Advanced Technologies and Data Analytics for Safe, Smart, and Efficient Transportation (ASSET)

This project assists the Massachusetts Department of Transportation (MassDOT) with (A) calibrating safety models for urban and suburban arterial intersections and developing artificial intelligence models for (B) detecting sidewalks and (C) counting multimodal trips. There are three main goals: (A) Calibrate the Safety Performance Functions (SPFs) in Chapter 16.6.4 of the Highway Safety Manual, 2nd Edition (HSM2), along with the associated parameters, for the twelve types of urban and suburban intersections in Massachusetts using the most recent data. (B) Develop an Artificial Intelligence (AI) model to automate the detection and mapping of sidewalks from publicly available aerial imagery. Also, the model will be used to identify changes in sidewalks using aerial imagery from multiple years. (C) Leverage AI to automate the counting of pedestrians, active transportation modes (such as bicycles and e-scooters), and site-generated trips from new developments. The results of this task will form the basis for developing AI and/or statistical models to estimate multimodal trip counts required for transportation planning purposes.

Language

  • English

Project

  • Status: Active
  • Funding: $604,334.00
  • Contract Numbers:

    129892

  • Sponsor Organizations:

    Massachusetts Department of Transportation

    10 Park Plaza
    Boston, MA  United States  02116
  • Managing Organizations:

    University of Massachusetts Lowell

    One University Drive
    Lowell, MA  United States  01854
  • Principal Investigators:

    Xie, Yuanchang

  • Start Date: 20250429
  • Expected Completion Date: 20261231
  • Actual Completion Date: 0

Subject/Index Terms

Filing Info

  • Accession Number: 01991800
  • Record Type: Research project
  • Source Agency: Massachusetts Department of Transportation
  • Contract Numbers: 129892
  • Files: RIP, STATEDOT
  • Created Date: Jun 3 2026 3:27PM