Optimising intersection signal plan under mixed traffic flow: hybrid non-dominated sorting genetic algorithm III and simulation approach

Traffic signalling plays a leading role in effectively alleviating traffic congestion. Previous studies have mainly focused on optimising traffic signal plans under homogeneous traffic flow. However, real-life traffic is predominantly mixed flow, limiting the widespread use of existing methods. This study considers the multi-objective signal plan optimisation problem for intersections under mixed traffic flow. The aim is to obtain a signal plan that improves operational efficiency. A multi-objective model is constructed using average delay, average waiting time and average speed through the intersection as objective functions. A hybrid method that combines non-dominated sorting genetic algorithm III (NSGA-III) with simulation is proposed to solve the above model. The simulation software SUMO is utilised to simulate traffic flow. Two existing left-turn bypass intersections in Pulau Pinang, Malaysia are selected as case studies. Results indicate that traffic signal plans obtained by the proposed method have more obvious advantages compared with existing signal plans. The proposed method reduces delay and waiting time by 48% and 56%, respectively, and increases the speed by 6% for the first intersection, and reduces delay and waiting time by 38% and 43%, respectively, and increases speed by 15% for the second intersection.