Optimizing Network Performance through Strategic, Operational, and Real-Time Traffic Assignment Planning

This thesis addresses strategies to mitigate traffic congestion through infrastructure expansion and traffic flow optimisation, with a focus on networks that include autonomous vehicles (AVs). A novel static traffic assignment algorithm based on point-to-point shortest paths is introduced, outperforming current methods. This algorithm is then used to enhance the Discrete Network Design Problem (DNDP), achieving significant speedup. For dynamic traffic conditions, a simulation-based framework is developed to manage mixed traffic involving AVs and human drivers. Finally, an online rerouting system is proposed for managing disruptions, demonstrating that AV rerouting substantially reduces total travel cost in both medium and large-scale networks