Autonomous vehicles hold promise for increased vehicle and traffic safety, and there are several developments in the field where one example is an avoidance maneuver. There it is dangerous for the vehicle to be in the opposing lane, but it is safe to drive in the original lane again after the obstacle. To capture this basic observation, a lane-deviation penalty (LDP) objective function is devised. Based on this objective function, a formulation is developed utilizing optimal all-wheel braking and steering at the limit of road–tire friction. This method is evaluated for a double lane-change scenario by computing the resulting behavior for several interesting cases, where parameters of the emergency situation such as the initial speed of the vehicle and the size and placement of the obstacle are varied, and it performs well. A comparison with maneuvers obtained by minimum-time and other lateral-penalty objective functions shows that the use of the considered penalty function decreases the time that the vehicle spends in the opposing lane.

无人驾驶汽车有望提高车辆和交通安全性，并且在该领域中有一些发展，其中一个例子就是回避机动。车辆在对面的车道有危险，但是在障碍物之后再次在原车道上行驶是安全的。为了捕获该基本观察，设计了车道偏离罚分（LDP）目标函数。基于该目标函数，开发了一种在道路轮胎摩擦极限时利用最佳全轮制动和转向的解决方案。通过计算几种有趣情况下的行为，评估这种方法在双车道变换情况下的性能，在这种情况下，紧急情况的参数（例如车辆的初始速度以及障碍物的大小和位置）会发生变化，并且效果良好。