This paper discusses driving styles while overtaking a vulnerable road user who moves along the shoulder in urban roads. Based on the data obtained from an experiment in pre-defined conditions (combinations of four main effects: vehicle’s initial speed, lane width of the road, vulnerable road users’ type, and location in the shoulder) with an immersive driving simulator, we analyzed four different driving styles of drivers while approaching and passing the objects. It is shown that drivers took avoidance maneuvers even if there was no clear risk of collision to vulnerable road users. The results showed that the drivers tended to have a unique perception about the lateral passing gap and overtaking strategy with two worth notice groups: overcaution drivers and reckless drivers. The road characteristic has a statistically significant effect for all types of drivers. Moreover, the effect of the vehicle’s initial speed on overtaking strategy and the effect of vulnerable road user location on minimum lateral passing gap are statistically significant. The findings provide some implications for the development of automotive safety systems that can reduce the risk of overtaking maneuvers in urban areas.
To increase the acceptance and willingness of customers in using advanced driver assistance systems and autonomous vehicles, one of the best solutions is to reproduce the driving behavior of humans. In this regard, estimating risk based on driver behavior is a priority. An index of perceptual risk estimation by drivers toward pedestrians approaching and overtaking maneuvers is proposed herein. Risk estimation comprises longitudinal and lateral risk estimations. The index is verified using maneuver data obtained from a driving simulator. It is discovered that drivers with different driving styles have different risk index ranges. The index may be used to classify drivers for selecting the appropriate response from an assisting system.
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