01756248

Component

https://doi.org/10.1177/0361198120953162

This paper describes an approach for the development of prediction models for the estimation of mileage-related vehicle depreciation that can be used in the estimation of the benefits derived from transportation network improvements. The approach takes advantage of published online data for vehicle valuations. A new asymmetric logistic prediction model for total vehicle depreciation, including initial and mileage-related depreciations, is proposed and fitted to collected valuations data. The added benefit of this prediction model is that it takes into consideration both vehicle age (i.e., years since manufacture) and vehicle usage (i.e., miles of travel). Six small light-duty vehicles (SLDVs), five large light-duty vehicles (LLDVs), three two-axle trucks, one single-unit truck, and two combination trucks were considered in this study. Vehicle fuel sources included gasoline, diesel, gasoline-ethanol blend of up to 85% ethanol (E85), and hybrid-electric, resulting in 26 combinations of vehicle type and fuel source. Additionally, the developed models were adjusted to account for the effects of average speed of vehicle and roadway characteristics (e.g., grade, curvature) on vehicle depreciation. The practicality of the developed models for large sport utility vehicles (SUVs) and midsize cars was illustrated using select examples highlighting the models’ sensitivity to vehicle average speed and roadway characteristics.

The contents of this paper reflect the views of the authors and do not necessarily reflect the official views and policies of the FHWA. © National Academy of Sciences: Transportation Research Board 2020.

English

pp 395-408

2020-12

Transportation Research Record: Journal of the Transportation Research Board

Web

References (30)

Depreciation; Logits; Mathematical prediction; Roads; Valuation; Vehicle characteristics

Finance; Highways; Vehicles and Equipment

TRIS, TRB, ATRI

Oct 23 2020 3:05PM