BALANCING PEDESTRIAN AND VEHICULAR NEEDS IN URBAN ENVIRONMENTS: AN AGENT BASED SIGNAL TIMING STUDY

Urban environments are increasingly challenged by the need to accommodate rising travel demand while preserving walkability, safety, and public-realm quality. Aggregate signal-timing methods often miss how micro-scale behavior or geometry changes shape delay and movement. The study develops an agent-based model of a mixed-use downtown grid in which vehicles, pedestrians, and signal controllers act as autonomous agents. The framework enables planners to test signal retiming, driver-courtesy campaigns, and adaptive control before deployment. The study aims to assess how modest design and behavioural interventions influence performance across different travel modes and planning priorities. Results show a clear pedestrian–vehicle trade-off and an interior signal-cycle length that minimizes total system delay. Increasing driver courtesy yields large reductions in pedestrian delay with limited impacts on vehicles. The study concludes that agent-based modeling can align operational performance with urban-planning objectives and recommend embedding calibrated digital twins into planning workflows for evidence-based evaluation of zoning decisions, traffic policy, and street design. Finally, because the model is intentionally stylised, its outputs are best interpreted as context-dependent heuristics rather than site-specific prescriptions. For operational use, the framework can be lightly calibrated with GIS-derived network geometry and local volumes and then applied to compare scenarios, rather than to forecast absolute delay levels. Keywords: Agent-based modelling, signal timing, pedestrian delay, urban planning, traffic safety.