An evaluation of emergency vehicle preferential treatment strategies by traffic simulation

Abstract

Emergency vehicles (EVs) must reach their destination within the shortest amount of time considering the importance of their service in saving lives and reducing damage to property. The aim of this research was to reduce the delay experienced by these vehicles through the alteration of traffic control signals to give preferential treatment to EVs upon detection. Specifically, this study compared three algorithms with concepts of EV pre-emption, longest queue first and emergency vehicle signal priority (EVSP) based on average general and EV delays through a traffic simulation approach using the Vissim software program and its component object model interface. The performance evaluation was applied at Tuk Chai intersection in Bangkok, Thailand as a case study. The second algorithm of longest queue first with pre-emption was found to be the best approach for both peak hour traffic conditions and 0.8 (peak) traffic conditions (i.e. peak hour traffic volume reduced by 20%), performing better than the do-nothing condition by 69.70% for stochastic EV input and 79.14% for fixed EV input. The findings also show that the algorithm of preferential treatment using EVSP strategies produced a competitive and robust performance with EV delay values better than the do-nothing condition by 75.96, 77.27 and 45.67% in 0.8 (peak), peak hour and 1.2 (peak) traffic conditions, respectively (the last of these three being peak hour traffic volume increased by 20%).