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BDI Model of Connected and Autonomous Vehicles

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Computational Collective Intelligence (ICCCI 2019)

Abstract

It is expected that connected and autonomous vehicles (CAVs) will become a regular mean of transportation by the year 2022. To fully leverage the potential of this new technology it is necessary to equip such cars with efficient algorithms permitting them to drive in a safe and optimal manner. Thereby we aim to design and implement tools for convenient evaluation of strategies for driving and interactions in various settings.

In this paper we present results of the first stage of our bigger research program on a simulation framework of CAVs. A search for balance between complexity and comprehensibility of the solution led us to the field of multiagent systems. Beliefs-Desires-Intentions (BDI) systems offer useful abstractions for activities of a single self-driving car and collective intelligence of such vehicles. Indeed, the BDI framework helps to combine two distinct natures of a self-driving car: its reactiveness and proactiveness. Moreover, modularity of the resulting architectures for an individual CAV and urban traffic induced by these cars makes the design intelligible and flexible. Our prototype verifies feasibility of this concept.

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Acknowledgements

This work was supported by the Polish National Science Centre Grant 2015/19/B/ST6/02589.

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Correspondence to Inga Rüb .

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Rüb, I., Dunin-Kȩplicz, B. (2019). BDI Model of Connected and Autonomous Vehicles. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11684. Springer, Cham. https://doi.org/10.1007/978-3-030-28374-2_16

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  • DOI: https://doi.org/10.1007/978-3-030-28374-2_16

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  • Online ISBN: 978-3-030-28374-2

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