Principal Investigator

Stephen Smith

Status

Completed

Start Date

Jan. 1, 2015

End Date

Dec. 31, 2015

Project Type

Research Advanced

Grant Program

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

Grant Cycle

2015 TSET UTC

Visibility

Public

Abstract

This project continues research aimed at real-time detection and use of pedestrian traffic flow information to enhance adaptive traffic signal control in urban areas where pedestrian traffic is substantial and must be given appropriate attention and priority. Our recent work with Surtrac, a real-time adaptive signal control system for urban grid networks, has resulted in an extended intersection scheduling procedure that integrates sensed pedestrians and vehicles into aggregate multi-modal traffic flows and allocates green time on this integrated basis. The effectiveness of this procedure has been demonstrated in simulation under the assumption that requisite sensing is in place. In this project, we further this work in two ways. First, we consider the companion issue of adequately sensing pedestrian and vehicle traffic in an integrated manner. Through collaboration with Citilog, Inc., which provides a unique, software-based approach to pedestrian detection, we will investigate development of higher-level techniques for extracting pedestrian density and direction information in addition to presence data. We will similarly evaluate the potential for basic pedestrian detection via radar, using the Wavetronix equipment currently installed in portions of the Surtrac test bed network (in the Pittsburgh East End). The second thrust of the project will explore use of additional information (e.g., movement disabilities) that may be obtained through direct pedestrian-to-infrastructure communication in making adaptive signal control decisions that promote safe and efficient pedestrian movement. We will evaluate our technology results through pilot testing and where successful attempt to take steps to deploy on a continuing basis within the Surtrac test bed.    

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

Budget

Amount of UTC Funds Awarded

$88539.00

Total Project Budget (from all funding sources)

$88539.00

Documents

Type	Name	Uploaded
Final Report	Smith_TSETFinalReport.pdf	May 7, 2018, 4:27 a.m.

Match Sources

No match sources!

Partners

No partners!