Navigation system and algorithm for solving road congestion through big data and statistics

Abstract

The invention discloses a navigation system and algorithm for solving road congestion through big data and statistics. The navigation system comprises a server side and at least two client sides, and each client side is provided with a driving route recording module and an uploading server module; the server side is provided with a user navigation destination analysis module and a second user navigation destination setting module; the driving route recording module records a walking route of a user in a period of time, searches a recommended route and stores the recommended route in a road driving database, and the uploading server module transmits the recommended route to the customer driving route receiving module at the server side and stores the recommended route in a driving route database of all users; the second user navigation destination setting module obtains a departure place and a destination provided by the client side and sends the departure place and the destination to the user navigation destination analysis module, and the server side searches for corresponding recommended routes in all user driving route databases and sends the recommended routes to the auxiliary navigation module of the client side. According to the invention, recommended routes of experienced drivers are learned, and recommended routes are provided for drivers with unfamiliar road conditions.

Description

technical field [0001] The invention relates to the technical field of navigation, in particular to a navigation system and algorithm for solving road congestion with big data and statistics. Background technique [0002] For users with cars, everyone likes to drive when traveling. There are always a group of people whose starting point and destination are basically the same, but the routes they drive are somewhat different, especially in order to avoid traffic jams and road closures. The route to travel is different, for example, when a section of high-speed road is blocked by heavy fog; or when there are many vehicles commuting to and from get off work in a busy urban area, and there are many traffic lights; some experienced drivers know how to avoid congestion , while some novices or strangers don't know how to avoid congestion, thus wasting a lot of time getting stuck halfway. [0003] Therefore, the defect of the prior art is that the existing navigation algorithms all p...

AI Technical Summary

Problems solved by technology

[0002] For users with cars, everyone likes to drive when traveling. There are always a group of people whose starting point and destination are basically the same, but the routes they drive are somewhat different, especially in order to avoid traffic jams and road closures. The route to travel is different, for example, when a section of high-speed road is blocked by heavy fog; or when there are many vehicles commuting to and from get off work in a busy urban area, and there are many traffic lights; some experienced drivers know how to avoid congestion , while some novices or strangers do not know how to avoid congestion, thus wasting a lot of time stuck in the middle of the road

[0003] Therefore, the defect of the prior art is that the existing navigation algorithms all provide route guidance for the starting point A to the destination point C, and he can not learn the route selected by an experienced driver or a driver who is familiar with the road conditions. Or it is to find a solution to solve the congestion, which leads to some good route solutions to the congestion not reflected in the navigation algorithm

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