The invention discloses a vehicle perception and danger early warning method and system based on environmental sound analysis, and the system is characterized by comprising a sound collection module, a sound analysis module and a danger early warning module. Sound sensors arranged on the periphery of the vehicle body collect sound information around the vehicle, the sound information is transmitted to the sound analysis module, short-time energy characteristics of the sound information are extracted and compared with MFCC (Mel Frequency Cepstrum Coefficient) characteristics for analysis, and target object attributes (motor vehicles, non-motor vehicles, pedestrians and animals) are judged; the position and the relative motion relation of the sound source relative to the vehicle are judged by analyzing the time difference (TDOA) of sound reaching different position sensors, and the attributes of surrounding traffic composers and the relative position information of the vehicle and the surrounding traffic composers are displayed by a vehicle-mounted display. Whether danger occurs or not is judged according to the relative movement relation between the sensed attribute, position, movement and other information of the surrounding traffic composer and the vehicle, danger early warning is carried out on the driver of the vehicle and other traffic composers under the dangerous condition, and fusion with other types of sensor sensing information can also be carried out so that the environment sensing precision is improved.
本发明公开了一种基于环境声音分析的车辆感知及危险预警方法与系统,其特征在于,该系统包括声音采集模块、声音分析模块和危险预警模块。通过布设在车身四周的声音传感器收集车辆周围的声音信息,将声音信息传递到声音分析模块,提取其短时能量特征与MFCC(梅尔频率倒谱系数)特征进行对比分析,判断目标物属性(机动车、非机动车、行人、动物);通过分析声音到达不同位置传感器的时间差(TDOA),判断声源相对车辆本身的位置及相对运动关系,由车载显示器显示周边交通组成者的属性、自车与周边交通组成者的相对位置信息。根据感知到的周边交通组成者的属性、位置、运动等信息与自车的相对运动关系,判断是否会发生危险,并在危险情况下对自车驾驶员及其他交通组成者进行危险预警,也可与其他类型的传感器感知信息进行融合,提高环境感知精度。
Vehicle perception and danger early warning method and system based on environmental sound analysis
一种基于环境声音分析的车辆感知及危险预警方法与系统
2022-02-18
Patent
Electronic Resource
Chinese
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