Dynamic path planning method based on traffic prediction

Abstract

The invention discloses a dynamic path planning method based on traffic prediction, whichcomprises the steps ofnetwork model abstraction, network stacking, and spatiotemporal rolling algorithm;the network model abstraction is conducted, specifically, a real road is transformed into a network diagram structure of nodes and weights, and the network model abstractionis divided into an upper layer network model abstraction and a lower layer network model abstraction, and the weight setting comprehensively considers the traffic flow density and the path length; the network stacking is conducted, specifically, real-time traffic information is integrated with predicted traffic information of multiple step lengths to obtain a final network model;and the spatiotemporal rolling algorithm comprises atime rolling process and a space rolling process, the traffic state is refreshed according to a certain time interval, and dynamic planning is realized. According to the dynamic path planning methodbased on traffic prediction,it can be ensured thatthe increase of the travel path is within a certain range in the case of relatively congested traffic, and the travel time is greatly shortened.

Description

technical field [0001] The invention belongs to the field of optimal path problems, specifically a dynamic path planning algorithm that comprehensively considers real-time traffic information, forecast traffic information and road length. Background technique [0002] The shortest path problem is a classic problem in graph theory, and it is also a research hotspot in the fields of geographic information science. It has a wide range of applications in the fields of transportation planning, transportation and logistics management. The actual network entity (mainly referring to the actual road network in this invention) needs to be abstracted into a network graph concept in graph theory according to its characteristics, that is, to establish a network model. After the network model is established, various network analysis methods in graph theory can be used to discuss and study it. [0003] The following introduces the relevant background technology of the optimal path problem...

AI Technical Summary

Problems solved by technology

When the graph representation method is used, whether it is an adjacency matrix or an adjacency list, a large amount of memory must be allocated for storage. In addition, this method is prepared to search all network nodes when solving the solution. When the number of network nodes is large, its The time spent on the algorithm is also difficult to meet the needs of actual operations

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