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首页> 外文期刊>IFAC PapersOnLine >Are “Hard Sciences” Enough for Teaching Applied Control Design? Driving Assistance and Autonomy in Vehicles as a Case Study.
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Are “Hard Sciences” Enough for Teaching Applied Control Design? Driving Assistance and Autonomy in Vehicles as a Case Study.

机译：“硬科学”足以教授应用控制设计吗？案例研究：车辆的驾驶辅助和自动驾驶。

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摘要

This note aims to discuss the increasing importance of introducing to students in applied control, domains other those directly needed for controlling the underlined studied systems. Indeed, the numeric revolution the last decades had as consequence an increasingly possible closer interaction between controlled systems and humans. This increasing “proximity” between system(s) and human(s) generate the need to better consider the interactions between both and the possible (nice or disastrous) consequences resulting from this close interaction, and how to adjust then, if possible, the parameters, in order to maximize the positive interactions effects. This paper highlights some key issues involved in the advanced driving assistance systems (ADAS) and autonomous vehicles design, used as a case study for giving the reader some elements to the question stated in the title. Note that the goal of this paper is not to address control design for ADAS or autonomous vehicles from an educational point of view. It is aimed here instead, to discuss what else more than “hard sciences” (control, computer sciences, artificial intelligence, etc.) would a control engineer need to be aware of in order to be able to push advances in his field, in coherence with humans needs, and to also be aware of ethical issues related to his/her work. This knowledge could also help him have a good communication with experts in other domains.
机译：本说明旨在讨论向学生介绍应用控制，控制带下划线的学习系统直接需要的其他领域的重要性。确实，过去几十年的数字革命导致受控系统与人类之间越来越可能的更紧密的交互。系统与人之间日益增加的“接近性”导致需要更好地考虑两者之间的相互作用以及这种紧密相互作用所导致的可能（好的或灾难性的）后果，以及如何调整（如果可能）参数，以最大化积极的互动效果。本文重点介绍了高级驾驶辅助系统（ADAS）和自动驾驶汽车设计中涉及的一些关键问题，以此为案例研究为读者提供了标题中所述问题的一些要素。请注意，本文的目的不是从教育的角度解决ADAS或自动驾驶汽车的控制设计问题。相反，这里的目的是讨论控制工程师需要了解的除了“硬科学”（控制，计算机科学，人工智能等）以外的其他东西，以便能够在其领域内取得进步。与人的需求保持一致，并了解与他/她的工作有关的道德问题。这些知识还可以帮助他与其他领域的专家进行良好的交流。

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