高速公路突发事件救援车辆诱导

为了提升高速公路突发事件应急救援效率，将交通状况、在途潜在风险等信息纳入高速公路突发事件救援车辆诱导研究中，基于实时和时变路网环境下的交通信息，以车辆出行时间最小，路径可靠性最强为目标，构建基于在途时间和路径可靠性的车辆诱导最优化模型。设计一种实时信息和时变信息结合策略，使模型规划路径随路网交通量变化而相应做出阶段性调整，采用滚动时域策略将该动态决策问题转化为一系列离散时间点的静态决策问题，用于计算应急救援路径时间；在此基础上，考虑到高速公路突发事件发生后路网交通事故率升高，同时容易发生拥堵的状况，进一步将救援规划路径可靠性作为决策目标，即应急救援车辆规划路径在面对道路中断或者严重拥堵时是否拥有更多的调整策略，更新救援路径尽快完成救援任务；为了便于量化计算将上述目标转化为统一的价值成本，共同决定救援车辆的行驶路径。研究结果表明：当行驶路段交叉口间距离较长，中间无其他道路连通，行驶过程中由于突发事件破坏趋势蔓延导致道路中断或拥堵等意外发生时，无法更新调整救援路径，最终导致救援延误；因此，基于救援时间和路径可靠性的车辆诱导最优化模型能够克服以上问题，进一步提高救援效率。

Vehicle Scheduling for Mountainous Expressway Traffic Emergency

In order to improve the efficiency of emergency rescue in expressway emergencies, the traffic conditions, potential risks on the road, and other traffic information were considered in this study of highway emergency rescue vehicle induction. Based on traffic information in a real-time and time-varying road network environment, the goal is to minimize the travel time of vehicles and obtain the strongest path reliability. In this paper, a combined strategy of real-time and time-varying information model is proposed so that the path planning can be adjusted periodically according to changes in road network traffic volume. The dynamic decision-making problem was transformed into a series of static decision-making problems at discrete time points by rolling time-domain strategy, which were then used to calculate the emergency rescue path time. On this basis, the traffic accident rates on a road network were increased, which is likely to cause congestion. This study further considered the reliability of the rescue path planning as the decision target. That is, the emergency rescue vehicle path planning has more adjustment strategies in the face of road interruptions or severe congestion in order to update the rescue path and complete the rescue task as soon as possible. In order to facilitate calculation, the above factors were converted into unified cost values. The research results showed that when the distance between road intersections is relatively large and there are no other road connections in the middle, the road interruptions or congestion caused by the spread of the destruction trend of emergencies in the driving process, the rescue path cannot be updated and adjusted, resulting in rescue delay. Therefore, the vehicle induction optimization model based on rescue time and path reliability can overcome the abovementioned problems and further improve rescue efficiency.