Drivers’ Decision Making of Overtaking Strategies of Cyclists on Rural Roads–A Driving Simulator Experiment
Conference poster, 2019

Cyclists’ involvement in road crashes has not been improving with the same magnitude as other modes of transport. Especially, the interactions between cyclists and motorized traffic can end up with the most severe types of crashes. To improve the safety of these interactions, a thorough understanding of road users’ decisions and behaviours is first needed. In this study, the authors focus on drivers’ overtaking manoeuvres of cyclists on rural roads. The main objective of this study is to develop a model that can predict drivers’ decisions whether to perform a flying or an accelerative overtaking manoeuvre when approaching a cyclist in the presence of oncoming traffic. A driving simulator study was designed to collect trajectory data of the overtaking vehicle, cyclist, and oncoming traffic. Drivers’ characteristics data was collected using surveys. In total, 37 drivers participated, each of them performing 7 overtaking manoeuvres. Out of 259 overtaking manoeuvres, 168 were flying and 91 were accelerative. Two binary logistic regression models were developed and estimated. In the two models, the time-to-collision and the driver’s speed significantly affect the decision on the overtaking manoeuvre type. In the first model, the correlations among the observations of the same driver were captured through the drivers’ characteristics. In the second model, these correlations were captured through a driver specific error term. The overall performance is 87.7% and 94.9% for the first and second models, respectively. In the paper the authors discuss the usability of each model for policy making, system design, and system evaluation.

Author

Haneen Farah

Giulio Bianchi Piccinini

Chalmers, Mechanics and Maritime Sciences, Vehicle Safety

Marco Dozza

Olycksanalys och prevention

Makoto Itoh

Transportation Research Board 98th Annual MeetingTransportation Research Board
Washington, ,

Safety in automated driving (ADS): modelling interaction between road-users and automated vehicles

Chalmers, 2018-01-01 -- 2019-12-31.

Driving Forces

Sustainable development

Areas of Advance

Transport

Subject Categories

Transport Systems and Logistics

Infrastructure Engineering

Applied Psychology

Vehicle Engineering

More information

Created

5/27/2019