Optimization designing and solving of signal based on CTM

Wang Zheng-wu; Luo Da-yong; Huang Zhong-xiang

Volume 7 Issue 4

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Wang Zheng-wu, Luo Da-yong, Huang Zhong-xiang. Optimization designing and solving of signal based on CTM[J]. Journal of Traffic and Transportation Engineering, 2007, 7(4): 84-88.

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Wang Zheng-wu, Luo Da-yong, Huang Zhong-xiang. Optimization designing and solving of signal based on CTM[J]. Journal of Traffic and Transportation Engineering, 2007, 7(4): 84-88.

Wang Zheng-wu, Luo Da-yong, Huang Zhong-xiang. Optimization designing and solving of signal based on CTM[J]. Journal of Traffic and Transportation Engineering, 2007, 7(4): 84-88.

Citation:

Wang Zheng-wu, Luo Da-yong, Huang Zhong-xiang. Optimization designing and solving of signal based on CTM[J]. Journal of Traffic and Transportation Engineering, 2007, 7(4): 84-88.

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Optimization designing and solving of signal based on CTM

1.
School of Information Science and Engineering, Central South University, Changsha 410075, Hunan, China
2.
School of Traffic and Transportation, Changsha University of Science and Technology, Changsha 410076, Hunan, China

More Information

Author Bio:
Wang Zheng-wu (1973-), male, associate professor, doctoral student of engineering, +86-731-2309046, zhengwu.wang@126.com

Luo Da-yong (1944-), male, professor, +86-731-2656372, dyluo@mail.csu.edu.cn
Received Date: 2006-12-08
Publish Date: 2007-08-25

Abstract

Abstract

In order to effectively control traffic flow, and synchronously optimize phase, period and green time at intersection, cell transmission model(CTM)and bi-level programming method were studied, and a signal optimization method was proposed. A CTM of entrance traffic flow at intersection was built by modifying cell partition and its state expression, and a bi-level programming method was designed, whose upper programming was to optimize phase scheme, while lower programming was to optimize period and green time. After lower programming was translated by using precision penalty method, an solving algorithm integrated genetic algorithm and chaos optimization algorithm was put forward. Applied result shows that the algorithm not only averts the invalidation problem of chaos optimization algorithm in a large scale, but also increases the local search ability and search precision of genetic algorithm; the method is feasible, the total delay is 270.2 pcu·h, and it is reduced by 5.6% compared with induction control with fixed phases.
- traffic control,
- signal intersection,
- signal optimization,
- cell transmission model,
- genetical algorithm,
- chaos optimization algorithm,
- bi-level programming method

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References(11)

References

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