Customized path recommending method in Internet of Vehicles environment

Abstract

The invention discloses a customized path recommending method in an Internet of Vehicles environment. According to the method, in customized path recommending processes, a set of four trip factors including time factors, fee factors, convenience factors and distance factors are taken into account; in a traffic network, a stack idea-based backtracking algorithm for solving a set of all feasible paths from a starting point to an end point is adopted, and a Pearson correlation coefficient-based path recommending algorithm which is implemented according to traveler personality preference characteristic vectors and feasible path characteristic vectors is adopted. According to the method, a plurality kinds of accurate real-time traffic information provided by the Internet of Vehicles is fully used, customized trip demand of a traveler is taken into account, path recommending service in line with individual preference demand can be provided for the traveler, an individual trip path can be customized, accident traffic conditions can be responded to in real time, and customized path recommending service can be provided when traffic accidents occur.

Description

technical field [0001] The invention belongs to the technical fields of transportation and information science, and relates to a method for recommending a personalized route under the environment of the Internet of Vehicles. Background technique [0002] As an indispensable activity in people's daily life, modern transportation based on information technology and communication technology has been widely concerned. The Internet of Vehicles is a concentrated expression of the application of the Internet of Things to the intelligent transportation system. With the continuous promotion and popularization of the Internet of Vehicles technology, the collection, transmission and storage of road network traffic information are also more efficient and convenient, and a large amount of traffic information related to travel has poured into the travel viewer's vision. However, in the face of such complicated traffic information, how to extract information that meets one's individual pr...

AI Technical Summary

Problems solved by technology

That is to say, the path in the road network is a dynamic multi-attribute entity whose attributes change with time; subject to the limitations of traditional traffic information collection, transmission, storage, calculation and other technologies, the existing path planning system does not consider real-time dynamic Changing route traffic information

[0007] (2) The quantitative impact of adverse weather factors (such as fog, rain, snow, haze, etc.) on path status and individual travelers is not considered, and the impact of road construction, large-scale events and other events on traffic travel is also insufficiently considered

However, the existing path planning technology does not quantify the actual impact of these factors on road capacity.

[0008] (3) Does not consider the individual preference differences among different travel individuals

At the same time, it must also be recognized that the degree of preference of individual travelers is a subjective, fuzzy and difficult to quantify factor

In this way, the traditional route planning technology cannot realize the quantitative collection and analysis of the preference factors of individual travelers

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