Including Right-of-Way in a Joint Large-Scale Agent-Based Dynamic Traffic Assignment Model for Cars and Bicycles

Intersections typically account for a substantial part of the total travel time in urban areas, and an even higher share of the congested travel time, especially for bicycle traffic. Nevertheless, delays caused by yielding for cyclists or cars at intersections have previously not been modelled in large-scale bicycle traffic assignment models. This study proposes a computationally efficient large-scale applicable methodology for explicitly modelling yielding for conflicting moves at multi-modal intersections in an agent-based traffic assignment model. Nodes representing the intersections are classified into five node types that simulate potential moves across nodes differently while obeying right-of-way and preventing simultaneous conflicting moves. The methodology is implemented within a joint assignment model capable of modelling on-link congestion of both car and bicycle traffic and is applied to a large-scale case study of a Metropolitan Copenhagen network with 144,060 nodes and 572,935 links. The MATSim case study with 4,593,059 trips shows manageable computation times similar to when not modelling right-of-way at intersections. Especially for car traffic, yielding at intersections imposes considerable excess travel time. The effects are larger for trips going to the central part of the city where the inter-modal impact of conflicting bicycle traffic is identified as a major source of added travel time. The study finds that failing to model conflicting moves at intersections generally underestimates travel times and causes too much traffic to go through the urban core, highlighting the importance of joint modelling of intersections.