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Authors: Tobias Meuser ; Martin Wende ; Patrick Lieser ; Björn Richerzhagen and Ralf Steinmetz

Affiliation: Technische Universität Darmstadt, Germany

Keyword(s): Decision-making, Distributed, Quality of Information, Information Lifetime, Information Accuracy.

Related Ontology Subjects/Areas/Topics: Applications and Uses ; Artificial Intelligence ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Health Engineering and Technology Applications ; Knowledge-Based Systems ; Sensor Networks ; Sensor, Mesh and Ad Hoc Communications and Networks ; Symbolic Systems ; Telecommunications ; Vehicular Networks ; Wireless Information Networks and Systems

Abstract: To increase road safety and efficiency, connected vehicles rely on the exchange of information. On each vehicle, a decision-making algorithm processes the received information and determines the actions that are to be taken. State-of-the-art decision approaches focus on static information and ignore the temporal dynamics of the environment, which is characterized by high change rates in a vehicular scenario. Hence, they keep outdated information longer than necessary and miss optimization potential. To address this problem, we propose a quality of information (QoI) weight based on a Hidden Markov Model for each information type, e.g., a road congestion state. Using this weight in the decision process allows us to combine detection accuracy of the sensor and the information lifetime in the decision-making, and, consequently, adapt to environmental changes significantly faster. We evaluate our approach for the scenario of traffic jam detection and avoidance, showing that it re duces the costs of false decisions by up to 25% compared to existing approaches. (More)

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Paper citation in several formats:
Meuser, T. ; Wende, M. ; Lieser, P. ; Richerzhagen, B. and Steinmetz, R. (2018). Adaptive Decision Making based on Temporal Information Dynamics. In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-293-6; ISSN 2184-495X, SciTePress, pages 91-102. DOI: 10.5220/0006687900910102

@conference{vehits18,
author={Tobias Meuser and Martin Wende and Patrick Lieser and Björn Richerzhagen and Ralf Steinmetz},
title={Adaptive Decision Making based on Temporal Information Dynamics},
booktitle={Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2018},
pages={91-102},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006687900910102},
isbn={978-989-758-293-6},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Adaptive Decision Making based on Temporal Information Dynamics
SN - 978-989-758-293-6
IS - 2184-495X
AU - Meuser, T.
AU - Wende, M.
AU - Lieser, P.
AU - Richerzhagen, B.
AU - Steinmetz, R.
PY - 2018
SP - 91
EP - 102
DO - 10.5220/0006687900910102
PB - SciTePress