汽车辅助驾驶信息检测系统设计与实现
Design and Implementation of Vehicle Auxiliary Driving Information Detection System

随着社会经济的增长与人民生活质量的提高，人均汽车持有量快速上涨，交通事故愈发频繁。分析表明，大多数司机在行车过程中因无法及时且清晰地了解车辆周边情况而导致交通事故是交通事故频发的主要原因。为有效缓解由认为因素造成的交通事故问题，本文设计了一款基于YOLOv5目标检测算法的汽车辅助驾驶信息检测系统。该系统采用Flutter框架、Flask框架、SpringBoot等前后端开发技术，设计实现视频图像分析处理、测距、预警等模块，以实时检测图像中的车辆行人信息，并提供预警机制向用户实时预警预碰撞风险，保障用户的出行安全。同时，系统提供数据分析模块，收集用户的预警信息和出行信息，分析用户出行的风险情况，帮助用户改善行车习惯。
With the growth of social economy and the improvement of people’s quality of life, per capita car ownership has risen rapidly, and traffic accidents have become more frequent. The analysis shows that the main reason for the frequent traffic accidents is that most drivers fail to understand the surroundings of their vehicles in time and clearly. In order to effectively alleviate traffic accidents caused by perceived factors, this paper designed a vehicle auxiliary driving information detection system based on YOLOV5 object detection algorithm. The system adopts front and rear end development technologies such as Flutter framework, Flask framework and SpringBoot to design and implement modules such as video image analysis and processing, ranging and early warning, etc., in order to real-time detect vehicle and pedestrian information in the image, and provide early warning mechanism to real-time warn users of pre-collision risk, so as to ensure users’ travel safety. At the same time, the system provides a data analysis module to collect users’ early warning information and travel information, analyze users’ travel risks, and help users improve their driving habits.