TY - GEN
T1 - A hybrid algorithm based on GWO and GOA for cycle traffic light timing optimization
AU - Teng, Tzu Chi
AU - Chiang, Ming Chao
AU - Yang, Chu Sing
N1 - Funding Information:
The authors would like to thank the anonymous reviewers for their valuable comments and suggestions on the paper. This work was supported in part by the Ministry of Science and Technology of Taiwan, R.O.C., under Contracts MOST107-2221-E-110-021 and MOST108-2221-E-110-028.
PY - 2019/10
Y1 - 2019/10
N2 - Since the number of vehicles on the road has been dramatically increased, how to find out a 'good solution' to improve the traffic situation is a difficult optimization problem even if there is still plenty of room for improvement. The main focus of this study is on improving the quality of solutions for the traffic light optimization problem to minimize the waiting time of all the vehicles and maximize the number of vehicles arriving at the destination within a certain time period. An effective hybrid metaheuristic algorithm, called grey wolf grasshopper hybrid algorithm (GWGHA), that leverages the strength of grey wolf optimizer and grasshopper optimization algorithm will be presented in this paper to find a better result in solving the cycle traffic light problem (CTLP). The solutions obtained are simulated with a well-known microscopic traffic simulator named Simulation of Urban MObility (SUMO). Experiments were carried out based on data from Kaohsiung, Taiwan, Bahia Blanca, Argentina, and Ma laga, Spain that represent different experimental cases to evaluate the performance of GWGHA. The simulation results show that the proposed algorithm is superior to the state-of-the-art search algorithms compared in this paper for solving the CTLP.
AB - Since the number of vehicles on the road has been dramatically increased, how to find out a 'good solution' to improve the traffic situation is a difficult optimization problem even if there is still plenty of room for improvement. The main focus of this study is on improving the quality of solutions for the traffic light optimization problem to minimize the waiting time of all the vehicles and maximize the number of vehicles arriving at the destination within a certain time period. An effective hybrid metaheuristic algorithm, called grey wolf grasshopper hybrid algorithm (GWGHA), that leverages the strength of grey wolf optimizer and grasshopper optimization algorithm will be presented in this paper to find a better result in solving the cycle traffic light problem (CTLP). The solutions obtained are simulated with a well-known microscopic traffic simulator named Simulation of Urban MObility (SUMO). Experiments were carried out based on data from Kaohsiung, Taiwan, Bahia Blanca, Argentina, and Ma laga, Spain that represent different experimental cases to evaluate the performance of GWGHA. The simulation results show that the proposed algorithm is superior to the state-of-the-art search algorithms compared in this paper for solving the CTLP.
UR - http://www.scopus.com/inward/record.url?scp=85076746032&partnerID=8YFLogxK
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U2 - 10.1109/SMC.2019.8914661
DO - 10.1109/SMC.2019.8914661
M3 - Conference contribution
AN - SCOPUS:85076746032
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 774
EP - 779
BT - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
Y2 - 6 October 2019 through 9 October 2019
ER -