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Green wave traffic control system optimization based on adaptive genetic-artificial fish swarm algorithm

  • Theory and Applications of Soft Computing Methods
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Abstract

The urban green wave traffic control system is one of the effective means to solve the problems of urban traffic jams and reduce vehicle delay. Aiming at the problems of traditional green wave traffic control in optimization computation, this paper introduces the adaptive mechanism and crossover, mutation operators to artificial fish swarm algorithm (AFSA) in order to adjust the evolution group. Through setting bulletin board measure and retention strategy, the individual status of the optimal artificial fish is recorded. In that way, the adaptive genetic AFSA is established. Finally, the paper applies this algorithm to green wave traffic control in five continuous intersections on Jianning Road, Lanzhou, China, gains one traffic control program better than traditional method through calculation, and verifies the feasibility and effectiveness of adaptive genetic-AFSA to optimize green wave traffic control system.

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Acknowledgments

This work is supported by the Natural Science Foundation of China (Nos. 51408288, 61164003 and 61364026), and the Higher School Science Foundation of Gansu Province (No. 2014A-044).

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Authors and Affiliations

  1. School of Traffic and Transportation, Lanzhou Jiaotong University, Anning West Road, Lanzhou, 730070, Gansu, China

    Changxi Ma & Ruichun He

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  1. Changxi Ma
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  2. Ruichun He
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Correspondence to Ruichun He.

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Ma, C., He, R. Green wave traffic control system optimization based on adaptive genetic-artificial fish swarm algorithm. Neural Comput & Applic 31, 2073–2083 (2019). https://doi.org/10.1007/s00521-015-1931-y

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  • DOI: https://doi.org/10.1007/s00521-015-1931-y

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