Drivers overtaking bicyclists—An examination using naturalistic driving data. (June 2018) - Feng, Fred; Bao, Shan; Hampshire, Robert C.; Delp, Michael
Highlights: Naturalistic driving data provide valuable information about driver-bicyclist interactions. Drivers adapted overtaking maneuver to lane marking, bike lane, traffic, and lane width. With a marked bike lane drivers crossed dashed non-center lines less than solid centerlines. Nearly 8% of the overtaking occurred when the drivers were distracted. Drivers manipulating cell phones made less lane-crossing when overtaking bicyclists. Abstract: This paper demonstrates a unique and promising approach to study driver-bicyclist interactions from a driver's perspective by using in-vehicle sensory data from naturalistic driving studies. A total of 4789 events of drivers overtaking bicyclists were extracted from an existing naturalistic driving study in Michigan, United States. The vehicle lateral placement at the time of passing bicyclists was used as a surrogate safety measure. A number of factors were examined, including the lane marking type, the presence of a bike lane or paved shoulder, the presence of traffic, lane width, and driver distraction. Some notable findings include that (1) when a bike lane or paved shoulder was present, a dashed non-center line (i.e., a dashed line separating two lanes in the same direction) was associated with significantly less vehicle lane-crossing and closer distance to the bike lane/shoulder compared to a solid centerline; (2) an alarming 7.8% of the overtaking occurred when the drivers were distracted within five seconds prior to passing bicyclists. From a bicyclist's perspective, that translates to one overtaken by a distracted driver for every thirteen times they are overtaken. In addition, drivers manipulating a cell phone were associated with significantly less vehicle lane-crossing when overtaking bicyclists. The results of this work could be potentially used by traffic engineers, policymakers and legislators to support the designs of better road infrastructures, education programs, policies, and traffic laws that aim to improve the safety of all road users. The quantitative results could also be potentially used as a baseline to develop and benchmark automated vehicle technologies on how to interact with bicyclists on the road.