Skip to main content

Advertisement

SpringerLink
Log in

A Hybrid Heuristic for Solving a Parking Slot Assignment Problem for Groups of Drivers

  • Published:
International Journal of Intelligent Transportation Systems Research Aims and scope Submit manuscript

Abstract

Smart cities are attracting attention today as life in urban areas is becoming a growing challenge. Among many other problems, finding a free parking space is probably one of the major inconveniences for the citizens of a big city, especially in the city center and other crowded areas. The search for a parking place is a task which can consume a lot of time and affect the efficiency of economic activities, social interactions, and the health of citizens. The planners of transport and city traffic must pay close attention to this issue in order to achieve an efficient management of mobility in smart cities. The work presented here is intended to serve as an aid in the search for parking, seeking the general interest of a group of drivers. We present a comprehensive description of the problem and apply it to four particular cases with increasing levels of difficulty. Also, we propose a hybrid genetic algorithm for solving these cases and we compare it with other four algorithms in order to evaluate its performance. Experimental results driven on a simulation tests based to a real case study, show that the hybrid genetic algorithm generates promising solutions compared to state of the art algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Abidi, S., Krichen, S., Alba, E., Molina, J.M.: A new heuristic for solving the parking assignment problem. In: 19th International Conference on Knowledge Based and Intelligent Information and Engineering Systems. KES 2015 (2015)

  2. Arnott, R., Rave, T., Schb, R.: Alleviating Urban Traffic Congestion. MIT Press (2005)

  3. Benenson, I., Martens, K., Birfir, S.: PARKAGENT: an agent-based model of parking in the city. Comput. Environ. Urban Syst. 32(6), 431439 (2008)

    Article  Google Scholar 

  4. Caliskan, M., Barthels, A., Scheuermann, B., Mauve, M.: Predicting Parking Lot Occupancy in Vehicular Ad Hoc Networks. In: IEEE 65th Conference on Vehicular Technology, 2007 (2007)

  5. Geng, Y., Cassandras, C.G.: A new Smart Parking system infrastructure and implementation. Procedia Soc. Behav. Sci. 54, 12781287 (2012)

    Article  Google Scholar 

  6. Giuffrè, T., Siniscalchi, S.M., Tesoriere, G.: A novel architecture of parking management for smart cities. Procedia-Soc. Behav. Sci. 53, 16–28 (2012)

    Article  Google Scholar 

  7. Hanif, N.H.H.M., Badiozaman, M.H., Daud, H.: Smart parking reservation system using SMS. In: 2010 ICIAS (2010)

  8. IBM ILOG CPLEX 12.2 User’s Manual, IBM ILOG, Inc. (2015). http://www-03.ibm.com/software/products/en/ibmilogcpleoptistud/

  9. Frank, L.D., et al.: An Assessment of Urban Form and Pedestrian and Transit Improvements as an Integrated GHG Reduction Strategy, Washington State Department of Transportation (2011)

  10. Leephakpreeda, T.: Car-parking guidance with fuzzy knowledge-based decision making. Build. Environ. 42 (2), 803809 (2007)

    Article  Google Scholar 

  11. Mei, Z., Xiang, Y., Chen, J., Wang, W.: Optimizing model of curb parking pricing based on parking choice behavior. J. Transport. Syst. Eng. Inf. Technol. 10, 99104 (2010)

    Google Scholar 

  12. Reeves, C.R.: Genetic algorithms and neighborhood search, in Evolutionar Computing: AISB Workshop, Selected Papers, no. 865 in Lecture Notes in Computer Science. T. C. Forgarty, Leeds (1995)

    Google Scholar 

  13. Resende, M.G.C., Ribeiro, C.C.: Greedy randomized adaptive search procedures. In: Glover, F., Kochenberger, G.A. (eds.) Handbooks of Metaheuristics, Kluwer Academic Publishers Dordrecht, p 219249 (2003)

  14. Moini, N., Hill, D., Shabihkhani, R.: Impact assessments of on-street parking guidance system on mobility and environment. In: Transportation Research Board 92nd Annual Meeting. Transportation Research Board (2013)

  15. Olivera, A.C., Garca-Nieto, J.M., Alba, E.: Reducing vehicle emissions and fuel consumption in the city by using particle swarm optimization. Appl Intell 42(3), 389–405 (2015)

    Article  Google Scholar 

  16. Polak, J.W., Hilton, I.C., Axhausen, K.W., Young, W.: Parking guidance and information systems: performance and capability. Traffic Engineering and Control 31(10), 519–524 (1990)

    Google Scholar 

  17. Shi, A., Bo, H., Jian, W.: Study of the mode of real-time and dynamic parking guidance and information systems based on fuzzy clustering analysis. Machine Learning and Cybernetics (2004)

  18. Soup, D.: Cruising for parking. Access 30, 16–22 (2007)

    Google Scholar 

  19. Song, J., Wen, Z.: Study on urban parking guidance information system design. In: ICMV (2011)

  20. Teodorović, D., Luĉić, P.: Intelligent parking systems. Eur. J. Oper. Res. 175(3), 16661681 (2006)

    MATH  Google Scholar 

  21. Toroslu, I.H.: Personnel assignment problem with hierarchical ordering constraints. Comput Ind Eng 45, 493510 (2003)

    Article  Google Scholar 

  22. Waterson, B.J., Hounsell, N.B., Chatterjee, K.: Quantifying the potential savings in travel time resulting from parking guidance systems. J. Oper. Res. Soc. 52(10), 10671077 (2001)

    Article  MATH  Google Scholar 

Download references

Acknowledgments

This research has been partially funded by project number 8.06/5.47.4-142 in collaboration with the VSB-Technical University of Ostrava and Universidad de Málaga UMA/FEDER FC14-TIC36, programa de fortalecimiento de las capacidades de I+D+i en las universidades 2014-2015, de la Consejería e Economía, Innovación, Ciencia y Empleo, cofinanciado por el fondo europeo de desarrollo regional (FEDER). Also, partially funded by the Spanish MINECO project TIN2014-57341-R (http://moveon.lcc.uma.es). This support is gratefully acknowledged.

Author information

Authors and Affiliations

  1. ISG University of Tunis, Le Bardo, Tunisia

    Sofiene Abidi & Saoussen Krichen

  2. Universidad de Málaga, Málaga, Spain

    Enrique Alba & Juan Miguel Molina Bravo

Authors
  1. Sofiene Abidi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Saoussen Krichen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Enrique Alba
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Juan Miguel Molina Bravo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sofiene Abidi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abidi, S., Krichen, S., Alba, E. et al. A Hybrid Heuristic for Solving a Parking Slot Assignment Problem for Groups of Drivers. Int. J. ITS Res. 15, 85–97 (2017). https://doi.org/10.1007/s13177-016-0123-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13177-016-0123-1

Keywords

Search

Navigation