论文标题
部分可观测时空混沌系统的无模型预测
Autonomous Road Vehicle Emergency Obstacle Avoidance Maneuver Framework at Highway Speeds
论文作者
论文摘要
自动驾驶汽车（ARV）可以使用油门（加速度），制动（减速）和转向（侧向方向的变化）等输入来导航各种类型的道路网络。在大多数ARV驾驶场景中，涉及正常的车辆交通和与脆弱的道路使用者（VRU）相遇，ARV不需要采取反复措施。本文提出了一种新型的紧急障碍避免操作（EOAM）方法，用于以较高速度和较低的道路表面摩擦行驶，涉及时间关键的操纵性测定和控制。拟议的EOAM框架提供了ARV的感应，感知，控制和驱动系统能力作为一个凝聚力系统的使用，以避免避免在公路障碍物上，首先基于性能可行性和乘客舒适性，并设计为在ARV高级系统中良好整合。进行仿真，包括Simulink中的ARV EOAM逻辑和CARSIM中的车辆模型，速度范围为55至165 km/h，在路面上，摩擦范围为1.0至0.1。结果将在整个ARV系统的背景下进行分析并给出，这对未来的工作有影响。
An Autonomous Road Vehicle (ARV) can navigate various types of road networks using inputs such as throttle (acceleration), braking (deceleration), and steering (change of lateral direction). In most ARV driving scenarios that involve normal vehicle traffic and encounters with vulnerable road users (VRUs), ARVs are not required to take evasive action. This paper presents a novel Emergency Obstacle Avoidance Maneuver (EOAM) methodology for ARVs traveling at higher speeds and lower road surface friction, involving time-critical maneuver determination and control. The proposed EOAM Framework offers usage of the ARV's sensing, perception, control, and actuation system abilities as one cohesive system, to accomplish avoidance of an on-road obstacle, based first on performance feasibility and second on passenger comfort, and is designed to be well-integrated within an ARV high-level system. Co-simulation including the ARV EOAM logic in Simulink and a vehicle model in CarSim is conducted with speeds ranging from 55 to 165 km/h and on road surfaces with friction ranging from 1.0 to 0.1. The results are analyzed and given in the context of an entire ARV system, with implications for future work.
