Micro-simulation of vehicle conflicts involving right-turn vehicles at signalized intersections based on cellular automata

• Published in: Accident analysis and prevention 2014-02, Vol.63, p.94-103
• Main Authors: Chai, C., Wong, Y.D.
• Format: Article
• Language: English
• Subjects: Accidents, Traffic - prevention & control; Automobile Driving; Biological and medical sciences; Cellular automata; Computer Simulation; Environment Design; Humans; Intersections; Mathematical models; Medical sciences; Miscellaneous; Models, Theoretical; Permissive turning; Prevention and actions; Public health. Hygiene; Public health. Hygiene-occupational medicine; Safety; Signalized intersections; Strategy; Traffic engineering; Traffic flow; Vehicle conflicts; Vehicles
• ISSN: 0001-4575; 1879-2057
• DOI: 10.1016/j.aap.2013.10.023

•Cellular automata model is improved and modified to assess safety performance.•Proxy indicators are computed for conflicts occurrences.•The proposed approach is compared with crash occurrences and SSAM.•Safety impacts of control strategies and traffic conditions are estimated.•More flexible and accurate compared to analytical models. At intersection, vehicles coming from different directions conflict with each other. Improper geometric design and signal settings at signalized intersection will increase occurrence of conflicts between road users and results in a reduction of the safety level. This study established a cellular automata (CA) model to simulate vehicular interactions involving right-turn vehicles (as similar to left-turn vehicles in US). Through various simulation scenarios for four case cross-intersections, the relationships between conflict occurrences involving right-turn vehicles with traffic volume and right-turn movement control strategies are analyzed. Impacts of traffic volume, permissive right-turn compared to red-amber-green (RAG) arrow, shared straight-through and right-turn lane as well as signal setting are estimated from simulation results. The simulation model is found to be able to provide reasonable assessment of conflicts through comparison of existed simulation approach and observed accidents. Through the proposed approach, prediction models for occurrences and severity of vehicle conflicts can be developed for various geometric layouts and traffic control strategies.