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AI-driven multi-agent vehicular planning for battery efficiency and QoS in 6G smart cities

Lookup NU author(s): Rohin Gillgallon, Dr Giacomo BergamiORCiD, Reham Almutairi, Professor Graham MorganORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

We present Priority-Ordered Timed Multi-Objective A* (POTMO-A*), a multi-agent mobility algorithm contextualised in 6G Smart City scenarios: through multi-objective vehicle planning, not only the distance or time taken to traverse a given route is considered, but also the expected energy consumption and the volume of communicating vehicles at each graph node. Our results demonstrate that our proposed algorithm outperforms traditional shortest path algorithms, while addressing time complexity limitations by considering a heuristic in prioritising the different objectives. The additional inclusion of desirability areas further enabled our algorithm to route more ambulances to their target destinations with the best network QoS, while utilising less energy to do so, compared to traditional and weighted algorithms without desirability considerations.


Publication metadata

Author(s): Gillgallion R, Bergami G, Almutairi R, Morgan G

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 17th International Conference on Management of Digital Ecosystems

Year of Conference: 2025

Online publication date: 26/11/2025

Acceptance date: 26/09/2025

Date deposited: 01/10/2025

Publisher: Springer VG

URL: https://conferences.sigappfr.org/medes2025/

ePrints DOI: 10.57711/bh1q-m765

Notes: Will be published here: https://link.springer.com/conference/medes


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