摘要
针对目前国内外突发灾害事件频发、应急交通组织保障能力不足等问题,在充分考虑突发灾害对道路交通网络、交通出行行为影响的基础上,基于动态交通分配理论,结合突发灾害下的出行者疏散路线选择行为,构建了受灾区域应急疏散路线的交通信号优化控制模型,并采用并行蚁群算法对该模型进行优化求解,以提高求解速度和全局收敛能力.最后搭建了集群计算平台对该模型和算法进行模拟测试,结果表明,采用并行蚁群算法对模型进行优化求解,可以获得较好的时间性能和优化效率,满足应急交通保障系统在线决策支持的要求.
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 resuhs 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.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2013年第2期58-65,共8页
Journal of South China University of Technology(Natural Science Edition)
基金
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)
关键词
交通运输系统工程
应急交通控制
动态交通分配
交通信号
并行蚁群算法
突发灾害
transportation system engineering
emergency traffic control
dynamic traffic assignment
traffic signals
parallel ant colony algorithm
sudden-onset disaster
