based data of bicycle route networks and of the local contexts of the routes.
More in detail, the new model includes parameters estimated for the following covariates:
• route geometry (by slope and by horizontal curvature)
• intersection impedances derived from type of junction (by presence of signal-crossings and by kinds of crossing streets categorized by amounts of traffic)
• type of bicycle-route (bicycle lane in street, separate bicycle lane, combined walk- and bicycle lane or mixed-use streets)
• kind of surface (smooth surface or gravel)
• density of entrances along route (a proxy for slower bicycling due to urban/vibrant context)
The modelling is based on so-called Markov-dependence, including that the covariates are used to estimate continuous speed profiles along entire routes, and not only average speed levels on road segments seen separate and independent. Through this, the new model results in more realistic speed estimations than the previous models. The paper presents the result from applying the tool on a sample of bicycle routes in Gothenburg and compares the results with analyses from previous models and with empirical data of bicycling along the same routes.
Transportation Research Procedia
23521457 (ISSN) 23521465 (eISSN)Vol. 42 85-99
Building Futures (2010-2018)
Transportteknik och logistik
Sannolikhetsteori och statistik