The Impact of Type of Automation, Scenarios, and Driving Style on Motorcyclist Willingness to Cross a Junction - L.C. Kheng; J. Karjanto; N. Md. Yusof; A.F.H. Zulkifli; S. Sulaiman; N. Mustaffa; M.Z. Baharom; Z.M. Jawi; A.A. Ab. Rashid; K.A. Abu Kassim (Journal of the Society of Automotive Engineers Malaysia, 2022)
This paper discusses whether knowing the automation, appearance, and driving style of an oncoming vehicle (automated and manual) affects a motorcyclist’s decision to cross a junction. In a video- based experiment with 54 participants, two vehicles (Perodua Myvi) with different colors are presented as an automated vehicle (grey) and a manually-driven vehicle (white), respectively. A lookalike and rotating LiDAR was developed and placed on the top of one of the vehicles. Both vehicles went through four scenarios involving a junction with two driving styles (assertive and defensive). The participants were asked to indicate whether they would cross the junction with the approaching vehicle (automated and manual) at a distance ranging from 100 m to 25 m. The results showed no significant influence of automation, scenario, and driving style on the motorcyclist’s willingness to cross a junction. However, we found that the motorcyclists indicated a higher willingness to cross when the automated vehicle is approaching than when the manually-driven vehicle is at a distance of 50 m and 25 m. We conclude by discussing the limitation and the future study.