Study on Cooperation between Traffic Control and Route Guidance Based on Real-time Speed
Jie Cao, Chuan Wang
Abstract
Jie Cao, Chuan Wang
Abstract
Aiming at minimizing the total travel time of the road network, a cooperation model of traffic control and route guidance is built based on real-time speed obtained from cooperative vehicle infrastructure system. Genetic algorithm is used to solve the cooperation model to get the optimal green ratio and guidance rate of flow through transforming genetic algorithm with constraints into unconstrained genetic algorithm by penalty function. The simulation results of an experimental simulation on a small network show that this method can effectively balance the network flow, reduce total travel time and improve the efficiency of road network.
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Aiming at minimizing the total travel time of the road network, a cooperation model of traffic control and route guidance is built based on real-time speed obtained from cooperative vehicle infrastructure system. Genetic algorithm is used to solve the cooperation model to get the optimal green ratio and guidance rate of flow through transforming genetic algorithm with constraints into unconstrained genetic algorithm by penalty function. The simulation results of an experimental simulation on a small network show that this method can effectively balance the network flow, reduce total travel time and improve the efficiency of road network.
Key concepts: Genetic algorithm, Travel time, Computer science, Control (management), Traffic flow (computer networking), Function (biology), Flow network, Penalty method