As mobile devices came into wide use, it became practical and popular to collect travel data in personal logs by using a satellite navigation system such as the GPS. The spatial trajectory generated by the vehicle contains valuable information including real-time traffic situation, transportation environments, and driver’s behaviors. Many studies have been conducted to extract meaningful information from this trend.
On the other hand, the number of bicyclists is steadily growing for several decades, and the bicycle related crashes and bicycling safety are getting more concerns. In order to enhance bicycle safety, various factors affecting bicycle crash risk have been studied and proposed. The moving path generated by a bicycle was also investigated by previous researchers, however the spatial characteristics of the bicycle were not completely explored yet in the aspect of the bicycle crash risk and the bicyclists’ behavioral characteristics on the road.
In order to improve the bicycle safety, we attempted to extract both the kinematic and the spatial features from a large number of the bicycle trajectories and to investigate their significance as the crash risk factors. The trajectories were collected on the segregated, i.e., free from motor vehicle traffics, two-way riverside bicycle track by using GPS units. As the kinematic features, the speed and the heading change were estimated and as the spatial ones, several distance measures were evaluated on two summarized trajectories of the GPS data in both directions. The summary trajectories were constructed using the principal curve method. The extracted features were applied to the regression analysis in order to confirm their correlation to the bicycle crash risk. Our results show that the kinematic features were rather irrelevant while the spatial ones had meaningful correlation with the crash risk and thus confirm their usefulness in crash risk analysis.
Secondly, the visualization method for the bicycle tr...