As the autonomous vehicle industry continues to grow, various companies are exploring the use of aftermarket kits to retrofit existing vehicles with semi-autonomous capabilities. However, differences in implementation of the controller area network (CAN) used by each vehicle manufacturer poses a significant challenge to achieving large-scale implementation of retrofits. To address this challenge, this research proposes a method for reverse engineering the CAN channels associated with a vehicle's accelerator and brake pedals, without any prior knowledge of the vehicle. By simultaneously recording inertial measurement unit (IMU) and CAN data during vehicle operation, the proposed algorithms can identify the CAN channels that correspond to each control. During testing of six vehicles from three manufacturers, the proposed method was shown to successfully identify the CAN channels for the accelerator pedal and brake pedal for each vehicle tested. These promising results demonstrate the potential for using this approach for developing aftermarket autonomous vehicle kits - potentially with additional research to facilitate real-time use. Notably, the proposed system has the potential to maintain its effectiveness despite changes in vehicle CAN standards, and it could potentially be adapted to function with any vehicle communications medium.

中文翻译：

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开发控制器局域网消息自主逆向工程能力以支持自主控制改造

随着自动驾驶汽车行业的不断发展，多家公司正在探索使用售后套件来改造具有半自动驾驶功能的现有车辆。然而，各汽车制造商使用的控制器局域网（CAN）实施方式存在差异，这对实现大规模改造实施提出了重大挑战。为了应对这一挑战，本研究提出了一种对与车辆加速踏板和制动踏板相关的 CAN 通道进行逆向工程的方法，而无需事先了解车辆。通过在车辆运行期间同时记录惯性测量单元（IMU）和CAN数据，所提出的算法可以识别与每个控制相对应的CAN通道。在对三个制造商的六辆汽车进行测试时，所提出的方法被证明可以成功识别每辆测试车辆的加速踏板和制动踏板的 CAN 通道。这些有希望的结果证明了使用这种方法开发售后自动驾驶车辆套件的潜力 - 可能需要进行额外的研究以促进实时使用。值得注意的是，尽管车辆 CAN 标准发生变化，所提出的系统仍有可能保持其有效性，并且它可能适用于任何车辆通信介质。