To manage traffic emergencies, cities require multiple types of traffic rescue vehicles, which need to be dispatched from various rescue stations dispersed throughout the city. A reasonable way of deploying the rescue vehicles must be determined given that the times and locations at which the traffic emergencies occur are uncertain. In this paper, we propose a two-stage stochastic programming approach to deploying multiple types of emergency vehicles in response to traffic accidents in the context of uncertainty. The first stage of the proposed model concerns decisions on the quantities of the different types of vehicles to be stocked at each rescue station. In the second stage, when the locations and accident rescue demands are realized in each scenario, the decision-making involves dispatch of the emergency vehicles to the traffic accidents. To solve the proposed model, we suggest a variable neighborhood search method. Using the road network of Jiading District, Shanghai, as an example, we perform numerical experiments to investigate the efficiency of the proposed method and the model validity. Some managerial implications are also outlined in the sensitivity analysis.

中文翻译：

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不确定性下的交通应急车辆调配与调度

为了应对交通突发事件，城市需要多种类型的交通救援车辆，这些车辆需要从分散在城市各处的各个救援站出动。在交通突发事件发生的时间和地点不确定的情况下，必须确定救援车辆的合理部署方式。在本文中，我们提出了一种两阶段随机规划方法，用于在不确定的背景下部署多种类型的应急车辆以应对交通事故。拟议模型的第一阶段涉及决定每个救援站库存的不同类型车辆的数量。第二阶段，当了解了每种场景的地点和事故救援需求后，决策涉及向交通事故派遣应急车辆。为了解决所提出的模型，我们建议采用可变邻域搜索方法。以上海市嘉定区路网为例，通过数值实验验证了所提方法的效率和模型的有效性。敏感性分析中还概述了一些管理影响。