Regional risk prompting method and system based on precise positioning and path prediction

Abstract

The invention relates to a regional risk prompting method and system based on precise positioning and path prediction, and relates to the field of intelligent traffic. The method comprises the following steps: acquiring map data and electronic fence information of a first area, wherein the map data comprises lane information; obtaining positioning information and state information of a first vehicle, wherein the positioning information and the state information are used for constructing an input feature vector; executing lane matching according to the positioning information and the lane information, and determining a first lane of the first vehicle; generating an LSTM model through training, verification and testing based on the input feature vector, and outputting a predicted path of the first vehicle; and performing traversal matching on the predicted path and the electronic fence information, and displaying matched first information. According to the regional risk prompting method and system based on precise positioning and path prediction, retrieval matching of the risk region determined by the temporary fence is automatically completed by a program according to the high-precision positioning and path prediction result of the position of the vehicle, and a driver can be automatically notified, so that the timeliness and effectiveness of information transmission are improved.

Description

technical field [0001] This application relates to the field of intelligent transportation, in particular to a regional risk warning method and system based on precise positioning and path prediction. Background technique [0002] Since the epidemic, it has often been necessary to delineate some temporary irregular risk area electronic fences, which puts forward high requirements for the control of geographical areas. However, the locations of the above-mentioned areas are all temporary, and their attributes (risk level, etc.) will change at any time, which will cause certain troubles for personal travel and driving travel. The existing risk area information is generally obtained by drivers independently selecting some traffic information announcement systems, or paying attention to the travel areas they are interested in in some travel reminder apps. Relevant and up-to-date temporary risk area geo-fence information. [0003] Existing technologies require drivers to freque...

AI Technical Summary

Problems solved by technology

[0003] Existing technologies require drivers to frequently and actively browse information, most of the information is irrelevant to the driver, and the proportion of information that is really valuable to the driver's travel is very small

In addition, when the real valid information appears, the driver is likely to miss the information and end up in the risk area by not checking it in the first place

At the same time, the existing technology does not predict the driving route, and the relevance of the information is completely judged by the driver based on the travel route.

The above-mentioned method of manual judgment can only be used in scenarios with a small amount of information (such as dozens of pieces of information). When the amount of information is large (hundreds or even thousands of pieces of information), it is not feasible to use manual judgment

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