Principal Investigator

Stephen Smith

Status

Completed

Start Date

Jan. 1, 2014

End Date

Jan. 1, 2014

Project Type

Research Advanced

Grant Program

MAP-21 TSET - Tier 1 (2012 - 2016)

Grant Cycle

2014 TSET UTC

Visibility

Public

Abstract

The project goal is to add pedestrian detection capabilities, so as to give pedestrians first-class consideration when allocating green time on traffic lights. Vehicle traffic patterns can cause excessively long wait times and an increasing tendency for pedestrians to ignore signals and cross amidst oncoming traffic. Recent work on adaptive traffic signal control in urban environments has demonstrated the potential for significant gains in vehicle travel times, traffic throughput and air quality. Our effort will aim to reduce jaywalking and illegal crossings, and, therefore, improve the overall safety of pedestrian travel. We will leverage our recently-deployed SURTRAC adaptive traffic signal control system, and its pilot deployment in Pittsburgh. SURTRAC takes a decentralized yet coordinated approach to traffic network control. We will extend SURTRAC to consider pedestrians, and study tradeoffs against vehicle flow objectives.    

Description

-

Timeline

-

Strategic Description / RD&T

Deployment Plan

-

Expected Outcomes/Impacts

-

Expected Outputs

TRID

Individuals Involved

Email	Name	Affiliation	Role	Position
sfs@cs.cmu.edu	Smith, Stephen	Robotics Institute	PI	Faculty - Tenured
xie@wiomax.com	Xie, Xiao-Feng	Robotics Institute	Co-PI	Student - PhD

Budget

Amount of UTC Funds Awarded

$50000.00

Total Project Budget (from all funding sources)

$50000.00

Documents

Type	Name	Uploaded
Final Report	Pedestrian_Friendly_traffic_signals.pdf	April 2, 2018, 5:13 a.m.
Publication	Coping with large traffic volumes in schedule-driven traffic signal control	Oct. 24, 2020, 7:22 p.m.
Publication	Cooperative Schedule-Driven Intersection Control with Connected and Autonomous Vehicles	Oct. 24, 2020, 7:22 p.m.

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