Optimal Sensor Placement for Both Traffic Control and Traveler Information Applications

Traffic sensors have been deployed for decades to freeways to meet the requirements of various traffic/transportation applications, most noticeably traffic control and traveler information applications. A unique feature of traffic sensor deployment is that it is a continuous and evolving process. That is, with new applications emerge, additional sensors are usually required to be deployed to meet new requirements. This process is also sequential in nature as the new deployment has to consider existing sensors. In this article, we propose a modeling framework to capture this sequential decision-making process for traffic sensor deployment. The framework is based on the Dynamic Programming (DP) model the authors recently developed for determining optimal sensor deployment for freeway travel time estimation. We illustrate the framework using two applications: ramp metering control and travel time estimation. It is found that the proposed scheme can appropriately capture the decision-making process of traffic sensor deployment, and can generate optimal sensor placement at any stage by considering sensors that have already been deployed in the field. The model is tested using GPS-enabled cell phone data on a real-world freeway route in the San Francisco Bay Area.