TITLE:
A Promising Distance-Based Gasoline Tax Charging System Based on Spatio-Temporal Grid Reservation in the Era of Zero-Emission Vehicles
AUTHORS:
Babakarkhail Habibullah, Rui Teng, Kenya Sato
KEYWORDS:
Automated Vehicle, Zero-Emission Vehicle, Gasoline Tax, Micro-Road-Pricing, Spatio-Temporal-Grid
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.12 No.4,
September
15,
2022
ABSTRACT: Fuel taxes are still a primary funding source for
the development and maintenance of transportation infrastructure. Such a tax is
collected as a flat fee from the importer or producer of the taxable fuel
product. Fuel-efficiency improvements and the adoption of zero-emission
vehicles result in a continuous decrease in gasoline tax revenues. This paper
proposes a novel distance-based alternative method to replace current
gasoline tax collection systems in Japan by providing a software architecture
platform. In this platform, we utilize driving
information gathered via communication mechanisms installed in connected
automated vehicles to develop a system that collects gasoline tax based on reserving spatio-temporal grids.
Spatio-temporal sections are created by dividing space and time into equal
grids and a designated tax charge is assigned. Connected automated
vehicles reserve a planned travel route in advance and travel based on
reservation information. The performance evaluation results indicate that the proposed system adequately reserves the requested grids and accurately collects gasoline
taxes based on a spatio-temporal grid with minimum communication time
and no data package loss. The proposed method is based on micro travel distance
charges, which generates gasoline tax revenue by 5.7 percent for model year
2022 and 21.8 percent for model year 2030 as compared to the current flat-fee
system.