Highway vehicle intelligent deceleration early warning method and system based on vehicle-mounted smart phone and automobile data recorder

Abstract

The invention discloses a highway vehicle intelligent deceleration early warning method and system based on a vehicle-mounted smart phone and an automobile data recorder. The method comprises the following steps: 1, carrying out image recognition through the automobile data recorder to obtain a current road surface state, and transmitting the current road surface state to a mobile phone app module; 2, acquiring information of a vehicle and a front vehicle through a vehicle-mounted sensor, and transmitting the information to an app module; 3, lane recognition: judging whether lateral lane change overtaking exists or not; and 4, the mobile phone app terminal calculates a dynamic attachment coefficient according to a dynamic attachment coefficient fitting formula, judges whether deceleration and voice broadcast reminding are needed or not according to a safe distance model, and reminds a driver to control the vehicle speed in a voice form when a lateral lane-changing overtaking vehicle exists in the front. According to the system, the driving environment is comprehensively evaluated by comprehensively considering the road surface state, the road slope, the vehicle driving state and the like, the accuracy is improved and false alarms are reduced by adopting a lane recognition technology and a dynamic adhesion coefficient algorithm, a set of reliable deceleration early warning system is provided for common vehicles, and the driving safety of the vehicles on the expressway is improved.

Description

technical field [0001] The invention belongs to the field of safe driving of automobiles, and in particular relates to an expressway vehicle deceleration early warning system which can analyze the road surface state and provide early warning during the driving process of the vehicle by using a vehicle-mounted smart phone and a driving recorder. Background technique [0002] With the construction of our country's infrastructure, the total mileage of our country's high-speed roads has reached a new level and is still on the rise. According to research statistics, automobile rear-end collision is one of the main forms of highway traffic accidents, accounting for about 40% of traffic accidents in highways, and the death rate is up to more than half. Through the analysis of many high-speed rear-end collision accidents, the following conclusions are obtained: the driver is prone to lack of concentration due to the small changes in the surrounding environment and vehicle conditions...

AI Technical Summary

Problems solved by technology

However, the currently commercialized driving recorders on the market only have functions such as video recording, recording, and photographing, and have not added the analysis function of road conditions or vehicle conditions ahead.

The published patent CN107204055A proposes an intelligent networked driving recorder. Although this invention solves the problem of early warning of front and rear vehicles, it does not analyze the state of the road surface, and there is no way to monitor the driving process under different road conditions. Security warning

The published patent CN110285825A proposes a voice-assisted driver anti-rear collision system based on a driving recorder. Although there is an analysis and judgment on the state of the road surface, the adhesion coefficient under different road surface states used when calculating the safety distance is constant, and no consideration is given. In addition to the influence of other factors such as speed and slope on the coefficient of adhesion except the state of the road surface; and the car-following warning model proposed by it is too simplified and single, and the safety distance is too large to meet the actual situation of high-speed driving, making the road usage rate low; And because the binocular camera is used for distance measurement, it is greatly affected by the weather and cannot be used in some bad weather

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