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Recently, an open-source light-weight dynamic traffic assignment (DTA) package, namely DTALite, has been developed to allow a rapid utilization of advanced dynamic traffic analysis capabilities. Aiming to bridge the modeling gaps between multi-agent simulation and optimization in a multimodal environment, we further design and develop DTALite-S to simplify the traffic flow dynamic representation details in DTALite for future extensions. We hope to offer a unified modeling framework with inherently consistent space–time network representations for both optimization formulation and simulation process. This paper includes three major modeling components: (1) mathematic formulations to describe traffic and public transportation simulation problem on a space–time network; (2) transportation transition dynamics involving multiple agents in the optimization process; (3) an alternating direction method of multipliers (ADMM)-based modeling structure to link different features between multi-agent simulation and optimization used in transportation. This unified framework can be embedded in a Lagrangian relaxation method and a time-oriented sequential simulation procedure to handle many general applications. We carried out a case study by using this unified framework to simulate the  passenger traveling process in Beijing subway network which contains 18 urban rail transit lines, 343 stations, and 52 transfer stations. Via the ADMM-based solution approach, queue lengths at platforms, in-vehicle congestion levels and absolute deviation of travel times are obtained within 1560 seconds.The case study indicate that the open-source DTALite-S integrates simulation and optimization procedure for complex dynamic transportation systems and can efficiently generate comprehensive space-time traveling status.

urban rail transit

Open-Source Public Transportation Mobility Simulation Engine DTALite-S: A Discretized Space–Time Network-Based Modeling Framework for Bridging Multi-agent Simulation and Optimization