Abstract
In transportation networks, traditional fixed sensors are used to monitor the operation of transportation systems. However, fixed sensors cannot move once they are installed. In this paper, the motion ability of traffic sensors is introduced to improve the performance of transportation network surveillance. A mobile traffic sensor routing problem is proposed, modeled as a novel vehicle routing problem. A measure of traffic information acquisition benefits is developed and used to gauge the surveillance performance. To solve this mobile-sensor routing problem, a hybrid two-stage heuristic algorithm is designed, which is based on particle swarm optimization and ant colony optimization. Numerical experiments are conducted. The results show that the mobile traffic sensor has a better network surveillance performance than the fixed sensor in most experimental cases.
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