Citation

Ahmed N, Chowdhury SS, Tanim MF, Ahammed DT, Raihan MA, Hossain M. Transp. Res. Rec. 2024; 2678(6): 738-751.

Copyright

(Copyright © 2024, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981231198839

PMID

unavailable

Abstract

Collisions with motorized vehicles (MVs) are one of the leading causes of nonmotorized vehicle (NMV) crashes in a heterogeneous traffic stream. As well as NMVs' inherent vulnerability, MV drivers' risk perceptions of NMVs may also influence MV-NMV crashes. However, until now, this subjective perception has been little explored in the literature. This study examines the potential impact of numerous factors associated with motorized road users' perception of risk and the operational aspects of NMVs on MV-NMV crashes. An ordered probit model was developed using self-reported data from 1,560 Dhaka city motorists (motorcyclists, and car and bus drivers).

FINDINGS revealed that motorists have a higher probability of becoming aggressive, deem NMV drivers' behavior to be risky, and have low positive attitudes toward such vehicles when they have a stronger MV-NMV crash history. The results also suggest that bus drivers have fewer crashes with NMVs, although they feel these vehicles are structurally unsafe. In addition, age, education, and perceptions of lane separation, movement, stops, and users' trip frequency were significant in predicting crash frequency. Further, older and illiterate drivers were more likely to be involved in collisions with NMVs. Because of the bias of self-reported data, analysis of variance tests were conducted, and the results demonstrated a significant difference in risk perceptions between motorcyclists, car drivers, and bus drivers. Risk perceptions of NMVs were the highest among motorcyclists. The findings of this study are expected to aid policymakers in improving motorists' perceptions of NMVs and in increasing the latter's safety in developing nations with heterogenous traffic systems.

Language: en