Development of an Autonomous Reverse Engineering Capability for Controller Area Network Messages to Support Autonomous Control Retrofits

Kevin Setterstrom, Jeremy Straub
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Abstract

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.
支持自主控制改造的控制器局域网信息自主逆向工程能力的开发
随着自动驾驶汽车行业的不断发展,许多公司都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,每个汽车制造商使用的控制器区域网络(CAN)的实现差异对实现大规模实施改造构成了重大挑战。为了应对这一挑战,本研究提出了一种方法,在不事先了解车辆的情况下,对与车辆加速器和刹车踏板相关的CAN通道进行逆向工程。通过在车辆运行过程中同时记录惯性测量单元(IMU)和CAN数据,该算法可以识别对应于每个控制的CAN通道。在对来自三家制造商的六辆汽车的测试中,所提出的方法被证明可以成功地识别每辆被测试车辆的加速踏板和制动踏板的CAN通道。这些有希望的结果表明,使用这种方法开发售后自动驾驶汽车套件的潜力——可能需要额外的研究来促进实时使用。值得注意的是,尽管车辆CAN标准发生了变化,但所提出的系统仍有可能保持其有效性,并且它可以潜在地适应任何车辆通信介质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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