01126702

Component

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.

01120148

09-3315

English

16p

2009

Transportation Research Board 88th Annual Meeting

DVD

Figures (7) ; References (24) ; Tables (1)

Advanced traveler information systems; Dynamic programming; Global Positioning System; Operations; Sensors; Traffic control; Traveler information and communication systems

San Francisco Bay Area

Highways; Operations and Traffic Management; Planning and Forecasting; I73: Traffic Control

Transportation Research Board Annual Meeting 2009 Paper #09-3315

TRIS, TRB

Jan 30 2009 7:43PM