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Simulation-based Optimization of Mixed Road Pricing Policies in a large Real-world Network

机译：大型现实网络中基于仿真的混合道路定价策略优化

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摘要

The joint optimization of various types of road pricing strategies for a large-scale real-world network is challenging. Dynamic network supply models can overcome this shortcoming, and provide more detailed information regarding the system performance. However, the computational burden of simulation is still a big challenge for the optimization. Utilizing a simulation-based dynamic traffic assignment model, this paper proposes a simulation-based optimization method to solve the mixed road pricing problem, which is characterized by expensive-to-evaluate and non-closed-form multi-objectives. The mixed road pricing problem is formulated to satisfy dynamic user equilibrium conditions. It enables to capture the time-varying network performance via dynamic traffic assignment. The simulation-based optimization method is successfully applied to the joint optimization of a variety of toll facilities in a real-world network of the Montgomery County in Maryland, i.e. an HOT lane, express toll lanes, and a toll road.
机译：对于大规模的现实世界网络，各种道路定价策略的联合优化具有挑战性。动态网络供应模型可以克服此缺点，并提供有关系统性能的更多详细信息。但是，仿真的计算负担仍然是优化的一大挑战。利用基于仿真的动态交通分配模型，提出了一种基于仿真的优化方法来解决混合道路收费问题，该方法具有评估成本高和非封闭式多目标的特点。制定混合道路定价问题以满足动态用户平衡条件。它可以通过动态流量分配来捕获时变网络性能。基于模拟的优化方法已成功应用于马里兰州蒙哥马利县的现实世界网络中的各种收费设施的联合优化，即HOT车道，快速收费车道和收费公路。

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