Journal of South China University of Technology (Natural Science Edition) ›› 2013, Vol. 41 ›› Issue (2): 58-65.doi: 10.3969/j.issn.1000-565X.2013.02.010

• Traffic & Transportation Engineering • Previous Articles     Next Articles

Timing Optimization of Traffic Signals for Emergency Evacuation in Sudden-Onset Disasters

Lin Ci-yun1,2 Gong Bo-wen1,2 Zhao Ding-xuan1,3 Yang Zhao-sheng1,2   

  1. 1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, Jilin, China;2. College of Transportation, Jilin University, Changchun 130022, Jilin, China;3. College of Mechanical Science and Engineering, Jilin University, Changchun 130022, Jilin, China
  • Received:2011-12-26 Revised:2012-11-11 Online:2013-02-25 Published:2013-01-05
  • Contact: 龚勃文(1982-),女,博士,讲师,主要从事智能交通诱导理论与应用研究. E-mail:gongbowen@jlu.edu.cn
  • About author:林赐云(1980-),男,博士,讲师,主要从事智能交通控制理论与应用研究.E-mail:linciyun@jlu.edu.cn
  • Supported by:

    国家"863"计划项目(2009AA11Z218); 高等学校博士学科点专项科研基金新教师类资助课题(20110061120043);中国博士后科学基金资助项目(2011M500615,20100481054);中国博士后科学基金特别资助项目(2012T50300)

PDF

697

Abstract:

Aiming at the frequently-occurring sudden-onset disasters and insufficient emergency traffic guarantee ability in the world, this paper analyzes the influences of sudden-onset disasters on the urban traffic network and travel behaviors, and proposes a timing optimization model of traffic signals for emergency evacuation in sudden-onset disaster areas. The model, which is based on the dynamic traffic assignment theory and the route choice beha-viors of drivers in sudden-onset disasters, is then optimized by using a parallel ant colony algorithm to accelerate the speed of solving the problem and improve the global convergence ability. Finally, a cluster computing platform is constructed to test the proposed model and algorithm. The results show that the parallel ant colony algorithm helps to obtain better time performance and higher optimization efficiency, thus meeting the real-time demands of on-line decision support for the emergency traffic guarantee system.

Key words: transportation system engineering, emergency traffic control, dynamic traffic assignment, traffic sig-nals, parallel ant colony algorithm, sudden-onset disaster

CLC Number: