Data-Driven Mobility Strategies for Multi-Modal Transportation

By using various modes (e.g., walking, cycling, automobile, public transit, etc.), multi-modal transportation systems are effective in increasing people’s travel flexibility and reducing congestion. Hence, it is critical to understand how roadway speed management strategies would affect people’s mode choices. Additionally, with advanced technology, such as connected autonomous vehicle systems, we are now facing a transition from traditional urban planning to developing smart cities. To support multimodal transportation planning, this project will pave a bridge to connect speed management strategies of conventional signalized arterial to connected vehicle corridor. The research outcomes will help decision-makers understand the data and infrastructure needs in supporting future multimodal planning tasks and speed management. Multiple data resources, such as Pems and ATSPM from UDOT and traffic sensor data from PCDOT, will be used for this study. The research team, from U of Utah and U or Arizona, will develop data-driven approaches to achieve three primary objectives. The first objective of this project is to evaluate arterial speed management plans and investigate the impact of deploying speed feedback signs. The team will explore the relationship among speed feedback signs, posted speed limit enforcement, and intersection capacity, and investigate how these features may impact multi-modal transportation mobility and safety. Particularly, the team will study how buses, vehicles, pedestrians, and bicyclists are affected by the current speed management strategies. The second objective is to understand the role of speed management strategies in supporting smart city operational functions. Starting from 2016, UDOT has launched a project to build a full Dedicated-Short-Range-Communications (DSRC) corridor for CV technology testing. In this project, the team will work closely with UDOT for studying the impact of multi-modal speed management plans on the CV corridor. The last objective is to utilize big data to understand the interrelations among speed management, safety, congestion, travelers’ route choice. The research findings will help the cities be prepared for the coming of shared self-driving cars.

• Record URL:
  https://nitc.trec.pdx.edu/research/project/1298

Language

• English

Project

• Status: Active
• Funding: $303397
• Contract Numbers:

  NITC-1298

• Sponsor Organizations:

  University of Arizona, Tucson

  PO Box 210072
  Tucson, AZ  United States  85721

  University of Utah

  Department of Civil and Environmental Engineering
  110 Central Campus Drive Suite 2000
  Salt Lake City, UT  United States  84112

  Portland State University

  Department of Civil and Environmental Engineering
  Engineering Bldg, 301D, 1930 SW 4th Ave.
  Portland, OR  United States  97201

  Pima County Public Works Administration

  130 W. Congress, 10th floor
  Tucson, Arizona  United States  85701

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  TREC at Portland State University

  1900 SW Fourth Ave, Suite 175
  P.O. Box 751
  Portland, Oregon  United States  97201
• Performing Organizations:

  University of Arizona

  College of Engineering
  1209 East 2nd Street
  Tucson, AZ  United States  85721

  University of Utah, Salt Lake City

  College of Engineering, Department of Civil Engineering
  Salt Lake City, UT  United States  84112-0561

  Portland State University

  Department of Civil and Environmental Engineering
  Engineering Bldg, 301D, 1930 SW 4th Ave.
  Portland, OR  United States  97201
• Principal Investigators:

  Wu, Yao-Jan

  Yang, Xianfeng

  Kothuri, Sirisha

• Start Date: 20190901
• Expected Completion Date: 20210131
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Arterial highways; Connected vehicles; Data collection; Mobility; Multimodal transportation; Operating speed; Speed control; Speed signs; Traffic safety
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01710783
• Record Type: Research project
• Source Agency: National Institute for Transportation and Communities
• Contract Numbers: NITC-1298
• Files: UTC, RiP
• Created Date: Jul 11 2019 6:35PM