Conflicts in Human-Machine Systems as an Intersection of Bio- and Technosphere: Cooperation and Interaction Patterns for Human and Machine Interference and Conflict Resolution

Flemisch, Frank; Pacaux‐Lemoine, Marie‐Pierre; Vanderhaegen, Frédéric; Itoh, Makoto; Saito, Yuichi; Herzberger, Nicolas; Wasser, Joscha; Strugeon, Emmanuelle Grislin-Le; Baltzer, Marcel

doi:10.1109/ichms49158.2020.9209517

Cited by 11 publications

(2 citation statements)

References 23 publications

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“…In systems that need to propose driving strategies that conflict with driver intentions, it may be important to communicate the system’s intentions to drivers ( Mulder et al, 2012 ). Some recent studies have shed light on the analysis of shared control conflicts and proposed conflict resolution frameworks to address this ( Itoh et al, 2016 ; Flemisch et al, 2020 ). However, if the conflict resolution between a human and a system is not successful, the system should consider the decrease in sense of agency and propose a solution to recover the human’s sense of agency.…”

Section: Discussionmentioning

confidence: 99%

Deceleration Assistance Mitigated the Trade-off Between Sense of Agency and Driving Performance

et al. 2021

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Driving assistance technology has gained traction in recent years and is becoming more widely used in vehicles. However, drivers usually experience a reduced sense of agency when driving assistance is active even though automated assistance improves driving performance by reducing human error and ensuring quick reactions. The present study examined whether driving assistance can maintain human sense of agency during early deceleration in the face of collision risk, compared with manual deceleration. In the experimental task, participants decelerate their vehicle in a driving simulator to avoid collision with a vehicle that suddenly cut in front of them and decelerated. In the assisted condition, the system performed deceleration 100 ms after the cut-in. Participants were instructed to decelerate their vehicle and follow the vehicle that cut-in. This design ensured that the deceleration assistance applied a similar control to the vehicle as the drivers intended to, only faster and smoother. Participants rated their sense of agency and their driving performance. The results showed that drivers maintained their sense of agency and improved driving performance under driving assistance. The findings provided insights into designing driving assistance that can maintain drivers’ sense of agency while improving future driving performance. It is important to establish a mode of joint-control in which the system shares the intention of human drivers and provides improved execution of control.

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Section: Discussionmentioning

confidence: 99%

Deceleration Assistance Mitigated the Trade-off Between Sense of Agency and Driving Performance

et al. 2021

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“…Arbitration refers to the division of control between HAs and RAs during human-robot interaction [121]- [124]. One key challenge in formulating cooperative strategies is finding a balance between the control authority of humans and machines.…”

Section: B Arbitrationmentioning

confidence: 99%

A Review of Human–Machine Cooperation in the Robotics Domain

Yang

Zhu

Chen

2022

IEEE Trans. Human-Mach. Syst.

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Artificial intelligence (AI) technology has greatly expanded human capabilities through perception, understanding, action, and learning. The future of AI depends on cooperation between humans and AI. In addition to a fully automated or manually controlled machine, a machine can work in tandem with a human with different levels of assistance and automation. Machines and humans cooperate in different ways. Three strategies for cooperation are described in this article, as well as the nesting relationships among different control methods and cooperation strategies. Based on human thinking and behavior, a hierarchical human-machine cooperation (HMC) framework is improved and extended to design safe, efficient, and attractive systems. We review the common methods of perception, decision-making, and execution in the HMC framework. Future applications and trends of HMC are also discussed.

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