Optimal path planning algorithm for travel time reliability
An optimal path planning and optimal path technology, applied in the field of urban traffic management, can solve the problem of not representing travel path selection, and achieve the effect of improving algorithm operation efficiency, ensuring efficiency and diversity, and good applicability
Active Publication Date: 2019-12-31
中电科新型智慧城市研究院有限公司
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In fact, the expected shortest path is not necessarily the most reliable path, which makes the expected shortest path often not represent the optimal travel route selection
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[0040] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are exemplary only, and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.
[0041] Such as Figure 1-5 As shown, a kind of optimal path planning algorithm oriented to travel time reliability proposed by the present invention includes the following steps:
[0042] S10, generating a dynamic random network adjacency matrix:
[0043]According to the geometric relationship of the actual road network, the topological relationship matrix of the road network is generated; according to the data matching...
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The invention discloses an optimal path planning algorithm for travel time reliability. The optimal path planning algorithm comprises the following steps: S10, generating a dynamic random network adjacency matrix; S20, solving an expected shortest path based on a genetic algorithm; S30, evaluating the uncertainty of the path travel time based on a Monte Carlo method; and S40, outputting an optimalpath based on the travel duration and the reliability. The initial population of the genetic algorithm is generated by introducing the random walk model based on the Markov process, so that the operation efficiency of the genetic algorithm is greatly improved. An expected optimal path set containing K dynamic random networks is outputted according to an operation result of the genetic algorithm.The time reliability of paths is evaluated through a Monte Carlo method, to give out uncertainty consumed by travel time of different paths. Finally, optimal path selection meeting requirements is outputted. A model method comprehensively considers the travel duration and reliability of the path, and the path planning result is more reliable.
Description
technical field [0001] The invention relates to the technical field of urban traffic management, in particular to an optimal route planning algorithm oriented to travel time reliability. Background technique [0002] In urban road traffic network, the problem of optimal route planning for a given OD (source and destination) is essentially the shortest path (SP) problem in graph theory network. Since the 1950s, some classic shortest path algorithms have emerged, including: Dijkstra algorithm (labeling method), Bellman-Ford algorithm, Floyd algorithm, etc. However, these classic algorithms are all based on static deterministic networks, and a large number of networks in the real world usually have dynamic and random characteristics, and the classic shortest path algorithm is usually not suitable for networks with the above characteristics. [0003] The weight value of an edge in a dynamic random network is no longer a simple constant, but a random variable that depends on tim...
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Login to View More IPC IPC(8): G06Q10/04G06N3/12G01C21/34
CPCG06Q10/047G06N3/126G01C21/3492G01C21/3446
Inventor 吴光周胡金晖黄虎
Owner 中电科新型智慧城市研究院有限公司