We study a novel principle for safe and efficient collision avoidance that adopts a mathematically elegant and general framework abstracting as much as possible from the controlled vehicle's dynamics and of its environment. Vehicle dynamics is characterized by pre-computed functions for accelerating and braking to a given speed. Environment is modeled by a function of time giving the free distance ahead of the controlled vehicle under the assumption that the obstacles are either fixed or are moving in the same direction. The main result is a control policy enforcing the vehicle's speed so as to avoid collision and efficiently use the free distance ahead, provided some initial safety condition holds. The studied principle is applied to the design of two discrete controllers, one synchronous and another asynchronous. We show that both controllers are safe by construction. Furthermore, we show that their efficiency strictly increases for decreasing granularity of discretization. We present implementations of the two controllers, their experimental evaluation in the Carla autonomous driving simulator and investigate various performance issues.

中文翻译：

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自动驾驶汽车安全高效的防撞控制

我们研究了一种安全有效避免碰撞的新原理，该原理采用数学上优雅的通用框架，尽可能多地从受控车辆的动力学及其环境中抽象出来。车辆动力学的特点是预先计算的用于加速和制动到给定速度的函数。在假设障碍物固定或沿同一方向移动的情况下，环境由时间函数建模，给出受控车辆前方的自由距离。主要结果是强制车辆速度的控制策略，以避免碰撞并有效利用前方的自由距离，前提是某些初始安全条件成立。所研究的原理应用于两个离散控制器的设计，一个是同步的，另一个是异步的。我们证明这两个控制器在构造上都是安全的。此外，我们表明它们的效率随着离散化粒度的降低而严格增加。我们介绍了两个控制器的实现，它们在 Carla 自动驾驶模拟器中的实验评估，并研究了各种性能问题。