Near- (2020) and long-term (2030–2035) costs of automated, electrified, and shared mobility in the United States
Junia Compostella,
Lewis M. Fulton,
Robert De Kleine,
Hyung Chul Kim and
Timothy J. Wallington
Transport Policy, 2020, vol. 85, issue C, 54-66
Abstract:
Revolutions in shared mobility services, vehicle electrification, and automated vehicle technology will affect urban traffic patterns, energy use and CO2 emissions, the automotive industry, public transportation, and more. This paper examines the monetary costs of these innovations for users in the near-term (approximately 2020) and how they may evolve in the long-term (approximately 2030–2035). We estimate traveler costs for light duty vehicle trips on a per-mile basis, and investigate their sensitivity to vehicle powertrain, vehicle size, travel mode and intensity of vehicle use, and DC charging assumptions. To highlight differences between human and automated driving, we consider only autonomous vehicle scenarios in the long-term. We document three main findings. First, as battery costs continue to drop over the next decade, private battery electric vehicles will become more cost-competitive with internal combustion vehicles; and in high-mileage ridesourcing applications, electric vehicles will be much more cost-competitive. Second, near-term ridesourcing trips will likely remain about 4–5 times the per-mile cost of driving one's own car, while pooled trips cut this factor to around 3. Third, in the long-term automated vehicles may make ridesourcing cheaper than driving one's own vehicle. Even if the manufacturing cost of automated vehicles remains high, this cost will be minor when amortized over a service life of 400,000 miles. These findings are unchanged even with significant variations in assumed future battery and automation costs, electricity (charging) cost, vehicle insurance and maintenance cost, and ridesourcing providers' overhead rates.
Keywords: Electric vehicles; Automated vehicles; Ridesourcing; Monetary costs (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.tranpol.2019.10.001
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