Multi-agent Learning for Energy-Aware Placement of Autonomous Vehicles
| Autor: | Frederik Ruehl, Lars Hedrich, Omer Ibrahim Erduran, Mirjam Minor, Ahmad Tarraf, Hans Schroth |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
050210 logistics & transportation
0209 industrial biotechnology 020901 industrial engineering & automation Computer science Distributed computing Multi-agent system 0502 economics and business 05 social sciences Cluster (physics) 02 engineering and technology Energy (signal processing) Field (computer science) Meaning (linguistics) |
| Zdroj: | ICMLA |
| DOI: | 10.1109/icmla.2019.00273 |
| Popis: | Mobility gets an increasing amount of meaning and significance in the modern society. In this paper, we introduce a multi-agent learning application for a multi-agent system in e-mobility. In particular, we propose a geospatial model for free-floating and autonomously driving e-trikes and demonstrate a calculation method of positioning e-trikes on a given area by using different methods of cluster analysis. The solution of the cluster analysis contains cluster centers which represent a positioning for the e-trikes. The solution is then evaluateded by a simulation model with more sophisticated parameters. This research field opens different opportunities of application scenarios, which are discussed in the conclusion. |
| Databáze: | OpenAIRE |
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