01672571

Component

http://www.trb.org/Main/Blurbs/175112.aspx

The METRO Green Line links five major activity centers in the Twin Cities region. Much of the Green Line route is in dedicated right-of-way in the center of University Avenue, a major east–west street between St. Paul and Minneapolis. This busy commercial corridor has high volumes of pedestrian traffic and is crossed by major arterial streets. Green Line trains pass through 68 traffic signals along the length of the alignment, with typical signal spacing of 300 ft in the downtown areas and one-quarter mile along University Avenue. The number of traffic signals that the Green Line must travel through, combined with schedule time, makes transit signal priority (TSP) critical to reliable, on-time service. The desire to reduce travel times and improve on-time performance led the agency to propose a new approach to transit signal priority that would better address the challenges of light rail operation in a dense urban environment. Known as “predictive priority,” this approach had three main objectives: maximize the opportunity for LRT to receive a green signal, based on the predicted arrival of the train at an intersection; minimize disruption of signal sequence and traffic operations, especially skipping of phases; and avoid causing significant additional delay to road vehicle or pedestrian signal phases. Predictive priority is based on the detection of a train at an upstream intersection, typically 25 to 60 s prior to arrival at the next signalized intersection. The advanced detection is received by the signal controller via the fiber optic communication network and is used to transition the signal timing, ending phases early or extending phases as needed, so that the signal will be “green” for the LRT phase at the expected time of its arrival. Data collected before and after the implementation of predictive priority showed that the percentage of trains stopping at predictive priority intersections was less than 5%, LRT trip times in the city of St. Paul were reduced by 10% to 15%, and on-time performance increased from 60% to 85% as predictive priority was implemented at 19 intersections along University Avenue. Average travel times in St. Paul over this period were reduced from 34 to 35 min to less than 27 min, and variability in run times—a key factor in customer satisfaction—was significantly decreased. Delays for left-turning and cross-street traffic also declined. Predictive priority is a data-driven approach to transit signal priority that relies on a robust detection system for both light rail vehicles and on-street traffic. Without accurate and reliable data, the controller logic needed to optimize signal phases and minimize disruption could not be performed. The approach also requires strong integration with traffic signal controllers, and Metro Transit’s experience shows the benefits of involving signal controller vendors early in the process in order to maximize the capabilities of the controller software. Finally, it is critical to identify operational priorities and understand trade-offs between competing priorities when seeking to modify the signal operations strategies to accommodate a new mode.

01613496

English

pp 242-246

2016-9

Transportation Research Circular

13th National Light Rail and Streetcar Conference

9780309450591

Digital/other

Figures

Light rail transit; Mathematical prediction; Traffic signal control systems; Traffic signal controllers; Traffic signal priority; Travel time

Twin Cities Metropolitan Area (Minnesota)

Operations and Traffic Management; Public Transportation; Railroads

TRIS, TRB, ATRI

May 9 2018 10:23AM

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