基于路面颠簸几何的自动驾驶汽车模糊逻辑速度优化

Yassine Zein, M. Darwiche
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引用次数: 2

摘要

在当今科技快速发展的世界,半自动驾驶汽车正在成为一种常见的景象,并且数量正在增加。有些汽车配备了自动驾驶系统,在某些情况下无需驾驶员干预即可驾驶汽车,或者警告驾驶员前方有危险。完全自动驾驶汽车尚未问世,因为老式的道路基础设施会给它带来挑战。从减速带和交通灯到车道和警告标志,目前的自动驾驶系统必须应对所有这些情况。本文讨论了一种在自动驾驶模式下安全通过减速带的系统。高速穿越减速带可能导致失去控制、悬挂失灵、机上货物损坏和/或降低乘客舒适度。该系统可以从远处检测到减速带,通过研究垂直加速度干扰计算出合适的过马路速度,并通过模糊逻辑控制器(FLC)自动刹车,在汽车到达减速带之前降低速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FUZZY LOGIC VELOCITY OPTIMIZATION OF AUTONOMOUS VEHICLES BASED ON ROAD BUMP GEOMETRY
In today’s world of fast developing technologies, semi-autonomous vehicles are becoming a common sight and increasing in numbers. Some feature autopilot systems that drive the vehicle without any intervention from the driver in certain situations or warn the driver of dangers ahead. A fully autonomous vehicle is yet to come due to old fashioned road infrastructures that would convey challenging scenarios for it. From speed bumps and traffic lights to road lanes and warning signs, current autopilot systems will have to cope with all. A system that ensures safe crossing of speed bumps when in autopilot mode is discussed in this paper. Crossing a speed bump at high speeds may result in loss of control, suspension failure, onboard cargo damage, and/or compromised passenger comfort. The proposed system can detect a speed bump from a distance, calculate the suitable crossing speed by studying vertical acceleration disturbances, and apply the brakes automatically using a Fuzzy Logic Controller (FLC) to reduce the speed before the car reaches the speed bump.
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