Autonomous driving is among the most promising of upcoming traffic safety technologies. Prototypes of autonomous vehicles are already being tested on public streets today. However, while current prototypes prove the feasibility of truly driverless cars, edge cases remain which necessitate falling back on human operators. Teleoperated driving is one solution that would allow a human to remotely control a vehicle via mobile radio networks. Removing in-vehicle drivers would thus allow current autonomous technologies to further progress towards becoming genuinely driverless systems. This paper proposes a new model predictive steering control scheme, specifically designed for semi-autonomous, teleoperated road vehicles. The controller is capable of receiving teleoperator steering commands and, in the case of potential collisions, automatically correcting these commands. Collision avoidance is incorporated into the design using potential fields. A term in the cost function facilitates natural maneuvers, and constraints on the maximum potential keep the vehicle at safe distances from obstacles. This paper also proposes the use of high-order ellipses as a method to accurately model rectangular obstacles in tight driving scenarios. Simulation results support the effectiveness of the proposed approach.

中文翻译：

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Stee with Me：一种用于半自动遥控道路车辆的预测性、潜在的基于现场的控制方法

自动驾驶是未来最有前途的交通安全技术之一。今天，自动驾驶汽车的原型已经在公共街道上进行了测试。然而，虽然当前的原型证明了真正无人驾驶汽车的可行性，但仍然存在需要依靠人类操作员的边缘情况。遥控驾驶是一种允许人类通过移动无线电网络远程控制车辆的解决方案。因此，去除车载驱动程序将使当前的自主技术进一步朝着成为真正无人驾驶系统的方向发展。本文提出了一种新的模型预测转向控制方案，专为半自主、遥控的道路车辆而设计。控制器能够接收远程操作员的转向命令，并且在潜在碰撞的情况下，自动更正这些命令。使用势场将碰撞避免纳入设计中。成本函数中的一项有利于自然机动，对最大潜力的限制使车辆与障碍物保持安全距离。本文还提出了使用高阶椭圆作为在紧凑驾驶场景中精确建模矩形障碍物的方法。仿真结果支持所提出方法的有效性。本文还提出了使用高阶椭圆作为在紧凑驾驶场景中精确建模矩形障碍物的方法。仿真结果支持所提出方法的有效性。本文还提出了使用高阶椭圆作为在紧凑驾驶场景中精确建模矩形障碍物的方法。仿真结果支持所提出方法的有效性。