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A Quantitative Analysis of Possible Futures of Autonomous Transport

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  • Christopher L. Benson
  • Pranav D Sumanth
  • Alina P Colling

Abstract

Autonomous ships (AS) used for cargo transport have gained a considerable amount of attention in recent years. They promise benefits such as reduced crew costs, increased safety and increased flexibility. This paper explores the effects of a faster increase in technological performance in maritime shipping achieved by leveraging fast-improving technological domains such as computer processors, and advanced energy storage. Based on historical improvement rates of several modes of transport (Cargo Ships, Air, Rail, Trucking) a simplified Markov-chain Monte-Carlo (MCMC) simulation of an intermodal transport model (IMTM) is used to explore the effects of differing technological improvement rates for AS. The results show that the annual improvement rates of traditional shipping (Ocean Cargo Ships = 2.6%, Air Cargo = 5.5%, Trucking = 0.6%, Rail = 1.9%, Inland Water Transport = 0.4%) improve at lower rates than technologies associated with automation such as Computer Processors (35.6%), Fuel Cells (14.7%) and Automotive Autonomous Hardware (27.9%). The IMTM simulations up to the year 2050 show that the introduction of any mode of autonomous transport will increase competition in lower cost shipping options, but is unlikely to significantly alter the overall distribution of transport mode costs. Secondly, if all forms of transport end up converting to autonomous systems, then the uncertainty surrounding the improvement rates yields a complex intermodal transport solution involving several options, all at a much lower cost over time. Ultimately, the research shows a need for more accurate measurement of current autonomous transport costs and how they are changing over time.

Suggested Citation

  • Christopher L. Benson & Pranav D Sumanth & Alina P Colling, 2018. "A Quantitative Analysis of Possible Futures of Autonomous Transport," Papers 1806.01696, arXiv.org.
    • Handle: RePEc:arx:papers:1806.01696
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    References listed on IDEAS

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    1. Christopher L Benson & Christopher L Magee, 2015. "Quantitative Determination of Technological Improvement from Patent Data," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-23, April.
    2. Edward L. Glaeser & Janet E. Kohlhase, 2004. "Cities, regions and the decline of transport costs," Advances in Spatial Science, in: Raymond J. G. M. Florax & David A. Plane (ed.), Fifty Years of Regional Science, pages 197-228, Springer.
    3. David S. Jacks & Christopher M. Meissner & Dennis Novy, 2008. "Trade Costs, 1870-2000," American Economic Review, American Economic Association, vol. 98(2), pages 529-534, May.
    4. Bansal, Prateek & Kockelman, Kara M., 2017. "Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 49-63.
    5. David S Jacks & Krishna Pendakur, 2010. "Global Trade and the Maritime Transport Revolution," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 745-755, November.
    6. David Hummels, 2007. "Transportation Costs and International Trade in the Second Era of Globalization," Journal of Economic Perspectives, American Economic Association, vol. 21(3), pages 131-154, Summer.
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    Cited by:

    1. Park, Seongbeom & Lee, Hyunju & Kim, Dowon, 2024. "Regulatory compliance and operational efficiency in maritime transport: Strategies and insights," Transport Policy, Elsevier, vol. 155(C), pages 161-177.
    2. Ivan Yanchin & Oleg Petrov, 2021. "Validation and Refinement of a Ship Route During the Voyage," SN Operations Research Forum, Springer, vol. 2(2), pages 1-22, June.

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