Vehicle driving path prediction method and system

Abstract

The invention provides a vehicle driving path prediction method and system. The method includes the steps that a minimum internal storage is determined on the basis of a Hadoop platform, the largest length of a path is scanned, and an original path sequence database is evenly divided into n disjoint sub-path sequence databases; the original path sequence database and the n sub-path sequence databases are respectively uploaded to an HDFS; the n sub-path sequence databases are dispatched to different Map nodes by a master control node, each Map node executes an improved GSP algorithm, the sub-path sequence databases stored in a Map node internal storage are scanned according to a preset minimum supporting degree X, a local path sequence mode is worked out, and Reduce nodes are merged and processed so that an overall candidate sequence mode can be obtained; the original path sequence database is scanned again so that an overall path sequence mode can be obtained; the overall path sequence mode generates a path association rule and the confidence degree of the path association rule is calculated so that a vehicle driving path prediction result can be obtained.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation systems, and in particular relates to a method and system for predicting a vehicle driving path. Background technique [0002] (1) Intelligent Transportation System [0003] With the development and maturity of geolocation technology and the rise of mobile computing, the application based on path and location has become the common focus of academia, industry and even the government. As important attributes of mobile objects, route information and geographic location can provide important support for the improvement of many services and application systems. Taking the path and location information of moving objects as system input has spawned many new application areas. Intelligent transportation system is one of the most famous application fields. The predecessor of the intelligent transportation system is the intelligent vehicle road system. The intelligent transportation s...

AI Technical Summary

Problems solved by technology

[0037] In view of the short distance predicted by the existing route prediction method based on the Markov model, it can only predict the road section that the vehicle will arrive at the next moment. The existing route prediction method based on sequential pattern mining has low computing power in processing massive data and high-dimensional data. efficiency, and aiming at the property 1 of the vehicle travel path sequence, the present invention improves the generation process of the original GSP algorithm candidate sequence pattern, improves the computing performance of the original GSP algorithm, and utilizes the Map-Reduce programming framework to parallelize the improved GSP algorithm Design a sequence database decomposition strategy that meets the requirements of parallel computing to reduce I / O overhead

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