Enhancing Traffic Signal Controller Performance using LiDAR data.

Enhancing Traffic Signal Controller Performance Using LiDAR Data applies software-in-the-loop testing to a previously developed approach for optimizing traffic signal timings to reduce vehicle delays and increase throughput at signalized intersections, serving as a first step prior to field deployment. Field data will be gathered at a single signalized intersection using LiDAR equipment to investigate the potential of LiDAR data for the field evaluation of traffic signal controllers. Using the field data, optimized signal timings will be computed and implemented in a simulation environment along a segment of a major arterial. Conducted in collaboration with the Virginia Department of Transportation (VDOT), the study builds on the team’s prior work demonstrating that traditional methods such as the Webster formulation overestimate cycle lengths and fail to minimize delay under congested conditions, and applies a new Laguna-Du-Rakha (LDR) formulation that minimizes delay while reducing stops, deceleration, and acceleration at signalized intersections. The project will collect LiDAR field data at the signalized intersection of Cloverdale Road and Lee Highway to evaluate the suitability of these data for the field evaluation of signal control strategies. The team will compute optimum cycle lengths using the LDR formulae, extract vehicle trajectory data for the computation of queue lengths, delays, stops, and fuel and energy consumption, and construct and calibrate a simulation network of the intersection. Four signal timing plans, fixed-time and actuated control based on both the Webster and LDR methods, will be implemented and evaluated across ten traffic demand levels, with emphasis on high-demand conditions where the LDR formulation provides the greatest benefit. Pedestrian data will also be collected and incorporated.

Language

  • English

Project

Subject/Index Terms

Filing Info

  • Accession Number: 01998033
  • Record Type: Research project
  • Source Agency: Sustainable Mobility and Accessibility Regional Transportation Equity Research Center
  • Contract Numbers: 69A3552348303
  • Files: UTC, RIP
  • Created Date: Aug 1 2026 9:50AM