This study develops a mathematical optimization approach to manage the traffic mobility and carbon emission of a multimodal road network through period-to-period combined traffic pricing and subsidy scheme. The current approach considers interaction between traffic modes and explicitly formulates it into a general day-to-day traffic dynamics model, making it apply to a more general road network. In addition, the established optimization model takes both efficiency and environment into account the model objective, and allows for more practical and flexible settings on problem constraints or objectives. A constrained compass search algorithm is applied to solve the model with poor properties. In the end, numerical experiments are performed to demonstrate the effectiveness of the methodology. It is found that the constrained compass search algorithm shows desirable effectiveness and robustness, and the combined pricing and subsidy strategy is much more effective than a single strategy in improving the network mobility and reducing emission. We also find that the effectiveness of ticket discount is much lower than that of increasing frequency under a wide range of passengers’ value of time. This implies that a superior way of leveraging the money obtained from traffic congestion pricing would be subsiding the bus system for raising its departure frequency.

中文翻译：

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通过定期定价和补贴计划管理双模式道路网络的日常交通流动和排放


本研究开发了一种数学优化方法，通过周期性的交通定价和补贴计划相结合来管理多式联运道路网络的交通流动性和碳排放。当前的方法考虑了交通模式之间的相互作用，并将其明确地表述为一般的日常交通动态模型，使其适用于更一般的道路网络。此外，建立的优化模型同时考虑了效率和环境的模型目标，并允许对问题约束或目标进行更加实用和灵活的设置。采用约束罗盘搜索算法来求解性能较差的模型。最后，进行数值实验来证明该方法的有效性。研究发现，约束罗盘搜索算法表现出良好的有效性和鲁棒性，并且组合的定价和补贴策略在提高网络移动性和减少排放方面比单一策略更有效。我们还发现，在旅客时间价值范围较大的情况下，机票折扣的效果远低于增加班次的效果。这意味着利用交通拥堵定价获得的资金的更好方法是补贴公交系统以提高其发车频率。