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

Xiaopeng Li () and Yanfeng Ouyang ()
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Xiaopeng Li: Department of Civil and Environmental Engineering, Mississippi State University, Mississippi State, Mississippi 39762
Yanfeng Ouyang: Department of Civil and Environmental Engineering, University of Illinois at Urbana--Champaign, Urbana, Illinois 61801

Operations Research, 2012, vol. 60, issue 5, 1183-1198

Abstract: 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.

Keywords: traffic sensor deployment; reliability; mixed-integer program; Lagrangian relaxation; heuristics; continuum approximation (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (22)

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