Urban Transportation System Analytics and Optimization: A Sensor Data-Driven Approach

Sensor data, from vehicles and facilities, is revolutionizing how urban transportation systems operate. Pre-trip route choices can be informed by network status, en-route path choices can be predicated on evolving conditions, prices can influence path choice decisions, and more robust network operating conditions can be obtained. Careful placement of sensing equipment can enhance system observability in and controllability. This study has explored new and creative ways to use sensor data to 1) enhance freight-related path choice, both pre-trip and en-route, and 2) improve the performance of urban networks more generally from a freight perspective. While a significant body of literature exists on both path choice and traffic assignment, this study presents new and creative ways to address these topics predicated on real-time data and a freight-first mentality. These new methods can lead to better freight-focused routing decisions and network operating conditions whose performance for freight is improved and can be assessed statistically. Two specific research objectives have been targeted. The first is creation of new data-driven, truckoriented path choice algorithms. The second is a data-informed, freight-focused traffic assignment model. Both these efforts have produced results that can enhance freight flows and at the same time mitigate congestion. The efforts build on previous research efforts in which the authors were involved plus findings from projects in which they have collaborated.

• Record URL:
  • http://ntc.umd.edu/sites/default/files/documents/research/NTC2016-MU-R-01.pdf
• 
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  National Transportation Center at Maryland

  1124 Glenn Martin Hall
  University of Maryland
  College Park, MD  United States  20742

  North Carolina State University, Raleigh

  Department of Civil, Construction and Environmental Engineering
  Raleigh, NC  United States  27695-7908

  Arizona State University, Tempe

  School of Sustainable Engineering and the Built Environment
  P.O. Box 875306
  Tempe, AZ  United States  85207-5306

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • List, George
  • Addison, Jeremy
  • Byrom, Elizabeth
  • Zhou, Xuesong
  • Liu, Tony
• Publication Date: 2018-7

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; References; Tables;
• Pagination: 116p

Subject/Index Terms

• TRT Terms: Decision making; Freight traffic; Optimization; Route choice; Sensors; Shortest path algorithms; Traffic assignment; Travel time; Urban transportation
• Subject Areas: Data and Information Technology; Freight Transportation; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01678959
• Record Type: Publication
• Report/Paper Numbers: NTC2016-MU-R-01
• Files: UTC, TRIS, ATRI, USDOT
• Created Date: Aug 27 2018 2:05PM