Personal Mobility

This paper describes the ongoing evaluation study of anonymous mobile call sampling for transportation applications underway in the Washington, D.C. metropolitan area. The Universities of Maryland and Virginia, with support from their respective State Departments of Transportation, are investigating the potential of the RadioCamera technology invented by U.S. Wireless Corporation to provide critical data for traffic management applications. This method of data collection is contrasted with other probe and point detection mechanisms. Descriptions of prototype transportation management applications employing this technology are offered. Potential technical limitations are described, as well as means by which they might be obviated. The planned economic evaluation is outlined, including the economic measures to be quantified, the range over which valuation will be conducted, and the means by which benefits will be enumerated. Finally, some conclusions are offered.

University of Virginia

University of Maryland

Presented at the 11th ITS Annual Conference and Exposition, June 4-7, 2001 Miami Beach, Florida

The Tri-County Metropolitan Transportation District of Oregon (Tri-Met) has entered into an agreement with the City of Portland, Oregon to enable its transit buses to use the low Transit Priority request of the signals within the City’s jurisdiction. The three primary goals for the use of transit priority are: 1) to increase throughput within specified traffic corridors; 2) to reduce transit running times; and 3) to improve transit schedule reliability. This paper will focus on methods Tri-Met will employ to evaluate the effectiveness of its transit signal priority effort on transit operations, and to determine if its goals have been met. The project was scheduled to commence in February 2001, and preliminary evaluation results are expected by June 2001.

Tri-County Metropolitan Transportation District of Oregon (Tri-Met)

Presented at the 11th ITS Annual Conference and Exposition, June 4-7, 2001 Miami Beach, Florida

TransGuide, San Antonio's Intelligent Transportation System (ITS), has been in operation since July of 1995. Initially covering 26 miles of freeways, TransGuide has expanded to cover more than 60 miles of freeways throughout San Antonio. The expanded coverage of freeway conditions in San Antonio has been coupled with arterial traffic data to provide traffic information on over 150 miles of the San Antonio area roadway network. The San Antonio Model Deployment Initiative (MDI) expanded TransGuide system capabilities, and brought together traffic information from multiple agencies. Since the conclusion of the Model Deployment Initiative, the Texas Department of Transportation (TxDOT) has implemented new programs to build upon that program's success. Expansion of the TransGuide system on heavily congested freeway corridors outside of downtown allowed the benefits of the system to be available to drivers who did not encounter the TransGuide system when it was located only in the downtown area of San Antonio. The development of the MDI Data Server combined information from TxDOT, the City of San Antonio and VIA Metropolitan Transit Authority to form a single depository of traffic related information available to all local public agencies and private sector Information Service Providers (ISPs).

Texas DOT - TransGuide

Presented at the 11th ITS Annual Conference and Exposition, June 4-7, 2001 Miami Beach, Florida

Until recently the focus in traffic signal preemption and priority has been on developing and extending the capabilities of various technologies and studying their impact on real or hypothetical traffic flows. As these technologies have been implemented, however, institutional issues both before and after implementation have been recognized as significant. This paper examines the differing issues, needs, and concerns that elected officials and transit, traffic and emergency personnel in the Washington, D.C. region have regarding the implementation, installation, maintenance and use of both types of systems. Based on interviews with 37 area officials, system objectives and requirements were identified. The agencies and jurisdictions represented have very different levels of familiarity and experience with preemption and priority systems. For a signal preemption system the objectives identified were that it shall significantly reduce response time to emergencies, improve the safety and health of emergency personnel, and reduce accidents between non-emergency vehicles due to the passage of responding emergency units at intersections where it is installed. Stakeholders also suggested four policy requirements for priority systems. A signal priority system for transit shall improve schedule adherence, improve the efficiency with which buses run, be part of a lager ITS system that includes improved rider information and other services, and increase the overall efficiency with which the road network is used by contributing to an increase in bus ridership. The interviews also revealed that in order to achieve these objectives the systems were required to meet a number of requirements such as regional interoperability and the potential to hold users accountable. In all six system requirements were clearly defined.

George Mason University

Virginia Tech Transportation Institute

Presented at the 11th ITS Annual Conference and Exposition, June 4-7, 2001 Miami Beach, Florida

Traditional driver performance data collection methods have ordinarily relied on experimenters riding with drivers to collect data. Such methods are limited because drivers may exhibit performance that differs from that while driving alone. Alternatively, naturalistic observation methods can be employed by the use of vehicle instrumentation to collect data in an unobtrusive manner.

This paper outlines the data types, data collection, data analysis, expected results provided by these data, and how these data can be used by designers in the development of safe, naturalistic Intelligent Transportation Systems (ITS) of the future. Additionally, this paper includes an overview of a lane change and passing study that is currently taking place. The study involves 16 commuters who drove to and from work for 20 business days, for a minimum of 50 miles round trip each day. Starting in September 2000, ordinary drivers drove instrumented vehicles instead of their normal vehicles during their commute to and from work. Data collection was fully automated and equipment was unobtrusive. Both a sedan and an SUV were used in this study.

Virginia Tech Transportation Institute

Presented at the 11th ITS Annual Conference and Exposition, June 4-7, 2001 Miami Beach, Florida