The full deployment of autonomous driving systems on a worldwide scale requires that the self-driving vehicle be operated in a provably safe manner, i.e., the vehicle must be able to avoid collisions in any possible traffic situation. In this paper, we propose a framework based on Model Predictive Control (MPC) that endows the self-driving vehicle with the necessary safety guarantees. In particular, our framework ensures constraint satisfaction at all times, while tracking the reference trajectory as close as obstacles allow, resulting in a safe and comfortable driving behavior. To discuss the performance and real-time capability of our framework, we provide first an illustrative simulation example, and then we demonstrate the effectiveness of our framework in experiments with a real test vehicle.

翻译：全球范围内自动驾驶系统的全面部署要求自动驾驶车辆以可证明安全的方式运行，即车辆必须能在任何可能的交通场景中避免碰撞。本文提出一种基于模型预测控制（MPC）的框架，赋予自动驾驶车辆必要的安全保障。具体而言，该框架在始终满足约束条件的同时，在障碍物允许的范围内尽可能精确地跟踪参考轨迹，从而实现安全舒适的驾驶行为。为论证本框架的性能与实时性，我们首先给出一个说明性仿真示例，随后通过真实测试车辆的实验验证其有效性。