A Concept for Human-Machine Negotiation in Advanced Driving Assistance Systems

Rothfus, Simon; Schmidt, Robert; Flad, Michael; Hohmann, Sören

doi:10.1109/smc.2019.8914282

Cited by 13 publications

(12 citation statements)

References 18 publications

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“…Hence, this disagreement should be resolved without a detrimental effect on performance. Using a negotiation interface, e.g., similar to negotiation theory used to negotiate evasive maneuvers in autonomous car research [44], can potentially enable smooth LOA switches as both agents can negotiate their choice contrary to the current aggressive override. For example, an operator might refuse to hand over control in a middle of a maneuver and similarly the MI control switcher might insist on handing over control in a critical situation.…”

Section: Advancing MI Controlmentioning

confidence: 99%

Mixed-initiative Variable Autonomy for Remotely Operated Mobile Robots

Chiou

Hawes

2021

J. Hum.-Robot Interact.

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This article presents an Expert-guided Mixed-initiative Control Switcher (EMICS) for remotely operated mobile robots. The EMICS enables switching between different levels of autonomy during task execution initiated by either the human operator and/or the EMICS. The EMICS is evaluated in two disaster-response-inspired experiments, one with a simulated robot and test arena, and one with a real robot in a realistic environment. Analyses from the two experiments provide evidence that: (a) Human-Initiative (HI) systems outperform systems with single modes of operation, such as pure teleoperation, in navigation tasks; (b) in the context of the simulated robot experiment, Mixed-initiative (MI) systems provide improved performance in navigation tasks, improved operator performance in cognitive demanding secondary tasks, and improved operator workload compared to HI. Last, our experiment on a physical robot provides empirical evidence that identify two major challenges for MI control: (a) the design of context-aware MI control systems; and (b) the conflict for control between the robot’s MI control system and the operator. Insights regarding these challenges are discussed and ways to tackle them are proposed.

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Section: Advancing MI Controlmentioning

confidence: 99%

Mixed-initiative Variable Autonomy for Remotely Operated Mobile Robots

Chiou

Hawes

2021

J. Hum.-Robot Interact.

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“…Its objective is to model a humanmachine negotiation over a set of decision options O by exchanging offers o t i among participating agents i ∈ {A, H} (Automation & Human) at times t. The core component is a customized basic negotiation model (cf. [3], [20]): Agents interact according to the negotiation protocol, evaluate offers by means of an individual utility function and accept or generate offers via acceptance and bidding strategies. This basic model is enhanced by an identification module 1 and an adaptation concept.…”

Section: A Adaptive Negotiation Model Based Automation Designmentioning

confidence: 99%

“…The parameter ε i is called concession rate. • An asynchronous negotiation protocol [3], allowing the agents to communicate, i. e. exchanging offers, on an event basis which suits human communication behavior. 2) Identification: In order to influence the outcome of the negotiation and enhance the time-based concession of the basic negotiation model, agents may use the information from their cooperation partner's offers to identify his utility function and negotiation behavior in terms of the bidding strategy, and apply this knowledge within their own bidding strategy.…”

Section: Identification Adaptationmentioning

confidence: 99%

Human-Machine Cooperative Decision Making Outperforms Individualism and Autonomy

Rothfuß¹,

Wörner²,

Inga³

et al. 2023

Preprint

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<div>The experiment reported in this paper provides a first experimental evaluation of human-machine cooperation on decision level: It explicitly focuses on the interaction of human and machine in cooperative decision making situations for which a suitable experimental design is introduced. Furthermore, it challenges conventional leader-follower approaches by comparing them to newly proposed automation designs based on cooperative decision making models. These models originate from negotiation theory and game theory and allow for an investigation of cooperative decision making between equal partners. This equality is motivated by similar approaches on the action level of human-machine cooperation. <br></div><div>The experiment’s results indicate an added value of the proposed automation designs in terms of objective cooperative performance as well as human trust in and satisfaction with the cooperation. Hence, the experiment yields the same insight on decision level as already observed on action level: it may be beneficial to design machines as equal cooperation partners and in accordance to models of emancipated human-machine cooperation.</div>

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“…The resulting framework enables the robot's AI and the human operator to negotiate the LOA during operation via an interface of the implemented negotiation model, i. The proposed negotiation module in NEMICS is designed according to a negotiation framework similar to the one that has been proposed for human-machine negotiation in the context of highly automated driving [21], [22]. In the proposed negotiation model, two agents, i. e. the NEMICS (A) and the human operator (H), exchange offers which resemble the decision option, i. e. the different types of LOA which are teleoperation and autonomy.…”

Section: B Negotiation-enabled Mixed-initiative Control Switcher (Nem...mentioning

confidence: 99%

A Negotiation-Theoretic Framework for Control Authority Transfer in Mixed-Initiative Robotic Systems

Rothfuß¹,

Chiou²,

Inga³

et al. 2022

Preprint

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<p>This paper is accepted for the IEEE SMC 2022 conference and addresses the problem of transfer of control authority between a robot’s AI and a remote human operator, when controlling a Mixed-Initiative (MI) robotic system. We propose a negotiation-theoretic method that enables the robot’s AI and the human operator to cooperatively and dynamically determine (i. e. negotiate) the transfer of control authority between these two agents. An experimental study is presented in which a state-of-the-art Expert-guided Mixed-Initiative Control Switcher (EMICS) method is compared with our proposed Negotiation-Enabled Mixed-Initiative Control Switcher (NEMICS) algorithm. Results suggest that the NEMICS framework is able to successfully avoid conflicts for control, which is a fundamental challenge encountered with previous MI control methods. Comparing NEMICS with the EMICS, we provide evidence of improved navigational safety (i. e. fewer collisions). Additionally, our usability study suggests that human operators perceived their interactions with NEMICS as less intrusive than with EMICS.</p> <p><br></p> <p>The accompanying video demonstrates the differences between NEMICS and EMICS.</p>

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A Concept for Human-Machine Negotiation in Advanced Driving Assistance Systems

Cited by 13 publications

References 18 publications

Mixed-initiative Variable Autonomy for Remotely Operated Mobile Robots

Mixed-initiative Variable Autonomy for Remotely Operated Mobile Robots

Human-Machine Cooperative Decision Making Outperforms Individualism and Autonomy

A Negotiation-Theoretic Framework for Control Authority Transfer in Mixed-Initiative Robotic Systems

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