基于出行者需求快速聚类的公路交通路径规划研究

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (508 KB) HTML ()
输出: BibTeX | EndNote (RIS)

摘要 To realize real-time and reliable transportation path planning for improving the efficiency of a traveler in a highway transportation network, this paper presents a fast traveler demand clustering algorithm based on simulated annealing particle swarm optimization (SAPSO). First, we apply fast clustering according to the traveler demand obtained by a cooperative vehicle system, and then integrate the results with the planning destination target and traveling vehicle information to realize the optimized highway transportation path. Based on an experiment and comparison results, this method has better performance than two algorithms and has high effectiveness and should increase traveler satisfaction.

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	杨文丽
	杨蕴
	刘鸿伟

关键词 ： ITS, highway transportation path planning, fast traveler demand clustering algorithm, SAPSO, cooperative vehicle, optimization

Abstract：To realize real-time and reliable transportation path planning for improving the efficiency of a traveler in a highway transportation network, this paper presents a fast traveler demand clustering algorithm based on simulated annealing particle swarm optimization (SAPSO). First, we apply fast clustering according to the traveler demand obtained by a cooperative vehicle system, and then integrate the results with the planning destination target and traveling vehicle information to realize the optimized highway transportation path. Based on an experiment and comparison results, this method has better performance than two algorithms and has high effectiveness and should increase traveler satisfaction.

Key words： ITS highway transportation path planning fast traveler demand clustering algorithm SAPSO cooperative vehicle optimization

收稿日期: 2013-08-11

基金资助:Supported by the National Natural Science Foundation of China (No.2012ZX03005010)

通讯作者: YANG Wen-li, ywl@itsc.cn E-mail: ywl@itsc.cn

引用本文:

杨文丽, 杨蕴, 刘鸿伟. 基于出行者需求快速聚类的公路交通路径规划研究[J]. Journal of Highway and Transportation Research and Development, 2014, 8(1): 84-87.
YANG Wen-li, YANG Yun, LIU Hong-wei. Research of Highway Transportation Path Planning Based on a Fast Traveler Demand Clustering Algorithm. Journal of Highway and Transportation Research and Development, 2014, 8(1): 84-87.

链接本文:

http://manu27.magtech.com.cn/Jwk_gljtkj_en/CN/ 或 http://manu27.magtech.com.cn/Jwk_gljtkj_en/CN/Y2014/V8/I1/84

[1] WANG Wei, DENG Wei, YANG Qi. The Method of Highway Network Planning and Management[M]. Beijing:Science Press, 2006. (in Chinese)
[2] LU Ru-qian. Artificial Intelligence[M]. Beijing:Science Press, 1988. (in Chinese)
[3] KENNEDY J, EBERHART R. Particle Swarm Optimization[C]//Proceedings of IEEE International Conference on Neural Networks. Perth, Australia:IEEE Press,1995:1942-1948.
[4] SHI Y, EBWEHART R. Parameter Selection in Particle swarm Optimization[C]//Proceedings of the IEEE Congress on Evolutionary Computation. Piscataway,NJ:IEEE Press, 1998:69-73.
[5] ZENG Jian-chao, JING Jie, CUI Zhi-hua. Particles Swarm Optimization Algorithm[M]. Beijing:Science Publication, 2004. (in Chinese)
[6] DORIGO M, MANIEZZO V, COLORNI A. Ant System:Optimization by a Colony of Cooperating Agents[J].IEEE Trans. on Systems, 1996, 26(1):29-41.
[7] PANG Feng. The Principle of SA Algorithm and Algorithm's Application on Optimization Problem[D]. Jilin:Jilin University,2006. (in Chinese)
[8] JIANG Chuan-qi. Vehicle Routing Programming Based on Customer Clustering[J]. Microcomputer Information, 2012, 28(2):74-76. (in Chinese)
[9] SHEU Jiuh-biing. A Hybrid Fuzzy-optimization Approach to Customer Grouping-based Logistics Distribution Operations[J]. Applied Mathematical Modeling, 2007,31(6):1048-1066.
[10] WU Jin-hua, WU Hu-li, ZHOU Shi. The Study of Particle Swarm Optimizer Algorithm Based on Simulated Annealing[J].Chinese Journal of Scientific Instrument, 2008, 29(8):50-53. (in Chinese)
[11] WANG Lian-guo, HONG Yi, ZHAO Fu-qing, et al. A Hybrid Algorithm of Simulated Annealing and Particle Swarm Optimization[J]. Computer Simulation, 2008, 25(11):179-182. (in Chinese)
[12] CAI Zhi-li, SUN Feng-rui, WEI Ling-xiang, WANG Nan. Design of Cooperative Vehicle-Infrastructure System Based on Mobility Internet Technologies[J]. Journal of Shandong Jiaotong University,2011, 19(4):17-23. (in Chinese)
[13] CHEN Chao, LU Zhi-yong, FU Shan-shan, PENG Qi. et al. Overview of the Development in Cooperative Vehicle-Infrastructure System Home and Abroad[J]. Journal of Transport Information and Safety,2011, 29(1):102-109. (in Chinese)
[14] CHEN Ming-yu. Multi-factor Weight Determination Algorithm for Road Network Based on Fuzzy Mathematics[J]. Geometrics and Information Science of Wuhan University, 2007, 32(10):928-931. (in Chinese)
[15] CHEN Jia-qi, LIU Yue. Application of Hybrid Ant Colony Optimization to Urban Transportation Path Planning[J]. Applied Technique, 2012, 21(1):122-126. (in Chinese)