Urban freight transport is primarily fulfilled by commercial road vehicles. Within cities, overnight parking is a critical element influencing commercial vehicle operations, particularly for heavy vehicles with limited parking options. Providing adequate overnight parking spaces for commercial vehicles tends to be a challenge for urban planners. Inadequate parking supply can result in illegal parking and additional vehicle kilometers traveled, contributing to traffic congestion and air pollution. The lack of tools for evaluating the impacts of changing parking supply is an impediment in developing parking-related solutions that aim to minimize the negative externalities. In this study, we develop an overnight parking choice model for heavy commercial vehicles and integrate it with SimMobility, an agent-based urban simulation platform, demonstrating the potential of this tool for policy evaluation. Using simulations applied to a case study in Singapore, we compare two parking supply scenarios in terms of vehicle kilometers traveled due to changes in the first and last trips of vehicle tours, as well as resulting impacts in traffic flows.

中文翻译：

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使用基于代理的模拟评估城市商用车辆的夜间停车基础设施政策

城市货运主要由商用道路车辆完成。在城市内，夜间停车是影响商用车运营的关键因素，尤其是对于停车选择有限的重型车辆。为商用车辆提供充足的夜间停车位往往是城市规划者面临的挑战。停车供应不足会导致非法停车和额外的车辆行驶公里数，从而导致交通拥堵和空气污染。缺乏用于评估停车供应变化影响的工具阻碍了开发旨在最小化负面外部性的停车相关解决方案。在这项研究中，我们为重型商用车开发了一个夜间停车选择模型，并将其与基于代理的城市模拟平台 SimMobility 集成，展示了该工具在政策评估方面的潜力。使用应用于新加坡案例研究的模拟，我们比较了两种停车供应场景，因为车辆行驶的第一次和最后一次行程的变化导致车辆行驶公里数，以及由此产生的交通流量影响。