Principal Investigator

Sean Qian

Status

Completed

Start Date

Jan. 1, 2016

End Date

Jan. 1, 2017

Project Type

Research Advanced

Grant Program

PennDOT

Grant Cycle

PennDOT

Visibility

Public

Abstract

Non-recurrent traffic congestion caused by roadway construction work, planned events, and unplanned traffic incidents can create massive traffic tie-ups and can have equally large economic and environmental regional impacts. More roadway rehabilitation/reconstruction work is conducted over the recent years on heavily traveled urban corridors which are already “capacity-hungry.” With the availability of various traffic data (real-time and historically archived), how to minimize incident-induced disruption to commuting traffic and its impact to the environment presents a big challenge to public agencies. While planned and unplanned incidents require careful evaluation of alternative construction plans and corresponding traffic management plans, guidelines to develop efficient traffic demand management strategies are often lacking. Consequently, there is a real need to study planned and unplanned traffic incidents to learn valuable lessons to prepare public agencies to deal more effectively with large routine highway maintenance, reconstruction, big sports events, catastrophic vehicle crash and emergency situations. 
The Philadelphia Metropolitan Region is traffic data rich comparing to other metropolitan areas in the U.S. Various data sets in the Philadelphia region, including traditional traffic sensors (loops, cameras, etc.) and cutting-edge sensors (Bluetooth, GPS probe, parking, etc.), are available and have been archived for a decade. The rich data sets allow us to learn travelers’ behavior accurately and develop an in-depth understanding of non-recurrent traffic in large-scale networks. 
This research develops a regional dynamic network model that simulates millions of trips in the Philadelphia Metropolitan Region (see Figure 1 for the modeling scope) and captures those travelers’ travel behavior. It can be applied directly to predict traffic impact of planned and unplanned incidents, and provide real-time decision making for traffic operations. The regional model will also be tested as a real-time traffic management tool for two planned incidents, I-95 closures and Center City bridge closures. 
In the Philadelphia area, I-95 is currently being reconstructed. The reconstruction narrows lane widths, which leads to heavy traffic congestion during peak hours. Delaware Valley Regional Planning Commission (DVRPC), PennDOT and the city are looking at ways to implement various strategies to achieve Integrated Corridor Management to improve the efficiency, reliability and safety of this I-95 corridor. In addition, starting in December 2014 and extending through 2018, PennDOT will be reconstructing the Vine Street expressway bridges from 18th Street to 22nd Street and Schuylkill River bridges from Spring Garden to Chestnut Street. The reconstruction work will involve considerable lane closures, detours and other traffic diversions. It will also impact bus operations and pedestrian movements across the bridges to/from Center City. Both I-95 reconstruction and Center City Bridges reconstruction present a great opportunity to conduct research on impact of critical infrastructure closures and non-recurrent traffic management.    

Description

-

Timeline

January 1, 2016 - January 1, 2017

Strategic Description / RD&T

Deployment Plan

-

Expected Outcomes/Impacts

-

Expected Outputs

TRID

Individuals Involved

Email	Name	Affiliation	Role	Position
seanqian@cmu.edu	Qian, Sean	Carnegie Mellon University	PI	Faculty - Research/Systems

Budget

Amount of UTC Funds Awarded

$87600.00

Total Project Budget (from all funding sources)

$87600.00

Documents

Type	Name	Uploaded
Final Report	130_-_Dynamic_Network_Analysis_Real-time_Traffic_Management_for_Philadelphia_Metropolitan_Area.pdf	June 22, 2018, 12:53 p.m.
Publication	Understanding and predicting travel time with spatio-temporal features of network traffic flow, weather and incidents	Dec. 2, 2020, 9:20 a.m.
Publication	Measuring and reducing the disequilibrium levels of dynamic networks through ride-sourcing vehicle data.	Dec. 2, 2020, 9:20 a.m.
Publication	Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs.	Dec. 2, 2020, 9:21 a.m.
Publication	Multi-Source Traffic Data Reconstruction Using Joint Low-Rank and Fundamental Diagram Constraints.	Dec. 2, 2020, 9:21 a.m.
Publication	High-Resolution Traffic Sensing with Autonomous Vehicles	Dec. 2, 2020, 9:22 a.m.
Publication	Path-based system optimal dynamic traffic assignment: A subgradient approach.	Dec. 2, 2020, 9:32 a.m.

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