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Project

#306 Smart Multi-modal Transportation Solution for North Huntingdon Township in Response to Roadway Construction Projects on Route-30


Principal Investigator
Sean Qian
Status
Completed
Start Date
July 1, 2019
End Date
Aug. 30, 2020
Research Type
Applied
Grant Type
Research
Grant Program
Private Funding
Grant Cycle
2019 Smart Mobility Challenge
Visibility
Public

Abstract

Route 30 in the North Huntingdon Township serves as a main commercial corridor as well as a regional arterial. Part of a growing area, there are significant challenges with congestion, safety, travel demand and mobility. There is a great need to provide a holistic mobility solution including driving, transit usage, park and ride lots, and existing and projected land use development. This corridor offers all of the challenges to developing a transportation corridor multi-modal plan. In addition, PennDOT is well into the design phase for a redesign and rebuild of Route 30 to include major utility relocations, drainage, and alignment redesign that will create significant construction related congestion foe multiple years so that a multimodal plan for construction, as well as long term operations, can and should be incorporated into the multi-year construction project. 

This proposed research project will: 1) Develop a generic regional network model to estimate/predict time-varying traffic evolution on all roads in the Allegheny County and Westmoreland County, with the focus on the proximity of North Huntingdon Township. The model estimates origin-destination traffic demands within the region and captures travel behavior of those travelers (in particular their time-varying route choices, and modal choices); 2) Conduct a case study for Route 30 road closures: assess the dynamic traffic impact of road construction projects on Route 30 in the region; propose travel demand management (TDM) to mitigate overall impact caused by closures. The TDM plans include traffic detour plans (provided to residents via online webpages or emails), traffic signal timing on major intersections and on-site detour strategies through Dynamic Message Signs (DMS), and multi-modal transportation solutions.
    
Description
Tasks

Task 1:  Identify various data sources for in-depth data analytics

1.	Request GIS models and regional travel planning model from SPC where trip information associated in the region can be retrieved.
2.	Establish a refined GIS model for this research based upon the models from SPC and CMU Mobility Data Analytics Center (MAC). A stand-alone version of GIS with the following data is necessary for this study, which should include street names, street levels (highway, major arterials, minor streets, alleys, etc.), number of lanes, and speed limit.
3.	Obtain traffic counts on local streets and highway in this region from SPC, PennDOT and the Township. To produce accurate simulation results, 15-min traffic counts are necessary.   
4.	Obtain INRIX probe data from RITIS and HERE probe data from MAC. Those probe data cover highways in the region and major arterials within the region.
5.	Obtain traffic control timing schemes from the Township. 
6.	Obtain public transit ridership data from the Township.
7.	Obtain park-and-ride usage data from the Township
8.	Obtain project land-use development information from the Township
9.	Work with the Township and PennDOT to gather information about the construction plans for roadway closures (on Route 30), including (estimated) geographical scope of the closures, (estimated) lane closure configurations and (estimated) construction schedules. Each of those representative construction plans with the respective time frame is selected as a scenario. The scenarios will be determined by the Township and MAC on the mutual interests of all parties.


Deliverable:
•	Provide a detailed report on data collection efforts to include a list of data sources available in the region to model non-recurrent traffic. Also, include a list of scenarios to represent potential construction plans and/or incidents. The scenarios include lane configurations, dates, and/or time-of-day closure schedules.


Task 2:  Establishing a dynamic network model for the North Huntingdon Township Region

We will use mesoscopic traffic flow models to conduct this research task. We will develop a dynamic network model that provides estimated day-to-day origin-destination demand among all Traffic Analysis Zones that vary by time of day. The route choices and modal choices for all travelers in the region will be examined and carefully calibrated using data sets collected in Task 1. The network model is capable of estimating network-wide traffic impact caused by any incident based upon a generic regional network consisting of freeway and major arterials. It has the capacity of modeling dynamic traffic evolution with the consideration of real-time travel control and traffic demand management. It adopts state-of-the-art traffic models and is much more computationally efficient than other microscopic models that are extremely labor intensive to build.

The regional network, together with construction plans for Route 30, will be coded into the dynamic network model. Baseline travel demand will be estimated in the first place using the integrated traffic data on typical weekdays without the presence of construction projects (nor unplanned incidents). 

In addition, the overall traffic impact for each scenario (defined in Task 1) can be measured by time-of-day traffic evolution in the region, as well as performance metrics, such as total traffic delay, average travel time, emissions, energy use, vehicle-miles traveled, etc.

Deliverable: 
•	Provide a detailed report on modeling efforts and findings.


Task 3:  Modeling construction projects and multi-modal solutions to mitigate impacts
The scenarios of roadway closures will be modeled based on the calibrated regional network model. The simulation adopts the historical traffic demand and their pre-scribed route/modal choices from the dynamic network model built in Task 2. 

For each of the scenarios, we will propose a holistic TDM solutions to mitigate the impact of construction projects. The TDM plans include traffic detour plans (provided to residents via an online information system or emails to residents), traffic signal timing changes on major intersections, on-site detour strategies through Dynamic Message Signs (DMS), and public transit solutions.

Deliverables:
•	Provide a tool that provides details regarding construction projects and mitigation plans to the public. 
•	Suggestion a multi-modal solution to the Township.
•	Provide a report on modeling efforts and findings.


Task 4:  Final Report and Final Deliverables
Summarize all findings in the final report and deliver a prototype online information system providing traffic information, construction project details and mitigation plans to the public. 

Deliverable:
•	An online information system that provides details regarding construction projects and mitigation plans to the public
•	Submit Final Report.
    
Timeline
July 1, 2019 - June 30, 2020    
Deployment Plan
We will work closely with the township on a holistic TDM solutions to mitigate the impact of construction projects. The TDM plans include traffic detour plans (provided to residents via an online information system or emails to residents), traffic signal timing changes on major intersections, on-site detour strategies through Dynamic Message Signs (DMS), and public transit solutions.    
Expected Accomplishments and Metrics
•	Provide a tool that provides details regarding construction projects and mitigation plans to the public. 
•	Suggestion a multi-modal solution to the Township.
•	Provide a report on modeling efforts and findings.

time-of-day traffic evolution in the region, as well as performance metrics, such as total traffic delay, average travel time, emissions, energy use, vehicle-miles traveled, etc.    

Individuals Involved

Email Name Affiliation Role Position
arnav@cmu.edu Choudhry, Arnav CMU Other Student - PhD
bethannh@andrew.cmu.edu Hockenberry, Beth Carnegie Mellon University Other Other
seanqian@cmu.edu Qian, Sean CMU PI Faculty - Untenured, Tenure Track
weiran@cmu.edu Yao, Weiran CMU Other Student - PhD

Budget

Amount of UTC Funds Awarded
$85887.45
Total Project Budget (from all funding sources)
$138622.00

Documents

Type Name Uploaded
Data Management Plan dmp_NHD.docx May 16, 2019, 11:59 a.m.
Progress Report 306_Progress_Report_2019-09-30 Sept. 23, 2019, 8:42 p.m.
Progress Report 306_Progress_Report_2020-03-31 March 23, 2020, 9:46 p.m.
Final Report Final_Report_-_306.pdf Sept. 1, 2020, 5:55 a.m.

Match Sources

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Partners

Name Type
North Huntingdon Township Deployment Partner Deployment Partner