Self-adaptive auxiliary driving system and method based on pavement environment

Abstract

The invention provides a self-adaptive auxiliary driving system based on a pavement environment. The system comprises: a signal acquisition unit which comprises a TBOX, a temperature sensor and an image acquisition device, wherein the TBOX is used for acquiring a current place and real-time weather of a vehicle, the temperature sensor is used for acquiring real-time temperature, and the image acquisition device is used for acquiring an image of the environment of a vehicle body; a signal processing unit which integrates signals of the TBOX and the temperature sensor, and compares the signals with information acquired by the image acquisition device to obtain the current road condition; a safety evaluation unit which acquires vehicle body parameters from a vehicle CAN bus and evaluates vehicle braking and steering safety according to the current road condition; and a self-adaptive execution unit which automatically adjusts the safe vehicle following distance, the braking time and the steering angle acceleration value in the current state according to the feedback result of the safety evaluation unit, so that the vehicle adapts to the current weather and road surface conditions. According to the system, the current road surface information is accurately obtained, the performance of the ASAD system is adaptively adjusted, and the driving safety is improved.

Description

Technical field [0001] The present invention belongs to the field of Internet of Things, which specifically relates to an adaptive auxiliary driving system and method based on an pavement environment. Background technique [0002] After a hundred years of development, we can learn from the various sensors on the vehicle to understand the vehicle's vehicle suspension type, vehicle weight, vehicle tire information and external real-time temperature; TBOX application, enabling the vehicle to the outside world, thereby obtaining a vehicle position Real-time weather information; ADAS development also makes we can get road information through the camera. [0003] However, the information acquired by various sensors and ECUs is independent, and there is no integration to cooperate with each other, play a greater role. Current ADAS technology, with the camera, such as ACC, AEB, LKA, etc., but is limited to the camera, the ADAS function often occurs, error, etc., and does not depend on th...

AI Technical Summary

Problems solved by technology

[0005] The environmental analysis module of the system is only connected with the weather condition detection module and the image acquisition module, receives the rainfall, outside temperature and visibility information, and judges whether the road the vehicle is driving on is normal road, waterlogged road, icy road or snow-covered road. However, when the system judges based on the collected rainfall and the temperature outside the car, due to the low temperature environment in winter, the difference in humidity between the north and the south will have different effects on the road surface environment in rainy weather, and it cannot be judged accurately only by rainfall and temperature. Whether it is on a water-logged road, icy road or snow-covered road, and if you rely too much on the camera, the ADAS function will often have omissions and errors.

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