RESEARCH ON STATISTICAL DATA-BASED TRAFFIC FLOW LEVELING USING QUANTUM ANNEALER

Abstract

Recently, quantum annealing has attracted attention as a method for solving combinatorial optimization problems. Route optimization is one of the optimization problems that can be solved using quantum annealing, and applications such as taxi traffic flow optimization and automatic guided vehicle (AGV) control are known. In this study, we investigated the applicability of route optimization by quantum annealing to urban traffic control. A simple model of traffic flow is defined by using statistical traffic data provided by local governments and a graph corresponding to the road network of a real city. Using quantum annealer to calculate the optimization of the combination of vehicle routes, it was confirmed that the traffic volume was distributed and leveled around the main roads, compared to the case where each vehicle simply moves along the shortest route. In the future, we aim to apply the knowledge of route optimization obtained in this research to advanced traffic control including traffic signal control.