汽车ACC毫米波雷达和视觉传感器目标级融合方法研究

自适应巡航控制系统是实现未来智能化汽车辅助驾驶的重要功能之一,以往该系统主要采用毫米波雷达感知周围环境,但是容易出现较多的误识别和漏识别情况。针对现存的问题,文章研究了自适应巡航感知系统,不同于以往单一雷达的方案,本设计采用毫米波雷达和视觉传感器融合的办法改善感知系统的性能。通过搭建电动车传感器数据采集系统,编写CAN通信报文解析程序,分析毫米波雷达和视觉传感器特性等,完成了对雷达和视觉信号的采集及处理,实现了感知系统目标级融合。并在巡航和跟车工况下进行离线仿真,验证了目标级融合方案能够有效地提高感知系统的准确性和合理性。

Research on Target Level Fusion Scheme for Automotive ACC Based on Millimeter-wave Radar and Visual Sensor

The adaptive cruise control system is one of the important functions to realize the intelligent vehicle driving in the future.In the past,the system mainly used millimeter wave radar to sense the surrounding environment,but it is easy to appear more false identification and missing identification.Aiming at the existing problems,the adaptive cruise sensing system is studied in this paper,which is different from the previous single radar scheme.In this design,millimeter wave radar and visual sensor fusion are used to improve the performance of the sensing system.By building the sensor data acquisition system of electric vehicle,writing the CAN communication message analysis program,analyzing the characteristics of millimeter wave radar and visual sensor,the acquisition and processing of radar and visual signal are completed,the target level fusion of the perception system is realized.Under cruise and car-following conditions,the off-line simulation is carried out,which proves that the target level fusion scheme effectively improves the accuracy and rationality of the perception system.