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Electronic Road Pricing System for Low Emission Zones to Preserve Driver Privacy

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8825))

Abstract

At present, great cities try to prevent from high levels of pollution and traffic jam by restricting the access of vehicles to centric zones. They are also known as Low-Emission Zones (LEZ). Some of the most important issues of LEZs are the risk of losing privacy of the citizen who drives through the LEZ and a significant error percentage on detection of fraudulent drivers. In this article, an Electronic Road Pricing (ERP) system designed specifically for cities with Low-Emission Zones is proposed. The aim of this system is to detect fraud and to preserve driver privacy. In this case, revocable anonymity makes only fraudulent drivers lose their privacy.

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References

  1. Balasch, J., Rial, A., Troncoso, C., Preneel, B., Verbauwhede, I., Geuens, C.: Pretp: Privacy-preserving electronic toll pricing. In: USENIX Security Symposium, pp. 63–78 (2010)

    Google Scholar 

  2. Bellare, M., Rogaway, P.: Optimal asymmetric encryption. In: De Santis, A. (ed.) EUROCRYPT 1994. LNCS, vol. 950, pp. 92–111. Springer, Heidelberg (1995)

    Chapter  Google Scholar 

  3. BOE: Resolución int/2836/2013, CVE-DOGC-B-14013017-2014. Núm 6541 - 15.1.2014

    Google Scholar 

  4. Chen, X., Lenzini, G., Mauw, S., Pang, J.: A group signature based electronic toll pricing system. In: ARES, pp. 85–93. IEEE Computer Society (2012)

    Google Scholar 

  5. Costabile, F., Allegrini, I.: A new approach to link transport emissions and air quality: An intelligent transport system based on the control of traffic air pollution. Environmental Modelling and Software 23(3), 258–267 (2008)

    Article  Google Scholar 

  6. Day, J., Huang, Y., Knapp, E., Goldberg, I.: Spectre: spot-checked private ecash tolling at roadside. In: WPES, pp. 61–68. ACM (2011)

    Google Scholar 

  7. Garcia, F.D., Verheul, E.R., Jacobs, B.: Cell-based privacy-friendly roadpricing. Computers & Mathematics with Applications 65(5), 774–785 (2013)

    Article  MathSciNet  Google Scholar 

  8. Meiklejohn, S., Mowery, K., Checkoway, S., Shacham, H.: The phantom tollbooth: Privacy-preserving electronic toll collection in the presence of driver collusion. In: USENIX Security Symposium, pp. 32 (2011)

    Google Scholar 

  9. Popa, R.A., Balakrishnan, H., Blumberg, A.J.: Vpriv: Protecting privacy in location-based vehicular services. In: USENIX Security Symposium, pp. 335–350. USENIX Association (2009)

    Google Scholar 

  10. Santos, G.: Urban congestion charging: A comparison between London and Singapore. Transport Reviews 25(5), 511–534 (2005)

    Article  Google Scholar 

  11. Wolff, H.: Keep your clunker in the suburb: Low-emission zones and adoption of green vehicles. The Economic Journal, n/a–n/a (2014), http://dx.doi.org/10.1111/ecoj.12091

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© 2014 Springer International Publishing Switzerland

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Jardí-Cedó, R., Mut-Puigserver, M., Payeras-Capellà, M.M., Castellà-Roca, J., Viejo, A. (2014). Electronic Road Pricing System for Low Emission Zones to Preserve Driver Privacy. In: Torra, V., Narukawa, Y., Endo, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2014. Lecture Notes in Computer Science(), vol 8825. Springer, Cham. https://doi.org/10.1007/978-3-319-12054-6_1

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  • DOI: https://doi.org/10.1007/978-3-319-12054-6_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12053-9

  • Online ISBN: 978-3-319-12054-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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