Fuzzy Control of Intersection Signal Based on Optimized Genetic Algorithm

DOI

10.2991/iccte-16.2016.89How to use a DOI?

Keywords

Fuzzy control; Fitness; Evolutionary algorithm; Fuzzy control rules; Membership functions

Abstract

In order to adapt to the complex traffic and reduce the delay brought by simple traffic model, an improved adaptive genetic fuzzy control method was put forward for intersection traffic signal control. In order to improve the computational efficiency , the population size should be adjusted and the Gaussian membership function should be used. Dealing with local optimum happens in the early process of evolutionary algorithms, the method of increasing the part of the crossover and mutation probability has been used, so the stagnation of evolution process during high fitness individuals was avoid. To test the effectiveness and adaptability of this method , the classic method and the improved method was made to make the simulation respectively under high traffic flow, and the average delay data as a judge. The validation results show that the improved fuzzy control are effective in reducing the average vehicle delay in middle and later periods of the simulation. So that the efficiency of intersection traffic is increased.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jie Cao
AU  - Yi Wang
PY  - 2016/01
DA  - 2016/01
TI  - Fuzzy Control of Intersection Signal Based on Optimized Genetic Algorithm
BT  - Proceedings of the 2016 International Conference on Civil, Transportation and Environment
PB  - Atlantis Press
SP  - 538
EP  - 546
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccte-16.2016.89
DO  - 10.2991/iccte-16.2016.89
ID  - Cao2016/01
ER  -