Safety effect analysis of motorcycle V2I collision warning system

Abstract

Connected vehicle technology can help the driver make decisions, improve awareness of the road environment, and thereby possibly enhance traffic safety. This study explored the impact of a motorcycle vehicle‐to‐infrastructure (V2I) warning system on road safety through a field trial of a Motorcycle Safety Warning System (MSWS). This study used principal component analysis, K‐means, and ordinal logistic regression to explore the effects of the MSWS. After system activation, the road safety level (RSL) improved at 50% of the field trial sites. This study provides a reference for evaluating RSLs through the composite index of this study and verifies that the V2I warning signs of the MSWS provide a certain degree of improvement of motorcycle traffic safety. A V2I system like the MSWS can be used to collect data on driving behaviours in a short period for safety effect analysis, as compared to crash data, which require an extended period. In addition, the traffic behaviour data collected by a V2I system can also be used to identify potential high crash risk locations. The warning signs developed in this study can prevent accidents by alerting drivers who are speeding and at risk of crashes.

Evaluating the Impact of V2V Warning Information on Driving Behavior Modification Using Empirical Connected Vehicle Data

“…Zhang et al (2022) evaluated truck drivers' driving behavior using GPS data and an in-vehicle driver monitoring system [28]. Hsu et al (2022) evaluated the impact of a motorcycle safety warning system (MSWS) using RFID data [29]. MohamMad et al (2021) examined PVD collected from the safety pilot model deployment (SPMD) program to analyze vehicle maneuvers, such as differences in speed and lateral/longitudinal differences in acceleration in CV environments [30].…”