Automobile driving assistance system and control method

Abstract

The invention discloses an automobile driving assistance system and a control method. The automobile driving assistance system comprises an information acquisition module and an information fusion processor, wherein the information acquisition module comprises a front camera, a front radar and an ultrasonic radar; the information fusion processor is electrically connected with the information acquisition module; and the information fusion processor reads the information of the information acquisition module, performs information fusion processing and outputs a vehicle brake control signal, a speed and distance control signal and a driving track control signal. The front camera comprises an image recognition algorithm module, a light source recognition algorithm module and a lane line recognition algorithm module. The front radar comprises a front obstacle detection module and a front medium-long vehicle distance detection module. The ultrasonic radar comprises a surrounding vehicle distance detection module and a front near vehicle distance detection module.

Description

technical field [0001] The invention belongs to the technical field of automobile automatic driving, and in particular relates to an automobile auxiliary driving system and a control method. Background technique [0002] With the continuous expansion of the automobile market, the number of private cars continues to rise. While bringing convenience to people's travel, it also causes urban congestion problems, especially traffic jams have become the normal state of driving in big cities. When congested, the driver needs to pay attention to the situation of the vehicle in front at all times, and frequently performs pedal operations to start and stop the car, which is likely to cause driving fatigue. Due to the long-term congestion, it is easy to cause the driver's impatience, which is easy to cause traffic accidents. [0003] Today's congestion assistance technology mainly relies on GPS signals, vehicle-to-vehicle communication, and vehicle-to-road communication to obtain envi...

AI Technical Summary

Problems solved by technology

A small amount of misalignment can cause scratches

And in areas with limited GPS signals such as tunnels and mountain roads, this function cannot be used

[0008] 2. DSRC network communication can collect the information of surrounding vehicles, but if a certain car is not connected to the network, it becomes an information blind spot and poses a threat to other vehicles in the entire system

Therefore, until the system covers all vehicles, the information it provides is incomplete and unreliable

[0009] 3. Each sensor of the vehicle works independently, resulting in low information utilization, weak adaptability of related functions, and easy to be affected by complex working conditions, bad weather and other factors

GPS accuracy is also improving, but it still cannot meet the needs of high-density car following

At the same time, the information obtained through the vehicle-to-vehicle communication mode is only reliable when all surrounding cars are equipped with this system, and environmental information such as obstacles and pedestrians cannot be obtained

Therefore, the information obtained purely through the Internet of Vehicles is not enough to support the realization of low-speed car following.

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