A Probabilistic Approach to Parking - Benefits of Routing Instead of Spotting

Gabor Feher, Balazs Andras Lajtha, Akos Lovasz

2015

Abstract

Urban parking is an important issue in all modern countries. Technological advances, with in-car sensors and always connected smartphones have already paved the way to an ICT solution for this problem. However, every attempt - including that of such a big companies, as Google - has failed to provide a suitable solution. So far, the appeared solutions were centered around the notion of free parking spots. This approach does not take into account the dynamics of the traffic and the drivers outside of the system. Here we propose a fundamentally different approach based on parking probabilities and parking routes. Our solution can truly reduce the time, resource and environmental damage wasted on parking place hunting, while keeping the operational costs low and the users satisfied.

References

  1. Arnott, R., Rave, T., and Schb, R. (2005). Alleviating Urban Traffic Congestion, volume 1 of MIT Press Books. The MIT Press.
  2. Caliskan, M., Barthels, A., Scheuermann, B., and Mauve, M. (2007). Predicting parking lot occupancy in vehicular ad hoc networks. In Vehicular Technology Conference, 2007. VTC2007-Spring. IEEE 65th, page 277281.
  3. Chen, X., Santos-Neto, E., and Ripeanu, M. (2013). Smart parking by the COIN. In Proceedings of the Third ACM International Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications, DIVANet 7813, page 109114, New York, NY, USA. ACM.
  4. Dohler, M., Vilajosana, I., Vilajosana, X., and LLosa, J. (2011). Smart cities: An action plan. In Proceedings of Barcelona Smart Cities Congress.
  5. Goodwin, P. (2012). Peak travel, peak car and the future of mobility.
  6. Kessler, S. (2011). How Smarter Parking Technology Will Reduce Traffic Congestion.
  7. Kincaid, J. (2010). Googles open spot makes parking a breeze, assuming everyone turns into a good samaritan.
  8. Lan, K.-C. and Shih, W.-Y. (2014). An intelligent driver location system for smart parking. Expert Systems with Applications, 41(5):2443-2456.
  9. Lan, K. C. and Wang, H. Y. (2013). On providing incentives to collect road traffic information. In International wireless communications & mobile computing conference (IWCMC13).
  10. Nawaz, S., Efstratiou, C., and Mascolo, C. (2013). ParkSense: a smartphone based sensing system for onstreet parking. In Proceedings of the 19th annual international conference on Mobile computing & networking, page 7586.
  11. Wang, H. and He, W. (2011). A reservation-based smart parking system. In Computer Communications Workshops (INFOCOM WKSHPS), 2011 IEEE Conference on, page 690695.
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Paper Citation


in Harvard Style

Feher G., Andras Lajtha B. and Lovasz A. (2015). A Probabilistic Approach to Parking - Benefits of Routing Instead of Spotting . In Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-105-2, pages 95-100. DOI: 10.5220/0005495400950100


in Bibtex Style

@conference{smartgreens15,
author={Gabor Feher and Balazs Andras Lajtha and Akos Lovasz},
title={A Probabilistic Approach to Parking - Benefits of Routing Instead of Spotting},
booktitle={Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2015},
pages={95-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005495400950100},
isbn={978-989-758-105-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - A Probabilistic Approach to Parking - Benefits of Routing Instead of Spotting
SN - 978-989-758-105-2
AU - Feher G.
AU - Andras Lajtha B.
AU - Lovasz A.
PY - 2015
SP - 95
EP - 100
DO - 10.5220/0005495400950100