Simulation study of traffic accidents in bidirectional traffic models

TL;DR

This study uses Monte Carlo simulations to analyze collision risks in bidirectional traffic models, revealing how vehicle density and heavy vehicles influence accident probabilities.

Contribution

It develops conditions for bidirectional collisions and quantifies how vehicle density and heavy vehicles affect accident risks in traffic models.

Findings

Collision risk increases with asymmetric vehicle densities.

Heavy vehicles reduce traffic flow and increase accident risk.

Different collision types are analyzed based on simulation data.

Abstract

Conditions for the occurrence of bidirectional collisions are developed based on the Simon-Gutowitz bidirectional traffic model. Three types of dangerous situations can occur in this model. We analyze those corresponding to head-on collision, rear-end collision and lane-changing collision. Using Monte Carlo simulations, we compute the probability of the occurrence of these collisions for different values of the oncoming cars density. It is found that the risk of collisions is important when the density of cars in one lane is small and that of the other lane is high enough. The influence of different proportions of heavy vehicles is also studied. We found that heavy vehicles cause an important reduction of traffic flow on the home lane and provoke an increase of the risk of car accident.