Using agent-based vehicle traffic models to analyze traffic flow

Abstract

This thesis discusses the creation of an agent-based model for vehicle traffic that uses a previously developed mathematical car-following micro-simulation model. The agent-based model results are verified against the original model. The agent-based model is then used to explore the effects of inclement weather and autonomous drivers on traffic to explore the suitability of using the agent-based approach to model traffic. The primary environment focused on is a signalized four-way intersection, with an extension to freeways for autonomous vehicle simulation. The model is used to demonstrate how optimizing green light intervals at intersections based on current weather conditions can help to partially restore traffic throughput to normal condition levels. Results from simulations with autonomous vehicles demonstrate that traffic flow steadily increases as these vehicles enter the driving population. In the case of signalized intersections this improvement increases in inclement weather, but increases are flat across different weather conditions for freeways.