Incorporating within link dynamics in an agent-based computationally faster and scalable queue model

The growing pace of urbanization increases the need of simulation models to handle large-scale scenarios in reasonable time. The present study proposes a fast spatial queue model, which is anchored to an agent-based travel demand simulation framework. The existing queue model is extended to produce more realistic flow dynamics by introducing backward travelling holes to mixed traffic conditions. In this approach, the space freed by a leading vehicle is not immediately available to the following vehicle. The resulting dynamics resembles Newell's simplified kinematic wave model. The space freed corresponding to each leaving vehicle is named as hole' and, as following vehicles occupy the space freed by leading vehicles, the hole travels backward. This results in triangular fundamental diagrams for traffic flow. The robustness of the model is tested with flow density and average bike passing rate contours. Spatio-temporal trajectories are presented to differentiate the queuing patterns. Finally, a comparison of the computational performance of the different link and traffic dynamics of the queue model is made.