This report investigates technical approaches to address privacy concerns associated with two innovative applications enabled by connected vehicle systems, i.e., origin-destination (OD) flow measurement and differentiated congestion pricing. The former is to retrieve the OD information from connected vehicles while the latter charges congestion tolls with respect to travel characteristics of connected vehicles, e.g., origins, destinations or paths that they traverse between their origins and destinations. Since both applications require tracking vehicles, they may violate the anonymity by design principle adopted by connected vehicle systems. For OD flow measurement, a novel measurement scheme is developed to collect aggregate OD flow data without compromising motorists privacy. For differentiated congestion pricing, an incentive program is designed to encourage motorists to voluntarily reveal their private information and create a win-win situation for both motorists and the society.


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    Titel :

    Privacy-Preserving Methods to Retrieve Origin-Destination Information from Connected Vehicles


    Beteiligte:
    M. Zangui (Autor:in) / Y. Zhou (Autor:in) / Y. Yin (Autor:in) / S. Chen (Autor:in)

    Erscheinungsdatum :

    2013


    Format / Umfang :

    51 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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