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Radu Stoican, Angelo Cangelosi, Thomas Weisswange, "MEWA: A Benchmark For Meta-Learning in Collaborative Working Agents", IEEE Symposium Series on Computational Intelligence (SSCI 2023), 2023.

Abstract

Meta-reinforcement learning aims to overcome important limitations in reinforcement learning, like low sample efficiency and poor generalization, by creating agents that adapt to new tasks. The development of intelligent robots would benefit from such agents. Long-standing issues like data collection and generalization to real-world dynamic environments could be mitigated by sample-efficient adaptable algorithms. However, most such algorithms ...



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Sandra Ittner, Dominik Mühlbacher, Mark Vollrath, Thomas Weisswange, "Co-DAS: Developing a Co-Driver Assistance System to Reduce Passenger Discomfort ", Frontiers in Psychology, vol. 14, pp. 17, 2023.

Abstract

The front seat passenger is often neglected when developing support systems for cars. There exist few examples of systems that provide information or interaction possibilities specifically to those passengers. Previous research indicated that the passive role of the passenger can frequently lead to a feeling of discomfort, potentially caused by missing information and missing control with respect to the driving situation. This paper proposes a va...



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Matti Krüger, Vanessa Krüger, Taisuke Mukai, "Evaluation of Interfaces for Augmenting a Driver's Ability to Anticipate Front Risks in Real Traffic", 27th International Technical Conference on the Enhanced Safety of Vehicles (ESV), 2023.

Abstract

Effective alerts are often subject to a tradeoff between relevance and utility. While it is easier to acknowledge the relevance of a warning about an imminent hazard than a more distant threat, the possibilities to act appropriately in response to notifications decrease with threat distance. To benefit from the advantages of early notifications without creating annoyance and ignorance, we introduce a variety of Human-Machine Interfaces that pr...



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Takahiro Matsuoka, Tsuyoshi Nojiri, Vanessa Krüger, Matti Krüger, "Novel interfaces that enhance a driver’s ability to perceive forward collision risks", 27th International Technical Conference on the Enhanced Safety of Vehicles (ESV), 2023.

Abstract

Forward Collision Warning (FCW) systems that alert a driver about the risk of rear-end collisions can contribute to a reduction of traffic accidents caused by human errors. Typically, FCWs create alerts that appear late when the risk is already high and are of binary nature, i.e., either in an alerting state during high risk or not producing any alert at lower risks. The choice at what risk level to start alerting in a binary manner is subject to...



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Andreas Neofytou, Jaeyub Hyun, Mariusz Bujny, Thiago Rios, Stefan Menzel, Hyunsun Kim, "A Modularized Level Set Topology Optimization Methodology For Vibro-acoustic Problems", AIAA SciTech Forum, 2023.

Abstract

A modularized level set topology optimization methodology is used to solve vibro-acoustic topology optimization problems. The main objective is to minimize the sound pressure generated by vibrating structures at predefined locations within specified frequency ranges in an interior domain. The plug-and-play style architecture provides freedom to choose from a variety of software for the solution of the governing equations. Taking advantage of this...



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Thomas Jatschka, Tobias Rodemann, Guenther Raidl, "A Multilevel Optimization Approach for Large Scale Battery Exchange Station Location Planning", EvoCOP 2023, 2023.

Abstract

We propose a multilevel optimization algorithm (MLO) for solving large scale instances of the Multi-Period Battery Swapping Station Location Problem (MBSSLP), i.e., a problem for deciding the placement of battery swapping stations in an urban area. MLO generates a solution to an MBSSLP instance in three steps. First the problem size is iteratively reduced in a coarsening phase. Afterwards, a solution to the coarsest problem is obtained and the ob...



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Steffen Limmer, "Empirical Study of Stability and Fairness of Schemes for Benefit Distribution in Local Energy Communities", Energies, vol. 16, no. 4, 2023.

Abstract

The concept of local energy communities is receiving increasing attention. However, the question of how to distribute the benefit of a community among its members is still open. It is commonly desired that the benefit distribution is fair and stable. While benefit distribution schemes such as the nucleolus, Shapley value and Shapley-core are known to perform well in terms of fairness and stability, studies have shown that none of them can guarant...



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Patricia Wollstadt, Christiane Wiebel, Thomas Franke, "Who’s in charge of charging? Investigating Human-Machine-Cooperation in Smart Charging of Electric Vehicles ", International Conference on Human-Computer Interaction, HCII 2023: HCI in Mobility, Transport, and Automotive Systems, vol. 14048, pp. 131-143, 2023.

Abstract

We investigated the effect of varying the level of cooperation in a smart charging agent (SCA) on user perception and behavior. Our study involved manipulating the SCA’s cooperativeness by varying its degree of automation and the amount of information sharing with the user and measuring effects on changes in user behavior, perceived goal alignment, the user’s awareness of the SCA’s information processing, and perceived cooperativeness. Our ...



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Zahra Foroozandeh, Steffen Limmer, Fernando Lezama, Ricardo Faia, Sergio Ramos, Joao Soares, "A MBNLP Method for Centralized Energy Pricing and Scheduling in Local Energy Community", IEEE PES Generation, Transmission and Distribution Conference & Exposition 2022 – Latin America (IEEE GTD 2022), 2023.

Abstract

This paper proposes a new optimization model for pricing and demand scheduling in a grid-connected local energy community (LEC), including residential homes (consumers and prosumers), and combined heat and power (CHP) generation units. It is assumed that some homes have photovoltaic (PV) generation, electric vehicles (EVs), or both. A central entity is responsible for managing the EVs' charging and discharging process, and for scheduling energy e...



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Chao Wang, Anna Belardinelli, Daniel Tanneberg, Stephan Hasler, Theodoros Stouraitis, Michael Gienger, "Enhancing Incremental-learning process of Robotic with Augmented Reality", CHI 2023, 2023.

Abstract

This interactivity proposal plans to show how the augmented reality (AR) technology can enhance the user experience in teaching and interacting with the robots in the home environment via 3 examples: 1. A demonstration of teaching the robot to utilize some appliance via AR glass. 2. A demonstration that the robot use learned knowledge to accomplish certain task. 3. A demonstration of robotics display its intention and ergonomic consideration via...



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