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Evasive action characteristics of motorcycle riders towards occluded-surprise and expected pedestrians: A pedestrian mock-up study
P.K. Akinapalli, , H. Dia
Published in Elsevier Ltd
2022
Volume: 90
   
Pages: 412 - 424
Abstract
Evasive action performance of motorcycle riders plays a vital role in the prevention of road crashes. In possible conflicting scenarios, motorcycle riders need to respond quickly and perform evasive actions successfully to prevent collisions with other vulnerable road users such as crossing pedestrians. To study the motorcycle rider behavior in conflicts with occluded and visible pedestrians, we designed four mock-up pedestrian scenarios, which includes, two surprise scenarios, one stationary scenario, and one expected scenario. Riders’ responses to the conflicts were measured using instrumented vehicle's trajectory. Most riders preferred deceleration over swerving at the beginning of the interaction, followed by swerving at manageable speeds. Further, the analysis of riders’ deceleration rates revealed that a linear relationship existed between the deceleration rates and time to collisions (TTC). The study also analyzed the riders’ responses using repeated-measures analysis of variance (RM-ANOVA) to check for the effect of scenario type on deceleration rates. Results indicated that scenario type significantly affected the mean deceleration rates. Further, RM-ANOVA analysis carried out on the jerk behavior of motorcycle riders indicated that there was a significant effect of scenario type on the jerk behavior. Motorcycle riders’ jerks varied linearly with TTC and motorcyclists employ relatively higher decelerations and jerks when faced with pedestrians emerging suddenly from occluded locations such as from the blind spots formed due to parked vehicles. This study helps in understanding motorcycle rider behavior in critical situations and shows the need for assistive evasive systems for motorcycle riders to mitigate collisions with other vulnerable road users. © 2022 Elsevier Ltd
About the journal
JournalTransportation Research Part F: Traffic Psychology and Behaviour
PublisherElsevier Ltd
ISSN13698478