Pedestrian Detection for the Surtrac Adaptive Traffic System

Source Organization:
University:Carnegie Mellon University
Principal Investigator:Bernardo Pires and Stephen F. Smith
PI Contact,
Project Manager:Courtney Ehrlichman
Funding Source(s) and Amounts Provided (by each agency or organization):$85,000
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Start and End Dates:January 2016 - January 2017
Project Status:Active
Subject Categories:Infrastructure-based Technologies
Abstract:Surtac, the real-time adaptive traffic signal control system, has been demonstrated to significantly improve traffic flow on multiple performance metrics, including reductions of 25% of travel time and 40% wait time for motor vehicles. The objective of this project is to bring this same intelligence to pedestrian traffic, which has, thus far, not been targeted by Surtrac deployments. Phase 1 of this two-year project will analyze pedestrian traffic at multiple Surtrac deployments. Phase 2 will focus on an intersection already equipped with Surtrac system in the Oakland / East Liberty region and will add additional sensing and processing capabilities to determine the presence of pedestrians waiting to cross the intersection. Phase 3 will focus on the expected Surtrac deployment in Pittsburgh’s downtown and will focus on pedestrian density as a more fine grained input for the Surtrac scheduler.
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