The current transportation research environment uses sophisticated modeling of individual components of the surface transportation system to improve performance of the overall system. For example, route guidance models allow for the investigation of benefits (to the individual vehicle and the system) of information provision to drivers, while signal optimization programs determine near-optimal signal timing given traffic data. Traditionally, this breakdown of models into the vehicle and infrastructure domains has been appropriate in that there has been little or no dynamic interaction between the two systems. Signal control systems, for example, currently determine signal timing based on historical data or, in the best case, incorporate dynamic control that is driven by data from loop detectors or other fixed sensors. There is, however, no near real-time information available directly from the vehicles, such as speed, previous locations, vehicle origin and destination, and driver preferences. Vehicle route guidance systems also use historical and near real-time traffic data to assist drivers in route selection but typically do not explicitly consider the phasing of nearby signals. Given the current investigation of technical issues associated with vehicle-vehicle and vehicle-infrastructure communication (referred to as vehicle-infrastructure integration - VII), there is a need to critically examine how such an infrastructure could be used to improve surface transportation. This project proposes both development of modeling tools capable of capturing such networking and development of methods for beneficial integration. The fundamental basic questions that the investigator and his colleagues explore are, therefore, 1) What information should be provided?, 2) Who should receive information?, 3) When should the information be provided?, and 4) How will the information be used?

The automobile is the dominant mode of surface transportation in the United States. The surface transportation system that has developed to enable this mode of travel is made up of two components: (1) individual travelers in their automobiles (referred to as vehicles), and (2) the roadway/traffic control network (referred to as infrastructure). To date, these components are "managed" in an independent manner. Drivers make decisions with very little knowledge of the entire networks status, and infrastructure operators make decisions regarding network control (primarily through signal systems) based on vehicle count data collected at limited locations. This lack of "cooperation" between the components has evolved primarily due to the lack of affordable information technology that would allow the components to easily share data and make collective decisions that would benefit the entire system. Practical benefits of such cooperation include route guidance which assists drivers in minimizing time spent at red lights. It also includes traffic signal systems which can sense and respond quickly to reduce vehicle stops and delays. As wide-area wireless networks become commercially available, and in-vehicle computer systems become affordable and pervasive, the information technology will soon be available to radically rethink how the surface transportation infrastructure should be operated. Because of their mandate and economic interests, the vehicle industry concentrates on research and development to improve the vehicle component of the system - with little consideration of the infrastructure. Similarly, transportation agencies concentrate on research to improve the infrastructure - with little consideration of the vehicle component. Thus, the science base currently does not exist to allow industry and public officials to best direct this new system. The investigators are developing the science and model base for integrated/cooperative surface transportation system control and management made possible by advanced information technology. This will allow for the investigation of the integration of information technology and the transportation infrastructure, a critical step in the evolution of the US transportation system.

Agency
National Science Foundation (NSF)
Institute
Division of Civil, Mechanical, and Manufacturing Innovation (CMMI)
Application #
0510404
Program Officer
Dennis Wenger
Project Start
Project End
Budget Start
2005-08-15
Budget End
2009-07-31
Support Year
Fiscal Year
2005
Total Cost
$331,000
Indirect Cost
Name
University of Virginia
Department
Type
DUNS #
City
Charlottesville
State
VA
Country
United States
Zip Code
22904