Curve ACC target vehicle identification method based on multi-sensor fusion

Abstract

The invention discloses a curve ACC target vehicle identification method based on multi-sensor fusion, and belongs to the field of aided driving. A vehicle-mounted camera and a millimeter-wave radar are installed on a vehicle according to certain requirements, output information of the vehicle-mounted camera and the millimeter-wave radar is obtained through a CAN bus, and an empty target, an invalid target and an opposite vehicle target output by the radar are removed to obtain an effective tracking target. The vehicle-mounted camera and the millimeter-wave radar are subjected to space synchronization to enable data of the two sensors to be in the same coordinate system, and then time synchronization is carried out to solve the problem that sampling time points of the two sensors are not synchronous. A curve driving area is established according to data of the vehicle-mounted camera, target data output by a radar is matched with the curve driving area, a vehicle in a current lane is determined, and finally a final tracking target of a main vehicle is determined according to the nearest distance principle. According to the invention, the fusion technology of the vehicle-mounted camera and the millimeter-wave radar is utilized, and the curve driving area is established to be matched with the radar data, so that the target tracking vehicle in the curve can be effectively identified.

Description

technical field [0001] The invention relates to an effective target recognition method for ACC vehicles under a curve driving condition, in particular to a method for recognizing a curve ACC target vehicle based on multi-sensor fusion. Background technique [0002] Target recognition and tracking in curves is an important topic in the field of environmental perception, and has an important impact on the development of ADAS (Advanced Driving Assistant System) systems. Taking the ACC (Adaptive Cruise Control) system as an example, the existing method mainly adjusts the speed of the cruise vehicle adaptively based on the millimeter-wave radar information, and maintains a safe distance from the vehicle in front of the lane. However, on a curved road section, there are usually multiple target vehicles in front of the cruiser or the target vehicle exceeds the preset lane range. Accidents caused by abnormal acceleration or deceleration. In addition, considering the characteristic...

AI Technical Summary

Problems solved by technology

However, on a curved road section, there are usually multiple target vehicles in front of the cruiser or the target vehicle exceeds the preset lane range. Accidents caused by abnormal acceleration or deceleration

In addition, considering the characteristics of the radar itself, information on metal objects such as guardrails, buildings, and signboards on both sides of the curve will also be transmitted back by the radar. These objects may generate false alarms for vehicle control and cause traffic accidents. , affecting the normal operation of the expressway

[0003] Most of the existing methods use machine vision recognition technology or millimeter-wave radar data flags (moving, new targets, etc.) to identify the targets in front of the vehicle. For objects on the straight road, there is a high recognition rate, but in the bend At the road, the accuracy rate will be greatly reduced

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