Research On Route Selection Method And Reliability Optimization Of Emergency Vehicles

Under the background of the rapid development of domestic social economy and the continuous expansion of urban scale,the number of residents’ cars ownership is also increasing year by year,and urban congestion occurs frequently,resulting in travelers spending too much time on the road during the journey.The driver makes a preliminary judgment on the future traffic state in advance based on the historical traffic state of the road network,and then plans the travel path.And selection of travel path often pursues the shortest and reliable travel time along the way,especially for police cars,fire trucks or ambulances and other emergency vehicles in the implementation of the task,they need to quickly respond to time-critical firefighting tasks,medical assistance,etc.,to ensure the quality of emergency response.However,in fact,the time variation of traffic flow in urban road network could lead to the randomness of the running time of vehicles on the road section,so the route selection problem needs to consider both the shortest time and variability of time,so that the driver or emergency management department can make a decision on travel.When the emergency management department receives the emergency task,after the path planning,how to further reduce the delay in the travel process and ensure the emergency vehicles arrive at the mission site quickly.the optimization research of path selection and reliability is of great significance to emergency management departments and traffic management departments.Firstly,this research model the emergency vehicle section travel time based on the operating characteristics of emergency vehicles,and the model reflects the relationship between the traffic volume of the links and the travel time of the emergency vehicle.Considering the temporal and spatio relevance of the urban road network traffic flow,a spatio-temporal graph convolutional traffic flow prediction model is established,and the emergency vehicle travel time calculation model is used to convert the predicted traffic volume into the emergency vehicle travel time on road segment,so that the travel time of emergency vehicles can be predict indirectly through each road segment in the road network,and establish the basis for travel route selection of emergency vehicle.Secondly,according to the long-tail characteristics of the road segment travel time distribution of emergency vehicles,a variety of skew distribution models are used to fit the travel time of each road segment to describe the degree of dispersion of the road segment travel time in the distribution,combined with the emergency of each road segment The prediction result of the vehicle travel time,the early passage of the road and the delay of the vehicle running on the road,and the introduction of a reward and punishment mechanism to establish a utility model for measuring the travel time of the emergency vehicle.And then according to the time of the emergency vehicle arriving at each road segment.then proposed a method of mergency vehicle route selection with the goal of minimizing the total travel time of the route is.Then,on this basis,a novel index which is suitable for measuring the travel time reliability of emergency vehicles is proposed.Then,explored and analyzed the influence of the length of the road section,the number of lanes and the traffic volume of the road segment on the reliability,and carried out a regression analysis traffic volume on the road segment and reliability indicators.On this basis,established a path to minimize the utility value of the path travel time.Optimization model to optimize the travel route of emergency vehicles.Finally,taking Yuzhong District of Chongqing City as a case for empirical analysis,applying the emergency vehicle routing and optimization methods proposed in this article,Compared with the utility value of path travel time before optimization,it is shortened by30.31 s.It demonstrates the rationality and effectiveness of this research,which can ensure rapid response to emergency tasks to a certain extent.