基于STM32的电动自行车智能安全系统设计OA
Design of Intelligent Safety System for Electric Bicycle Based on STM32
随着电动自行车使用率持续攀升,交通事故率与违章行为亦呈上升态势.针对这一现状,以STM32单片机为核心控制单元,集成视觉模块、电池安全监测模块、驾驶人行为监测模块、驾驶状态安全监测模块及警报系统,并搭建手机App实现双向数据交互.系统运用YOLOv10算法,可在200 ms内精准识别驾驶人头盔佩戴情况与精神状态,检测准确率达96%以上;PID算法能根据路况与驾驶状态自动调节车辆速度,使速度控制误差小于±0.5 km/h;采用滤波算法优化传感器数据精度,将数据波动误差降低60%.经实测验证,电池温度控制策略可将电池运行温度波动控制在±2℃以内;PID速度控制算法使能量回收效率提升超30%;YOLOv10算法大幅缩短头盔与面部检测响应时间,检测效率提升约40%.该智能安全系统实现驾驶人状态实时监测、盲区检测预警、自动调速、防碰撞等功能,可及时纠正驾驶人不当行为,经模拟道路测试,电动自行车事故模拟发生率降低58%,为电动自行车安全出行提供可靠技术保障.
As the usage rate of electric bicycles continues to rise,both the incidence of traffic accidents and violations are also trending upwards.In response to this situation,the STM32 microcontroller is used as the core control unit,integrating visual module,battery safety monitoring module,driver behavior monitoring module,driving status safety monitoring module,and alarm system,and a mobile App is built to achieve bidirectional data interaction.The system employs the YOLOv10 algorithm,which can accurately recognize the driver´s helmet wearing condition and mental state within 200 ms,achieving a detection accuracy rate of over 96%;the PID algorithm can automatically adjust the vehicle speed based on road conditions and driving status,ensuring a speed control error of less than±0.5 km/h;a filtering algorithm is used to optimize sensor data accuracy,reducing data fluctuation errors by 60%.Verified by actual testing,the battery temperature control strategy can maintain the battery operating temperature fluctuation within±2℃;the PID speed control algorithm improves energy recovery efficiency by over 30%;the YOLOv10 algorithm significantly shortens the response time for helmet and facial detection,enhancing detection efficiency by about 40%.This intelligent safety system realizes real-time monitoring of the driver´s status,blind spot detection alarms,automatic speed adjustment,and anti-collision functions,which can promptly correct inappropriate driver behavior.Through simulated road testing,the simulated incidence rate of electric bicycle accidents is reduced by 58%,providing reliable technical support for safe travel on electric bicycles.
侯晓丽;黄丽霞;陈锦阳;杨晓彤;张再鹏;严继超
广州华立学院,广州 511300广州华立学院,广州 511300广州华立学院,广州 511300广州华立学院,广州 511300广州华立学院,广州 511300广州华立学院,广州 511300
信息技术与安全科学
YOLOv10 算法PID控制算法单片机头盔检测温度控制
YOLOv10 algorithmPID control algorithmmicrocontrollerhelmet detectiontemperature control
《机电工程技术》 2026 (6)
148-155,8
2023年广东省大学生创新训练项目(S202313656021)
评论