A Bi-Ievel Programming Model for Network Traffic Surveillance of Optimal Camera Location
Cameras enable synthesis of disaggregated vehicle information from multiple locations. This paper addresses the problem of how to determine the optimal locations of cameras for best traffic surveillance in urban road networks. AH users are divided into multiple classes according to their own acceptance degree of camera monitoring (ADOCM). A bi-level programming model for camera location problem (CLP) is introduced. The objective of upper level problem is to maximize the total observed traffic flow from the viewpoint of network planners. The lower level problem is to depict the logit-based stochastic route choice behavior of users. The method of successive averages (MSA) and Frank Wolfe algorithm are employed to solve the problem. Numerical examples show the managerial insight that the behavior against camera monitoring has brought considerable loss to network traffic surveillance.
location theory bi-level programming camera location traffic surveillance multiclass stochastic user equilibrium
Xiao-Shan Lu Hai-Jun Huang Jiancheng Long
School of Economics and Management, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
国际会议
昆明、丽江
英文
1035-1039
2011-04-15（万方平台首次上网日期，不代表论文的发表时间）