将轨迹跟踪指令转化为燃油车可执行的油门刹车指令，实现精准纵向控制。
Longitudinal Control for Autonomous Racing with Combustion Engine Vehicles
- 模块化设计，可适配不同轨迹控制算法与车辆。
- 实测最高纵向加速度达25 m/s²，实现高精度指令追踪。
- 集成防抱死、牵引力控制，保障真实赛道安全运行。
自动驾驶中通常采用路径或轨迹跟踪控制器生成如纵向加速度等高层指令，但内燃机车辆需要不同的执行输入。本文提出一种纵向控制方案，将高层轨迹跟踪指令转换为油门、制动压力和目标档位等底层车辆指令。采用模块化结构，便于集成不同轨迹跟踪算法与车辆平台。所提控制方案能实现对高层指令的精确跟踪。实验中集成防抱死系统（ABS）、牵引力控制系统及制动预热控制，确保真实测试中的安全性。基于阿布扎比自动驾驶赛车联盟首场比赛中EAV24赛车在亚斯码头F1赛道上的实测数据验证了该方法，最大纵向加速度达25 m/s²。
原文摘要 · Abstract (English)
Usually, a controller for path- or trajectory tracking is employed in autonomous driving. Typically, these controllers generate high-level commands like longitudinal acceleration or force. However, vehicles with combustion engines expect different actuation inputs. This paper proposes a longitudinal control concept that translates high-level trajectory-tracking commands to the required low-level vehicle commands such as throttle, brake pressure and a desired gear. We chose a modular structure to easily integrate different trajectory-tracking control algorithms and vehicles. The proposed control concept enables a close tracking of the high-level control command. An anti-lock braking system, traction control, and brake warmup control also ensure a safe operation during real-world tests. We provide experimental validation of our concept using real world data with longitudinal accelerations reaching up to $25 \, \frac{\mathrm{m}}{\mathrm{s}^2}$. The experiments were conducted using the EAV24 racecar during the first event of the Abu Dhabi Autonomous Racing League on the Yas Marina Formula 1 Circuit.
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