Privacy-Preserving Vehicle Miles Traveled (PPVMT) Tax
Motor fuel taxes form a great part of the total revenue collected for the development and maintenance of surface transportation. Gasoline tax payments are becoming a matter of concern as the share of Battery Vehicles (BVs) increases in the market. Those funds need to be collected in some other way in light of the decreased gasoline sales. In the recent years, a concept of mileage-based tax, called Vehicle Miles Traveled (VMT) tax, has been developed to address this concern. This approach calculates tax by monitoring vehicle road usage through GPS and odometer data. GPS data determines vehicle's region and the rate per mile to be assessed. The number of miles driven is taken from the odometer. Collection of fine-grained GPS data is privacy invasive and has been a strong reason against adoption of VMT tax. Coarsening the location dependent data does not help either. Ensuring secure computation of the data, and validation of GPS signals also of prime concern as the user might tamper with the system to report less miles. We propose Privacy-Preserving Vehicles Miles Traveled (PPVMT) tax based on additive secret-sharing to solve the privacy issues. In our model, the car computes the total miles driven in each (tax jurisdiction) region. The car splits the total miles of each region into random looking numbers which can later be aggregated in a specific manner to determine tax owed by each user and tax share of each region. We also propose `Car-as-a-Smartphone' model which reasons that features available in a car in the near future will be similar to a current smartphone. To detect system tampering and signal spoofing, we propose validation of the untrusted data from GPS and odometer with inertial motion sensors. We implemented a technique to verify the pattern of location coordinates reported by the GPS in the car from the gyroscope data. The technique raises the cost and the skill required to tamper with the system.
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