A road condition analysis and early warning method based on on-board diagnostic system data

Abstract

The invention relates to a road condition analysis and early warning method based on vehicle diagnosis system data. The present invention obtains the driving data of the vehicle by reading the OBD sample data installed on the vehicle, monitors the abnormal behavior, and then uploads it to the cloud data analysis center to analyze and learn the driving behavior of the user by using a variety of deep learning algorithms, and performs multiple times on the sample data Modeling and evaluation to determine the current road congestion and whether it is prone to dangerous behaviors such as sudden braking. After obtaining and analyzing enough data, the system will re-model the user's driving behavior to inform the user of the current road conditions. The present invention cleverly avoids the link of collecting road conditions on the spot. Predicting road conditions instead of spending a lot of money to collect road condition information not only reduces the difficulty of project deployment, but also saves capital consumption. With intelligent analysis and reminder functions, it can avoid bad driving behaviors, avoid congested roads, and warn accident-prone areas.

Description

technical field [0001] The invention belongs to the technical field of Internet of Vehicles security, and relates to a road condition analysis and early warning method based on vehicle diagnostic system data. Background technique [0002] With the rapid development of economy and society, traffic elements such as people, vehicles, and roads have increased sharply, and traffic problems across the country have become the focus. Existing driving behavior prediction technologies simply analyze driving time and driving mileage. They only collect data such as driving speed, driving time, driving mileage, and sudden braking times, and then refer to fixed standards to make judgments. The degree of intelligence is very low. It cannot be intelligently reminded according to different users and different road sections. It only relies on the auxiliary functions of the air conditioner and the window switch system, so it cannot be widely used in various vehicle models and cannot meet the ...

AI Technical Summary

Problems solved by technology

The existing driving behavior prediction technology simply analyzes the driving time and driving mileage, only collects data such as driving speed, driving time, driving mileage, and the number of sudden brakes, and then makes judgments with reference to fixed standards, which is very low in intelligence

It is not possible to provide intelligent reminders according to different users and different road sections

It only relies on the auxiliary functions of the air conditioner and window switch system, so it cannot be widely used in various models and cannot meet the needs of users

Moreover, most of the existing technologies on the market are mechanical safety reminders, and do not have intelligent functions to deal with emergencies, etc.

The degree of intelligence is low. It can only judge the road conditions and evaluate the driving status according to fixed standards. The scope of application is narrow and it cannot respond to the needs of the era for the Internet of Vehicles.

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