Human-machine interaction
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2023-01-01
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Elsevier
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Researchers and automakers are working toward more intelligent and robust ADAS to develop fully automated vehicles. However, they have been facing a hard challenge because of the complexity of the scenarios a driver faces every day. In that order, automated cars must assure almost perfect performance because human-caused accidents are socially and legally accepted, but those caused by machines are not. In this context, two main Human-Machine Cooperation (HMC) strategies are being explored to overcome the main challenges of fully autonomous vehicles (AVs) and propose new solutions that can be implemented in the short term to improve safety and efficiency of the driving task. These strategies are shared control and traded control. The first emphasizes the real-time cooperation at the control level between the driver and automation, with a dynamic allocation of control authority. The second looks for a dynamic shift of the human role between the driver and passenger, with a variable level of automation according to the complexity of the driving scenario. The present chapter provides a detailed description of both strategies with recent developments in terms of frameworks and algorithms.
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Publisher Copyright: © 2023 Elsevier Inc. All rights reserved.
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Marcano , M , Villagra , J , Medina-Lee , J , Pérez , J & Diaz , S 2023 , Human-machine interaction . in Decision-Making Techniques for Autonomous Vehicles . Elsevier , pp. 333-351 . https://doi.org/10.1016/B978-0-323-98339-6.00014-2