Enabling Next-Generation Safe, Efficient and Reliable Traffic Signal Management via Advanced Sensing and Foundation Models

Urban traffic signal management systems often rely on outdated techniques and strategies that fail to adapt to dynamic roadway conditions, leading to safety concerns, congestion, and access issues for road users. In addition, current signal optimization approaches rarely consider energy efficiency as the main objective. This research proposes a next-generation safe, efficient and reliable traffic signal control framework powered by advanced roadside sensing and foundation models, specifically Visual Language Models (VLMs) and Multi-Modal Large Language Models (MMLLMs). By integrating high-definition cameras, LiDAR, and real-time data analytics, the system will accurately detect multimodal traffic flows, predict future traffic conditions, and optimize signal phase and timings to enhance mobility while minimizing energy consumption. The framework will be validated through a case study at the Riverside Smart Intersection testbed, leveraging real-world data and co-simulation environments.

• Record URL:
  • https://ncst.ucdavis.edu/project/enabling-next-generation-safe-efficient-and-reliable-traffic-signal-management-advanced

Language

• English

Project

• Status: Active
• Funding: $150,000.00
• Contract Numbers:

  DOT 69A3552348319

  DOT 69A3552344814

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590

  National Center for Sustainable Transportation

  University of California, Davis
  Davis, CA  United States 

  University of California, Riverside

  1084 Columbia Ave.
  Riverside, CA  United States  92507
• Managing Organizations:

  National Center for Sustainable Transportation

  University of California, Davis
  Davis, CA  United States 

  University of California, Davis

  1 Shields Ave
  Davis, California  United States  95616

  University of California, Riverside

  1084 Columbia Ave.
  Riverside, CA  United States  92507
• Project Managers:

  Cliff, Sydney

• Performing Organizations:

  National Center for Sustainable Transportation

  University of California, Davis
  Davis, CA  United States 

  University of California, Riverside

  1084 Columbia Ave.
  Riverside, CA  United States  92507
• Principal Investigators:

  Wu, Guoyuan

  Li, Jiachen

• Start Date: 20260401
• Expected Completion Date: 20270331
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Artificial intelligence; Energy efficiency; Simulation; Traffic signal control systems; Urban areas
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01985472
• Record Type: Research project
• Source Agency: National Center for Sustainable Transportation
• Contract Numbers: DOT 69A3552348319, DOT 69A3552344814
• Files: UTC, RIP
• Created Date: Apr 12 2026 11:42PM