Vehicle shortest time traffic path processing method based on time delay Petri network

Abstract

The invention belongs to the technical field of traffic path planning, and discloses a vehicle shortest-time traffic path processing method based on a time delay Petri net. The method comprises the steps: carrying out the modeling of a known traffic path graph through the time delay Petri net, and enabling a complex traffic path to be expressed in a concise mode through the time delay Petri net; calculating a reachability graph of the model, and when a vehicle departs from the starting point, selecting a path at each intersection according to a heuristic function, and converting a process of reaching a target point into a process of calculating a shortest time sequence from an initial identifier to a target identifier. In the invention, the algorithm for calculating the shortest time sequence is suitable for urban traffic modeled by a time delay Petri network, wherein a shortest time path is searched for vehicles, and the algorithm aims to relieve urban local traffic congestion and reduce travel. According to the invention, the real traffic environment is modeled by using the time delay Petri network, and the vehicle is simulated to select the optimal path to arrive at the destination in real-time traffic, so that congestion is avoided and time is saved.

Description

technical field [0001] The invention belongs to the technical field of traffic route planning, and in particular relates to a method for processing traffic routes in the shortest time for vehicles based on a time-delayed Petri net. Background technique [0002] At present, as an important mathematical modeling tool, Petri net is widely used in flexible system model, computer integrated manufacturing, artificial intelligence, system analysis and other fields. Behavioral techniques. However, the simulation ability of the prototype Petri net is limited, and the expansion of the prototype Petri net can improve its simulation ability. The time-delayed Petri net is an important Petri net with time factors, which has been widely used in the modeling of concurrent systems. By assigning a certain time to the place (P) or transition (T) to simulate the real system environment, in In time-delayed Petri nets, the transition transmission sequence that takes the shortest time from initi...

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Problems solved by technology

[0003] In recent years, with the development of network technology, communication technology and information technology, scholars have proposed many algorithms for the optimization algorithm of the shortest time path in delayed Petri nets, but some methods still have some deficiencies, which are specifically reflected as follows: 1. The classic one is the Dijkstra algorithm, which can basically realize the problem of accessibility and launch sequence calculation, and find the path from the initial identification to the target identification by searching the partial reachability graph, but the problem is that when the initial identification and the target identification are far apart The time-reachable graph can become very large, causing the search difficulty to increase exponentially

2. Based on the partial reachability graph search algorithm, the algorithm needs to rely on the selection of parameters, and the results obtained for different parameters are very different, and the algorithm cannot prove that the final result is optimal

3. The ant colony algorithm is used to solve problems that do not have a mature algorithm. The convergence time depends on the selected parameters and can only be applied to small-scale problems.

[0005] (1) The existing Dijkstra algorithm has the problem that the reachable graph will become very large when the initial mark and the target mark are far apart, resulting in an exponential increase in search difficulty, and the use of the search for the shortest time path will result in longer search time. For Practical vehicle navigation has limitations

[0006] (2) The results obtained by the existing partial reachable graph search algorithm for different parameters are very different, and the algorithm cannot prove that the final result is optimal. If it is applied in actual engineering, the parameter selection for different paths There is a large difference, the calculation result may be quite different from the actual shortest time path, and there is no guarantee that the desired result is optimal

[0007] (3) The convergence time of the existing ant colony algorithm depends on the selected parameters, which can only be applied to small-scale problems; the same is true for the ant colony algorithm, which depends on the selection of parameters, and there is a big difference in the selection of parameters when choosing different paths. The optimal path may not necessarily be obtained

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