Search

Although the National Transportation Safety Board has strongly recommended the application of collision avoidance warning systems and automated emergency braking (CAWS/AEB), the transit industry has lagged behind autos and trucks. CAWS/AEB for buses is more complex than for cars and trucks and represents a niche market. If bus manufacturers and suppliers are to invest in developing this technology, they will need to be convinced there is a market for it. Transit agencies also will need to be convinced that the technology works and is affordable. For both vendors and purchasers, a business case could be made that some or all of the expense of procuring and deploying the technology can be recovered through savings from reduced insurance premiums and claims payouts by preventing or mitigating collisions. This paper describes two methods for estimating the business case for equipping transit buses with CAWS/AEB. First, industrywide data on the numbers of collisions and casualty and liability expenses incurred by transit agencies were examined, and statistical relationships were modeled to determine whether reducing the numbers of collisions would reduce casualty and liability expenses. Second, individual collision claims records for specific transit agencies were examined to determine whether the collisions could have been prevented by CAWS/AEB, and the potential savings.

This paper discusses the importance of near-crash events and associated metadata as valuable sources for smart transit applications, such as surrogate safety measures for transit safety research. The STAR Lab at the University of Washington, sponsored by the Federal Transit Administration, has developed an edge computing system that processes onboard videos for near-crash detection. This paper builds on previous work by addressing two research questions: first, how to leverage the near-crash detection system to synthesize rich data sources on transit vehicles, and second, how to use the smart data hub to support transit operation and safety studies. The proposed procedures for event-based transit data collection, evaluation of commercial collision avoidance warning systems (CAWS) technologies, and transit safety hotspot identification are detailed. CAWS’ performance was benchmarked on four transit buses that were operated for almost a year in Pierce County, WA, U.S. Furthermore, the meta-information of near-crash events enables hotspot analysis and the identification of several exemplar clusters that can be explained by driver behavior and roadway geometries. The results of the experiments demonstrate the system’s promising performance and its applicability to addressing various transit operation questions.

The transit score is a measure that can inform the selection of appropriate transit investments for a given community. The model estimates a measure of the potential for success of various transit investments—the transit score—as a function of the densities of population, employment, and carless households. A version of this methodology was developed in 1989 by the Delaware Valley Regional Planning Commission (DVRPC), the metropolitan planning organization for the Philadelphia, Pennsylvania, and Camden-Trenton, New Jersey, region. The method was adapted and expanded by the New Jersey Transit Corporation (NJ TRANSIT) in 2000 to evaluate future rail and fixed guideway extensions in its 2020 plan. Several other versions of the transit score methodology are known to exist and have been applied in studies across the United States. In 2005, DVRPC staff, in collaboration with NJ TRANSIT, undertook a project to validate and apply the transit score methodology to areas within the DVRPC region. Three versions of the transit score model were calibrated with linear regression models by using observed transit journey-to-work mode share as a proxy for transit score. Development of the transit score model is documented, revisions and statistical validation are described, and a range of applications of the transit score, both completed and contemplated, are discussed.

New York's Metropolitan Transportation Authority (MTA) is conducting a study to improve the underground pedestrian facilities associated with the major subway stations and transportation terminals in midtown Manhattan. These facilities form an extensive, though disjointed, underground pedestrian network in the heart of New York City's business, commercial and entertainment district. This paper highlights the findings of the recently completed first phase of the Midtown Underground Pedestrian Connections Study which examined the need for and the feasibility of constructing the “missing links” in the network as well as improving the existing passageways. In addition to discussing the project's organization, goals and process, this paper describes the midtown transportation facilities, the existing pedestrian flow patterns, and the proposed improvements to the network. The results of a special study are presented which recommends a scheme to enhance the role of the 42nd Street Shuttle Subway in Midtown circulation by modifying the operation and configuration of the terminals. The shuttle carries 90,000 passengers per day between Grand Central and Times Square, providing a vital link between major transportation facilities and activity centers.

Recent emphasis in comprehensive planning for coastal zone regions has created the need for more effective tools for information processing and analysis to aid policymakers and planners in developing strategies for preservation of coastal zone areas. New agencies with broad powers have been created at both state and federal levels to deal with growth management in large coastal regions. However, coastal zone management (CZM) agencies have not yet been able to deal effectively with development processes. A “holding action”; is being maintained in the face of mounting pressure by developers, while planners struggle to develop (1) a data base with sufficient detail for planning; (2) a fair and rapid process for reviewing environmental impact statements and granting of development permits; and (3) a system for making the development permit application process more routine. The key to success of the CZM process is the development of a management information system (MIS) created explicitly for CZM. The prototypical system designed by the authors combines graphic display capabilities (i.e., map display) with interactive on-line computing and large storage-capacity computers. Problems of data structure development are documented, together with problems of assembling a large-scale, highly detailed data base. Of particular importance is the need for well-developed objectives and specifications for the use of computer-based data in resolving disputes on environmental issues. A set of objectives and specifications for a prototypical coastal zone MIS is developed. The system is described in detail, showing how its capabilities directly address policy questions formulated by coastal zone planners.