Deep learning-based vehicle path optimization method and system

Abstract

The invention discloses a deep learning-based vehicle path optimization method and system. The method includes the following steps that: real-time road data and historical road data are acquired, the acquired data are preprocessed, so that a tagged data set can be formed; a deep belief network model is constructed, and the deep belief network model is trained; the trained deep belief network model is utilized to predict all the paths from a vehicle to a destination, and the congestion coefficients of each path are output; and the paths are evaluated comprehensively based on two indexes, namely the congestion coefficients and distances, and an optimal path is outputted, wherein the optimal path is a path corresponding to the minimum linear accumulation result of the two indexes, namely a corresponding congestion coefficient and a distance. According to the method and system, through the powerful feature extraction function of the deep belief network model, required information can be obtained from multi-dimensional road traffic data, interference can be reduced, a congestion situation is predicted accurately and reasonably, path search efficiency can be improved, human-made mistakes can be reduced, and valuable time can be saved for disaster relief work.

Description

technical field [0001] The present invention relates to a vehicle route optimization method and system based on deep learning, especially for special vehicles weighing the balance between road distance and travel time in a complex urban traffic environment. Background technique [0002] In the past half century, the vehicle routing problem has been one of the research hotspots in the field of transportation. With the substantial increase of traffic flow, distance is no longer the focus of attention. Need to think more about the problem from the perspective of time. In real traffic conditions, due to the uncertainty of demand (different travel volumes of people at different time points) and uncertainty of supply (such as traffic accidents, weather reasons, road maintenance, etc.) decline), the travel time of the road section is changing within a certain range. The uncertainty of travel time greatly affects the reliability of the transportation system and causes most of the ...

AI Technical Summary

Problems solved by technology

However, these methods do not conduct an in-depth analysis of the reliability of travel routes, and the established models, methods and theories are still limited to traditional route optimization methods and ideas

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