New Methodology for Intersection Signal Timing Optimization to Simultaneously Minimize Vehicle and Pedestrian Delays

Abstract

This study introduces a new methodology for signal timing optimization that is carried out by adjusting green splits of a.m. peak, p.m. peak, and rest of the day timing plans for each signalized intersection in the urban street network without changing the existing cycle length and signal coordination to minimize total vehicle and pedestrian delays per cycle. It contains a basic model that handles vehicle delays only and an enhanced model that simultaneously addresses vehicle and pedestrian delays using two different pedestrian delay estimation methods. Both models are incorporated into a high fidelity simulation-based regional travel demand forecasting model for detailed traffic assignments. A computational study is performed for methodology application using data on Chicago metropolitan area travel demand, traffic counts, geometric designs, and signal timing plans for major intersections in the Chicago central business district (CBD) area. A sensitivity analysis is conducted in the application of the enhanced model to examine the impacts of assigning different weights to vehicle and pedestrian delays on intersection vehicle travel time and delay reductions after signal timing optimization. The computational experiment reveals that after systemwide signal timing optimization, vehicle delays in the CBD area could reduce by 13% when considering only vehicle delays and by 5% when simultaneously considering vehicle and pedestrian delays.