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机器学习在自动驾驶碰撞算法伦理设计中的应用。

Application of Machine Learning in Ethical Design of Autonomous Driving Crash Algorithms.

机构信息

Advanced Institute of Information Technology, Peking University, Hangzhou 311200, China.

出版信息

Comput Intell Neurosci. 2022 Sep 24;2022:2938011. doi: 10.1155/2022/2938011. eCollection 2022.

DOI:10.1155/2022/2938011
PMID:36248938
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9553442/
Abstract

The age of algorithms is here, and it is really changing people's lives. More and more ethical problems related to algorithms have attracted people's attention, but the related ethical research is still far behind the research of algorithms. As more intelligent algorithms emerge in an endless stream, there will also be a lot of algorithmic ethical issues. On the other hand, with the continuous improvement of the development level of the automobile industry, people have a stronger demand for the safety and stability of modern transportation, and more and more autonomous driving technology has been promoted and applied in the market. At present, most of the studies on the longitudinal collision avoidance system of vehicles use collision warning or emergency braking to avoid collision. However, when the vehicle is in a special situation such as high speed and slippery road, emergency steering is more effective. In order to further improve the vehicle safety and ethical algorithm design points, this article revolves around vehicle lateral active collision avoidance control method research, the collision avoidance decision-making, and path planning and collision avoidance transverse vehicle longitudinal motion control is analyzed, and based on automated driving simulation experiment, the tests carried out to verify the designed control strategy. The experimental results show that the proposed method not only has a good effect of preventing automatic driving collision but also can meet the requirements of algorithm ethics. This research can effectively guide the research of algorithmic ethics in the field of autonomous driving and effectively reduce the occurrence of traffic accidents.

摘要

算法时代已经到来,它正在改变人们的生活。越来越多与算法相关的伦理问题引起了人们的关注,但相关的伦理研究仍然远远落后于算法研究。随着越来越多的智能算法层出不穷,也将出现大量的算法伦理问题。另一方面,随着汽车工业发展水平的不断提高,人们对现代交通的安全性和稳定性有了更强的需求,越来越多的自动驾驶技术在市场上得到推广和应用。目前,车辆纵向避撞系统的研究大多采用碰撞预警或紧急制动来避免碰撞。但是,当车辆处于高速和湿滑路面等特殊情况时,紧急转向更加有效。为了进一步提高车辆安全和道德算法设计要点,本文围绕车辆横向主动避撞控制方法研究,避撞决策、路径规划和避撞横向车辆纵向运动控制进行分析,并基于自动驾驶仿真实验,对设计的控制策略进行了验证。实验结果表明,所提出的方法不仅对自动驾驶碰撞有很好的预防效果,而且可以满足算法道德的要求。本研究可以有效地指导自动驾驶领域的算法伦理研究,有效地减少交通事故的发生。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/614a/9553442/b4247b4cd92d/CIN2022-2938011.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/614a/9553442/e2cef632a691/CIN2022-2938011.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/614a/9553442/df94f9c01d41/CIN2022-2938011.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/614a/9553442/04a7af36fa09/CIN2022-2938011.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/614a/9553442/b4247b4cd92d/CIN2022-2938011.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/614a/9553442/e2cef632a691/CIN2022-2938011.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/614a/9553442/df94f9c01d41/CIN2022-2938011.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/614a/9553442/04a7af36fa09/CIN2022-2938011.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/614a/9553442/b4247b4cd92d/CIN2022-2938011.008.jpg

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