A navigation method and navigation system based on big data

Abstract

A navigation method and navigation system based on big data, comprising the following steps: S1, acquiring basic data, the basic data including map data and vehicle trajectory data; S2, adding time tags to the basic data to obtain analysis sample data; S3, based on Analyze sample data to generate preliminary forecast results; S4. Acquire dynamic data, which includes traffic interruption data; S5. Use dynamic data to optimize preliminary forecast results to obtain optimized forecast results; S6. Perform error correction on optimized forecast results to obtain final forecasts Result; S7, obtain the user's current location and destination, and generate multiple alternative routes; S8, evaluate the multiple alternative routes according to the final prediction result in S6; S9, generate a navigation route and transmit it according to the evaluation result to the user. The present invention firstly predicts the traffic condition, and then generates a navigation route based on the prediction result, so that the navigation accuracy is higher and the driving habit of the driver can be complied with.

Description

Technical field [0001] The present invention relates to the field of navigation technology, and in particular, a navigation method and a navigation system based on large data. Background technique [0002] With the rapid development of my country's economy, the car has entered thousands of households, and become an important means of transportation in everyday travel. In turn, the navigation system has also developed rapidly with the increase of car ownership. In the navigation process, the choice of path is a very important part, usually taken into account the distance, time, and whether it is congested. Most of the existing navigation systems have taken into account the factors of traffic congestion, but most of the ways are lag, that is, when traffic congestion, it is prompted to circumvent traffic congestion, and the traffic congestion can be predicted, so the actual effect is limited. Although there are also some ways to predict traffic, most of these methods are based on tr...

AI Technical Summary

Problems solved by technology

Most of the existing navigation systems have considered the factor of traffic congestion, but most of the methods used are lagging, that is, prompting vehicles to detour after traffic congestion occurs, and cannot predict traffic congestion in advance, so the actual effect is limited

Although there are some methods for predicting traffic, most of these methods are based on traffic flow and use complex algorithms such as machine learning algorithms or deep learning algorithms to achieve predictions. These methods generally have the problem of difficult implementation

In addition, most of the navigation methods in the prior art do not consider the similarity between roads. For some drivers who are not very skilled in driving, such as drivers in the internship period, they suddenly switch to completely unfamiliar roads. After that, there will often be situations of going in the wrong lane or slowing down at low speeds, both of which are likely to cause traffic jams and are not conducive to ensuring smooth traffic

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