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Simultaneous internalization of traffic congestion and noise exposure costs

机译：同时内部化交通拥堵和噪声暴露成本

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摘要

This study elaborates on the interrelation of external effects, in particular road traffic congestion and noise. An agent-based simulation framework is used to compute and internalize user-specific external congestion effects and noise exposures. The resulting user equilibrium corresponds to an approximation of the system optimum. For traffic congestion and noise, single objective optimization is compared with multiple objective optimization. The simulation-based optimization approach is applied to the real-world case study of the Greater Berlin area. The results reveal a negative correlation between congestion and noise. Nevertheless, the multiple objective optimization yields a simultaneous reduction in congestion and noise. During peak times, congestion is the more relevant external effect, whereas, during the evening, night and morning, noise is the more relevant externality. Thus, a key element for policy making is to follow a dynamic approach, i.e. to temporally change the incentives. During off-peak times, noise should be reduced by concentrating traffic flows along main roads, i.e. inner-city motorways. In contrast, during peak times, congestion is reduced by shifting transport users from the inner-city motorway to smaller roads which, however, may have an effect on other externalities.
机译：这项研究详细阐述了外部影响的相互关系，特别是道路交通拥堵和噪音。基于代理的仿真框架用于计算和内部化特定于用户的外部拥塞效应和噪声暴露。最终的用户平衡相当于系统最佳值的近似值。对于交通拥堵和噪音，将单目标优化与多目标优化进行比较。基于仿真的优化方法已应用于大柏林地区的实际案例研究。结果表明，拥塞与噪声之间呈负相关。然而，多目标优化可同时减少拥塞和噪声。在高峰时段，拥塞是更相关的外部影响，而在晚上，晚上和早晨，噪音是更相关的外部影响。因此，决策的关键要素是遵循动态方法，即暂时改变激励措施。在非高峰时段，应通过集中沿主要道路（即市区高速公路）的交通流来减少噪声。相反，在高峰时段，通过将运输用户从市区高速公路转移到较小的道路，可以减少拥堵，但是这可能会影响其他外部性。

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