A New Parking Space Allocation System based on a Distributed Constraint Optimization Approach

Atik Ali, Souhila Arib, Samir Aknine

Abstract

This paper develops and evaluates a new decentralized mechanism for the allocation of parking slots in downtown, using a distributed constraints optimization approach (DCOP). Our mechanism works with the multi- parking/multi-zone model, where vehicles are connected and can exchange information with the distributed allocation system. This mechanism can reach the minimal allocation costs where vehicles are assigned to the parking lots with the best possible aggregated user costs. The cost is calculated based on driver’s aggregated preferences over slots. We empirically evaluated the performance of our approach with randomly generated costs and tested on three different configurations. The evaluation shows the performance of each configuration in terms of runtime and volume of exchanged data.

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Paper Citation


in Harvard Style

Ali A., Arib S. and Aknine S. (2021). A New Parking Space Allocation System based on a Distributed Constraint Optimization Approach.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 196-204. DOI: 10.5220/0010249201960204


in Bibtex Style

@conference{icaart21,
author={Atik Ali and Souhila Arib and Samir Aknine},
title={A New Parking Space Allocation System based on a Distributed Constraint Optimization Approach},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={196-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010249201960204},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - A New Parking Space Allocation System based on a Distributed Constraint Optimization Approach
SN - 978-989-758-484-8
AU - Ali A.
AU - Arib S.
AU - Aknine S.
PY - 2021
SP - 196
EP - 204
DO - 10.5220/0010249201960204