This report presents the mitigation methods tested and used by transit agencies to reduce collisions between light rail vehicles (LRVs) and motor vehicles where light rail transit (LRT) runs through or adjacent to highway intersections controlled by conventional traffic signals. A particular focus is placed on collisions occurring between LRVs and vehicles making left-hand turns at these intersections. This report offers success stories and specific actions to achieve positive results, as well as examples of unsuccessful actions. The issues addressed include a range of LRT operations and environments such as median-running, side-running, contra-flow, and mixed-use LRT alignments; urban and suburban setting; and a variety of U.S. geographic regions.
This report provides documentation and presents the results of a study to improve the safety of light rail transit (LRT) in semiexclusive rights-of-way where light rail vehicles operate at speeds greater than 35 mph through crossings with streets and pedestrians pathways. This report also presents the results of field tests conducted to improve the safety of higher speed LRT systems through grade crossing design.
Presents a review of the current practices associated with the operation of traffic signals at intersections located near highway-rail grade crossings.
TCRP Report 137: Improving Pedestrian and Motorist Safety Along Light Rail Transit Alignments addresses pedestrian and motorist behaviors contributing to light rail transit (LRT) safety and describes mitigating measures available to improve safety along LRT alignments. The report also includes recommendations to facilitate the compilation of accident data in a coordinated and homogeneous manner across LRT systems. Finally, the report provides a catalog of existing and innovative safety devices, safety treatments, and practices to use along LRT alignments. The results of this research may be useful to transit operators, consultants, and state safety oversight agencies.
An intelligent transportation system (ITS) offers considerable opportunities for increasing the safety, efficiency, and predictability of traffic flow and reducing vehicle emissions. Sensors (or detectors) enable the effective gathering of arterial and controlled-access highway information in support of automatic incident detection, active transportation and demand management, traffic-adaptive signal control, and ramp and freeway metering and dispatching of emergency response providers. As traffic flow sensors are integrated with big data sources such as connected and cooperative vehicles, and cell phones and other Bluetooth-enabled devices, more accurate and timely traffic flow information can be obtained. The book examines the roles of traffic management centers that serve cities, counties, and other regions, and the collocation issues that ensue when multiple agencies share the same space. It describes sensor applications and data requirements for several ITS strategies; sensor technologies; sensor installation, initialization, and field-testing procedures; and alternate sources of traffic flow data. The book addresses concerns related to the introduction of automated and connected vehicles, and the benefits that systems engineering and national ITS architectures in the US, Europe, Japan, and elsewhere bring to ITS. Sensor and data fusion benefits to traffic management are described, while the Bayesian and Dempster–Shafer approaches to data fusion are discussed in more detail. ITS Sensors and Architectures for Traffic Management and Connected Vehicles suits the needs of personnel in transportation institutes and highway agencies, and students in undergraduate or graduate transportation engineering courses.
