Path-based capacity-restrained dynamic traffic assignment algorithm

This study proposes a new fast convergence path-based dynamic traffic assignment algorithm. The algorithm is based on an analytical capacity-restrained dynamic user equilibrium model, in which link travel times are temporal functions of link flows. In previous models the length of time intervals has to be much longer (about five times) than the link travel times in each time interval using the simplifying assumption that each link will be fully traversed within the time interval that a path reaches its tail node. Otherwise, these models will make large errors and will exhibit difficulties in attaining optimality. This paper tackles the problem by proposing a systematic way of link segmentation. The numerical and case study results of the proposed algorithm show its excellent performance. The algorithm rapidly converges to optimality and provides path information over time intervals, which make it suitable for evaluating the intelligent transportation systems in strategic transport planning.