Citation

Bonela SR, Kadali BR. IATSS Res. 2023; 47(4): 545-556.

Copyright

(Copyright © 2023, International Association of Traffic and Safety Sciences, Publisher Elsevier Publishing)

DOI

10.1016/j.iatssr.2023.12.002

PMID

unavailable

Abstract

In India, the crossing conflicts between right-turn vehicles of minor road traffic and conflicting vehicles on major roads have become more severe at unsignalized T-intersections in recent times. Due to the rapid growth of vehicular traffic, including motorized two-wheelers, auto-rickshaws, etc., results in an increase in right-turn crossing conflicts (RTCC) at unsignalized T-intersections. The severity of right-turn vehicles is related to the characteristics of both right-turning and conflicting through vehicles. Therefore, this study examines the effect of vehicle types on RTCC. The RTCC are observed using time-to-collision (TTC), at five unsignalized T-intersections in three different cities in India. The RTCC are categorized into critical RTCC and non-critical RTCC based on TTC threshold values obtained by the k-means clustering algorithm. A Generalized Poisson Regression model was developed using Python software. The study results revealed that the presence of higher composition of two-wheelers, auto-rickshaws, and cars in right-turn and conflicting through vehicles significantly influences the severity of RTCC. Also, the model results concluded that the speeds of right-turn and conflicting through vehicles, conflicting through traffic, right-turn traffic, vehicle gap, waiting time, and abnormal driving paths significantly affect the RTCC at unsignalized T-intersections. The findings of this study help traffic engineers and safety experts identify the critical unsignalized T-intersections using the number of right-turn crossing conflicts.

Language: en

Keywords

Generalized Poisson regression model; K-means clustering; Right-turn crossing conflicts; Time-to-collision; Unsignalized T-intersections