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Fuzzy-based Collision Avoidance System for Autonomous Driving in Complicated Traffic Scenarios

机译:复杂交通场景下基于模糊的自动驾驶防撞系统

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Collision avoidance is an important requirement for safe and autonomous driving in modern transportation system. In this paper, we present a fuzzy based control approach for smart and safe obstacle avoidance in complicated traffic scenario where there are static and dynamic obstacles (e.g. broken-down vehicles, wrong parking road-side vehicles, or moving vehicles, etc.) The fuzzy system makes an optimal decision to control the car throttle, braking, and steering to avoid collision using the available information on the road map (i.e. the distance to obstacles, the current traffic in the neighbouring lanes, the velocity of the front and rear car, etc.). Simulation results from three different scenarios involving a combination of dynamic and static or broken-down vehicles show that the fuzzy controlled car can effectively avoid obstacle or collision in complicated traffic situations.
机译:避免碰撞是现代交通系统中安全自动驾驶的重要要求。在本文中,我们提出了一种基于模糊的控制方法,用于在有静态和动态障碍物(例如抛锚的车辆,错误的路边停车的车辆或行驶的车辆等)的复杂交通情况下,智能,安全地避开障碍物。模糊系统使用路线图上的可用信息(例如,到障碍物的距离,相邻车道中的当前交通,前车和后车的速度)做出最佳决策,以控制汽车的油门,制动和转向以避免碰撞等)。在动态和静态或故障车辆组合的三种不同情况下的仿真结果表明,模糊控制的车辆可以有效避免复杂交通情况下的障碍物或碰撞。

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