Reliable Traffic Sensor Deployment Under Probabilistic Disruptions and Generalized Surveillance Effectiveness Measures

作     者：Li, Xiaopeng Ouyang, Yanfeng 

作者机构：Mississippi State Univ Dept Civil & Environm Engn Mississippi State MS 39762 USA Univ Illinois Dept Civil & Environm Engn Urbana IL 61801 USA 

出 版 物：《OPERATIONS RESEARCH》 (运筹学)

年 卷 期：2012年第60卷第5期

页      面：1183-1198页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：National Science Foundation [CMMI 0748067] Directorate For Engineering Div Of Civil, Mechanical, & Manufact Inn Funding Source: National Science Foundation 

主　　题：traffic sensor deployment reliability mixed-integer program Lagrangian relaxation heuristics continuum approximation 

摘      要：Sensor systems as critical components of a transportation network provide a variety of real-time traffic surveillance information for traffic management and control. The deployment of sensors significantly affects their overall surveillance effectiveness. This paper proposes a reliable sensor location model to optimize surveillance effectiveness when sensors are subject to site-dependent probabilistic failures, and a general effectiveness measure is proposed to encompass most existing measures needed for engineering practice (e.g., flow volume coverage, vehicle-mile coverage, and squared error reduction). The problem is first formulated into a compact mixed-integer program, and we develop a variety of solution algorithms (including a custom-designed Lagrangian relaxation algorithm) and analyze their properties. We also propose alternative formulations including a continuum approximation model for single corridor problems and reliable fixed-charge sensor location models. Numerical case studies are conducted to test the performance of the proposed algorithms and draw managerial insights on how different parameter settings (e.g., failure probability and spatial heterogeneity) affect overall surveillance effectiveness and the optimal sensor deployment.