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Article
Affiliation(s)

GEF-2A, The Higher Institute of Management of Tunis, Tunis University, Tunis, Tunisia

ABSTRACT

By coordination and cooperation between multi-agents, this paper proposes the network of intelligent agents which can reduce the search time needed to finding a parking place. Based on multi-agent model, the fined solution is designed to help drivers   in finding a parking space at anytime and anywhere. Three services are offered: the search for a vacant place, directions to a parking space and booking a place for parking. The results of this study generated by the platform MATSim transport simulation, show that our approach optimizes the operation of vehicles in a parking need with the aim of reducing congestion, and improve traffic flow in urban area. A comparison between the first method where the vehicles are random and the second method where vehicles are steered to vacant parking spaces shows that the minimization of time looking for a parking space could improve circulation by reducing the number of cars in the morning of 2% and 0.7% of the evening. In addition, the traffic per hour per day was reduced by approximately 4.17%. 

KEYWORDS

Intelligent parking management, multi-agent system, benefit evaluation, urban transportation.

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References

[1]   D.C., Shoup, “Cruising for parking”. Transport Policy, 2006, 13, 479-486.

[2]   A. Tofani, G. Dipoppa, G., “Report on available infrastructure simulators. Ente per le Nuove Tecnologie, l’Energia e l’Ambiente (ENEA), DIESIS; Design of an Interoperable European federated Simulation network for critical Infrastructures, 23 octobre 2008. Available in http://www.diesis-project.eu/include/Documents/Delivera ble2.3.pdf.

[3]   R. Mraihi, “Transport Intensity and Energy Efficiency: Analysis of Policy Implications of Coupling and Decoupling. In M. Eissa (Ed.), Energy Efficiency - The Innovative Ways for Smart Energy, the Future Towards Modern Utilities. Chapter 13 (pp. 271-288), InTech, 2012.

[4]   G. Marsden, “The evidence base for parking policies-A review”. Transport Policy: Special Issue on Parking, 13(6), 2006, 447–457.

[5]   W. Fan, M. K. Babar “Modeling the parking pricing of multiple parking facilities under different operation regimes”.Journal of Transportation Technologies, 2, 2012, pp. 260-266.

[6]   I. Benenson, K. Martens, S. “PARKAGENT: An agent-based model of parking in the city. Computers, Environment and Urban Systems, 32, 2008, pp. 430-439.

[7]   R. Lu, H. Zhu, “An Intelligent Secure and Privacy-Preserving Parking Scheme Through Vehicular Communications. IEEE Transactions on vehicular, 59, 2010, pp. 2773-2784.

[8]   S.Y. Chou, S.W. Lin, C.C. Li, “Dynamic parking negotiation and guidance using an agent-based platform. Expert Systems with Applications, 35 (3), 2008, pp. 805-817.

[9]   Y.C. Shiue, J. Lin, S.C. Chen, “A Study of Geographic Information System Combining with GPS and 3G for Parking Guidance and Information System. World Academy of Science, Engineering and Technology, 2010, pp. 418-423.

[10]  F. Baumarius, “A multi-agent approach towards modeling urbain trafic scenarios. The Research report RR- 92-47, Deutsches Forschungszentrum fOr KOnstliche Intelligenz GmbH, 1992, pp. 2-16.

[11]  H. Wang, W. He, “A reservation-based smart parking system. In Proc. 5th International Workshop on Cyber-Physical Networking Systems (colocated with IEEE INFOCOM), April 2011.

[12]  M.T. Tsai, C.P. Chu, “Evaluating parking reservation policy in urban areas: An environmental perspective. Transportation Research, Part D, 17, 2012, pp. 145-148.

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