共享电单车的自动驾驶技术研究

Research on Key Technologies of Autonomous Driving of Shared Electric Bicycles

共享电单车的出现给人们的短距离出行带来了极大便利。但由于使用者交通安全和规范意识不足,导致安全事故、违规停放、管理混乱等诸多问题。通过自动驾驶技术的赋能,可极大地减轻人们的驾驶压力,提高交通安全性,改善共享电单车存取不便的问题。对共享电单车自动驾驶的关键技术展开研究,应用磁场定向控制(FOC)技术,实现车身姿态、速度和方向的高效、精确控制;将传感器通过USB、RS-232等接口与Jetson TX2上位机实现通信连接,为软件和算法提供数据信息;运用视觉和惯性导航融合的同步定位与建图(SLAM)技术,提高系统稳定性和适应能力,实现高精度的自身定位和地图构建;结合图像识别、自动避障和路径规划等自动驾驶算法,开发出一款具有自动驾驶功能的共享电单车。该研究可为电单车的自动驾驶提供研究经验,以期进一步提高共享电单车的安全性、操作与管理便捷性,有助于推动自动驾驶共享电单车的应用普及,为城市的交通拥堵问题找到新的解决途径。

The emergence of shared electric bicycles has brought great convenience to people’s short-distance travel.However,due to the lack of traffic safety and normative awareness of users,there were many problems such as safety accidents,illegal parking,management confusion and so on.Through the empowerment of autonomous driving technology,people’s driving pressure could be greatly reduced,traffic safety could be insured,and the inconvenience of shared bicycle access could be improved.The key technologies of autonomous driving of shared electric bicycles were investigated.The Field Oriented Control(FOC)technology was applied to achieve high efficiency and precise control of the body’s posture,speed and direction.The sensor network implemented the communication connection with the upper computer Jetson TX2 through USB,RS-232 and other interfaces to provide data information for software and algorithms.The Simultaneous Localization and Mapping(SLAM)scheme with visual and inertial navigation enabled the system to have strong stability and adaptability to achieve high-precision self-positioning and map construction.Combined with image recognition,automatic obstacle avoidance and pathplanning algorithm,developed a set of shared electric bicycles with autonomous driving functions.The research could provide research experience for the automatic driving of electric bicycles,in order to further improve the safety,operation and management convenience of shared electric bicycles,which was beneficial to promote the popularization of the application of self-driving shared electric bicycles and find new solutions for urban traffic congestion.