降级路网应急救援车辆路径选择方法研究

发布时间：2018-08-04 16:26

【摘要】：社会经济的飞速发展、城市规模的不断扩大及各种不确定性因素(如降雨降雪天气、交通事故、雾霾天气以及大规模停电等)的影响可能导致发生严重危害人们生命财产安全的事件。管理人员已充分认识到了快速可靠的应急救援的重要性,而应急救援的路径选择问题是其关键。事实上,时变的交通流量、偶发的交通事故、突发的交通拥挤,交通管制等会造成路网全局或局部通行能力的衰减,引起路网容量不同程度的降级,导致车辆在路段上旅行时间存在随机性,从救援中心到事故地之间只存在随机最短路径。由于应急救援车辆路径问题具有紧急性、不确定性等特点,决定了求解常态下车辆路径问题的方法不适合应急救援问题,因此,研究降级路网的应急救援路径问题,可以弥补路网发生降级时应急救援路径选择理论研究的不足,而且对应急救援管理者的决策具有一定借鉴意义。本文主要研究路网降级时应急救援车辆的路径选择问题。首先,通过对国内外降级路网、应急救援路径选择以及行程时间可靠性三个方面的现状研究进行归纳分析,提出研究思路与整体框架。然后,在定义降级路网后,建立了降级路网行程时间期望值模型和可靠度模型；分析应急救援的特点,对照常态下车辆路径选择的影响因素,确定了影响应急救援路径选择的因素。进而针对城市路网发生降级、道路通行能力下降时,考虑拥堵点、拥堵时间的随机变化以及出行者心理决策作用,提出了以拥堵点为起点的柔性择路策略；以应急救援路径期望行程时间最短、行程时间可靠性最大为目标构建了应急救援路径选择的多目标加权规划模型；在基于基本蚁群算法基础上,提出动态调整信息素挥发因子策略、动态调整信息素策略,并改进转移概率公式,基于改进蚁群算法设计了应急救援路径选择模型的求解算法。最后,对降级路网应急救援路径选择问题进行了案例分析,比较以路径行程时间最小为目标的路径问题可知加权模型具有可行性,更符合应急救援路径选择实情。
[Abstract]:With the rapid development of social economy, the continuous expansion of urban scale and various uncertain factors (such as rainfall and snow weather, traffic accidents, The effects of haze weather and power outages can lead to serious damage to people's lives and property. Managers have fully recognized the importance of rapid and reliable emergency rescue, and the path selection of emergency rescue is the key. In fact, time-varying traffic flow, accidental traffic accidents, sudden traffic congestion, traffic control and so on will cause the overall or local capacity of the road network to decline, resulting in varying degrees of degradation of network capacity. As a result, there is randomness in the travel time of the vehicle on the road, and there is only a random shortest path between the rescue center and the accident site. Because the emergency vehicle routing problem has the characteristics of urgency and uncertainty, it is decided that the method to solve the vehicle routing problem under normal condition is not suitable for the emergency rescue problem. Therefore, the emergency rescue path problem of downgrade road network is studied. It can make up for the deficiency of the theory of emergency rescue path selection in the downgrade of road network, and it can be used for reference for emergency rescue managers to make decisions. This paper mainly studies the route selection of emergency rescue vehicle when the road network is downgraded. Firstly, the current situation of downgrade road network at home and abroad, emergency rescue path selection and travel time reliability are summarized and analyzed, and the research ideas and overall framework are put forward. Then, after defining the downgrade road network, the expected value model of travel time and reliability model of downgrade road network are established, and the characteristics of emergency rescue are analyzed, and the influencing factors of vehicle route selection under normal condition are compared. The factors that affect the choice of emergency rescue path are determined. According to the demotion of urban road network and the decline of road capacity, considering the random change of congestion point, congestion time and the role of travelers' psychological decision, a flexible road selection strategy with congestion point as the starting point is put forward. Aiming at the shortest expected travel time and maximum travel time reliability of the emergency rescue path, a multi-objective weighted programming model for emergency rescue path selection is constructed, which is based on the basic ant colony algorithm. Dynamic adjustment of pheromone volatilization factor strategy, dynamic adjustment of pheromone strategy, and improvement of transfer probability formula are proposed. Based on improved ant colony algorithm, an algorithm for solving emergency rescue path selection model is designed. Finally, a case study on the route selection of emergency rescue in downgrade road network is carried out. Compared with the path problem with the minimum path travel time as the goal, the weighted model is feasible, which is more in line with the reality of emergency rescue path selection.
【学位授予单位】：长沙理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491

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