Path planning method for avoiding of traffic hotspots

Abstract

A path planning method for avoiding of traffic hotspots helps to realize an intelligent path planning method with a purpose of the shortest journey time, by dynamical planning of paths with an avoiding property, based on a destination where a driving user goes. The traffic hotspot information, such as large-scale activities, traffic accidents, traffic-peak block roads, school time or commuter time of large-scale units, weather information and the like, are mined continually from a plurality of data sources comprising webpages, microblogs, real-time reported traffic information, historical regularity information and the like. By acquisition of the traffic hotspot information in real time, and combination with influences of a road maximum speed limit, road width and traffic light delay at intersections to driving as well as whether a main road containing a non-motor vehicle zone, a rapid navigation route with an avoiding function is planed, and also a dynamic path planning can be carried out in real time base on a current position. The method helps to provide a fastest path to the destination for drivers and alleviate city traffic jam in certain degree.

Description

technical field [0001] The invention relates to a route planning method for avoiding traffic hotspots, and belongs to the research field of navigation route planning technology. Background technique [0002] Today, when the total number of motor vehicles is increasing, road congestion is becoming more and more serious, especially in big cities like Beijing and Shanghai, it has become a very troublesome thing to travel during morning and evening peak hours. , Encountering major traffic accidents or road sections with crowds is even more miserable for drivers and friends. With the development of science, in the face of solving the problem of people's travel difficulties, this method collects traffic hotspot information that may cause traffic congestion during driving, regular historical information in the database, and real-time reported traffic information. Real-time dynamic planning Driving route, aiming at the shortest time-consuming, provides users with an intelligent rou...

AI Technical Summary

Problems solved by technology

With the development of science and technology, intelligent navigation has also been studied by many scholars and a lot of work has been done, but there are still some disadvantages, such as: single planning route, inability to plan routes in real time according to current traffic conditions, small applicable areas, etc.

The main reasons for the above problems are that the geographic data is not comprehensive enough, there is no background database data support, the route planning process cannot interact with the network, traffic hotspot information cannot be obtained, and there is no driving route prediction and dynamic planning of driving routes, etc., seriously affecting travel

For some navigation methods with evasion function currently studied by many experts and scholars, it is also mainly aimed at a specific area, and the road condition data is obtained through investigation of the area and a relatively single data source is used to predict the road condition. The practical range is limited, the data is not comprehensive enough, and it is impossible to capture emergencies and timely respond to the current road condition information to the user, so that the navigation path cannot be avoided in real time for multivariate data

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