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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References
Charlcar: prototype implementation. https://www.mimuw.edu.pl/~inga/charlcar.tgz
Al-Zinati, M., Zalila-Wenkstern, R.: Matisse 2.0: a large-scale multi-agent simulation system for agent-based its. In: 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), vol. 2, pp. 328–335 (2015)
Behere, S., Torngren, M.: A functional architecture for autonomous driving. In: 2015 First International Workshop on Automotive Software Architecture (WASA), pp. 3–10 (2015)
Brooks, R.: A robust layered control system for a mobile robot. IEEE J. Robot. Autom. 2, 14–23 (1986)
de Campos, G.R., Falcone, P., Sjöberg, J.: Autonomous cooperative driving: a velocity-based negotiation approach for intersection crossing. In: ITSC 2013, pp. 1456–1461 (2013)
Davila, A., Nombela, M.: Platooning - safe and eco-friendly mobility (2012)
Dunin-Kȩplicz, B., Verbrugge, R.: Teamwork in Multi-Agent Systems: A Formal Approach. Wiley (2010)
Pollack, M.E., Israel, D., Bratman, M.: Towards an architecture for resource-bounded agents (1987)
Fagnant, D.J., Kockelman, K.: Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transp. Res. Part A: Policy Pract. 77, 167–181 (2015)
Ferguson, I.A.: Touring machines: autonomous agents with attitudes. Computer 25(5), 51–55 (1992)
Georgeff, M.P., Ingrand, F.F.: Decision-making in an embedded reasoning system. In: Proceedings of the 11th International Joint Conference on Artificial Intelligence, IJCAI 1889, vol. 2, pp. 972–978 (1989)
Gora, P., Rüb, I.: Traffic models for self-driving connected cars. Transp. Res. Proc. 14, 2207–2216 (2016)
Gruel, W., Stanford, J.M.: Assessing the long-term effects of autonomous vehicles: a speculative approach. Transp. Res. Proc. 13, 18–29 (2016)
Guériau, M., Billot, R., El Faouzi, N.E., Hassas, S., Armetta, F.: Multi-agent dynamic coupling for cooperative vehicles modeling. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, AAAI 2015, pp. 4276–4277. AAAI Press (2015)
Jin, Q., Wu, G., Boriboonsomsin, K., Barth, M.: Multi-agent intersection management for connected vehicles using an optimal scheduling approach. In: 2012 International Conference on Connected Vehicles and Expo (ICCVE), pp. 185–190 (2012)
Johansson, R., et al.: Functional safety and evolvable architectures for autonomy. In: Watzenig, D., Horn, M. (eds.) Automated Driving, pp. 547–560. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-31895-0_25
Dennis, L., Fisher, M., Lincoln, N.K., Veres, S.M., Lisitsa, A.: An agent based framework for adaptive control and decision making of autonomous vehicles. IFAC Proc. Vol. 43(10), 310–317 (2010). https://doi.org/10.3182/20100826-3-TR-4015.00058. http://www.sciencedirect.com/science/article/pii/S1474667015323843
Kamali, M., Dennis, L.A., McAree, O., Fisher, M., Veres, S.M.: Formal verification of autonomous vehicle platooning. Sci. Comput. Program. 148, 88–106 (2017)
Krajzewicz, D.: Traffic simulation with SUMO - simulation of urban mobility. In: Barceló, J. (ed.) Fundamentals of Traffic Simulation, vol. 145, pp. 269–293. Springer, New York (2010). https://doi.org/10.1007/978-1-4419-6142-6_7
Lambert, F.: BMW will launch the electric and autonomous iNext in 2021 (2016). https://electrek.co/2016/05/12/bmw-electric-autonomous-inext-2021/
Leary, K.: Japan is testing driverless buses to help the elderly get around (2017). https://futurism.com/japan-is-testing-driverless-buses-to-help-the-elderly-get-around/
Ling, Y., Mullen, T., Lin, X.: Analysis of optimal thread pool size. SIGOPS Oper. Syst. Rev. 34(2), 42–55 (2000)
Lygeros, J., Godbole, D.N., Sastry, S.: A design framework for hierarchical, hybrid control. Technical report, Machines and Robotic Laboratory, University of California, Berkeley (1997)
Maleš, L., Ribarić, S.: A model of extended BDI agent with autonomous entities (integrating autonomous entities within BDI agent). In: 2016 IEEE 8th International Conference on Intelligent Systems (IS), pp. 205–214 (2016)
Müller, J., Pischel, M.: The agent architecture inteRRaP: concept and application (1993)
Passos, L., Rossetti, R., Kokkinogenis, Z.: Towards the next-generation traffic simulation tools: a first appraisal, pp. 1–6 (2011)
Sage, A., Lienert, P.: GM executive credits silicon valley for accelerating development of self-driving cars (2016). http://www.reuters.com/article/us-ford-autonomous/ford-plans-self-driving-car-for-ride-share-fleets-in-2021-idUSKCN10R1G1
Thangarajah, J., Harland, J., Morley, D.N., Yorke-Smith, N.: On the life-cycle of BDI agent goals. In: Proceedings of the 19th European Conference on Artificial Intelligence, ECAI 2010, Lisbon, Portugal, 16–20 August 2010, pp. 1031–1032 (2010)
Wooldridge, M.: An Introduction to MultiAgent Systems, 2nd edn. Wiley, Hoboken (2009)
Zhang, R., Rossi, F., Pavone, M.: Routing autonomous vehicles in congested transportation networks: structural properties and coordination algorithms (2016)
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This work was supported by the Polish National Science Centre Grant 2015/19/B/ST6/02589.
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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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