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Impacts of Autonomous Vehicles on Consumers Time-Use Patterns

Author

Listed:
  • Saptarshi Das

    (Golisano Institute for Sustainability, Rochester Institute of Technology, 190 Lomb Memorial Drive, Rochester, NY 14623, USA)

  • Ashok Sekar

    (LBJ School of Public Affairs, University of Texas at Austin, 2300 Red River Street, E-2700, Austin, TX 78712, USA)

  • Roger Chen

    (Golisano Institute for Sustainability, Rochester Institute of Technology, 190 Lomb Memorial Drive, Rochester, NY 14623, USA)

  • Hyung Chul Kim

    (Research and Advanced Engineering, Ford Motor Company, 2101 Village Road, Dearborn, MI 48121, USA)

  • Timothy J. Wallington

    (Research and Advanced Engineering, Ford Motor Company, 2101 Village Road, Dearborn, MI 48121, USA)

  • Eric Williams

    (Golisano Institute for Sustainability, Rochester Institute of Technology, 190 Lomb Memorial Drive, Rochester, NY 14623, USA)

Abstract

We use the American Time Use Survey (ATUS) to characterize how different consumers in the US might use Autonomous Vehicles (AVs). Our approach is to identify sub-groups of the population likely to benefit from AVs and compare their activity patterns with an otherwise similar group. The first subgroup is working individuals who drive to work with long total travel times. Auto-travelers in the top 20% of travel time number 19 million and travel 1.6 h more on a workday than those in the bottom 80%. For car-commuting professionals, the additional travel time of the long-traveling group comes from 30 min less work, 29 min less sleep, and 30 min less television watching per day. The second subgroup is working individuals with a long travel time and who take public transport. Long public transit riders show very similar differences in activity times as the driving subgroup. Work, sleep, and video functionalities of AVs are presumably in high demand by both groups. The third sub-group identified is elderly retired people. AVs enable mobility-restricted groups to travel more like those without restrictions. We compare two age groups, 60–75 years and >75 years old, the latter, on average, experiencing more mobility restrictions than their younger counterparts. The retired population older than 75 years numbers 16 million and travels 14 min less per day than retirees aged 60–75 years. The main activity change corresponding to this reduced travel is 7 min per day less shopping and 8 min per day less socializing. If older retired people use AVs to match the lifestyle of the 60–75 years old group, this would induce additional personal travel and retail sector demand. The economic, environmental and social implications of AV are very difficult to predict but expected to be transformative. The contribution of this work is that it utilizes time-use surveys to suggest how AV adoption could induce lifestyle changes inside and outside the vehicle.

Suggested Citation

  • Saptarshi Das & Ashok Sekar & Roger Chen & Hyung Chul Kim & Timothy J. Wallington & Eric Williams, 2017. "Impacts of Autonomous Vehicles on Consumers Time-Use Patterns," Challenges, MDPI, vol. 8(2), pages 1-15, December.
  • Handle: RePEc:gam:jchals:v:8:y:2017:i:2:p:32-:d:122720
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    References listed on IDEAS

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    1. Beirão, Gabriela & Sarsfield Cabral, J.A., 2007. "Understanding attitudes towards public transport and private car: A qualitative study," Transport Policy, Elsevier, vol. 14(6), pages 478-489, November.
    2. Wadud, Zia & MacKenzie, Don & Leiby, Paul, 2016. "Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 1-18.
    3. Kitamura, Ryuichi & Fujii, Satoshi & Pas, Eric I., 1997. "Time-use data, analysis and modeling: toward the next generation of transportation planning methodologies," Transport Policy, Elsevier, vol. 4(4), pages 225-235, October.
    4. Yeh, Sonia, 2007. "An empirical analysis on the adoption of alternative fuel vehicles: The case of natural gas vehicles," Energy Policy, Elsevier, vol. 35(11), pages 5865-5875, November.
    5. Paulley, Neil & Balcombe, Richard & Mackett, Roger & Titheridge, Helena & Preston, John & Wardman, Mark & Shires, Jeremy & White, Peter, 2006. "The demand for public transport: The effects of fares, quality of service, income and car ownership," Transport Policy, Elsevier, vol. 13(4), pages 295-306, July.
    6. Jeffery B. Greenblatt & Samveg Saxena, 2015. "Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles," Nature Climate Change, Nature, vol. 5(9), pages 860-863, September.
    7. Sekar, Ashok & Williams, Eric & Chen, Roger, 2016. "Heterogeneity in time and energy use of watching television," Energy Policy, Elsevier, vol. 93(C), pages 50-58.
    8. Helveston, John Paul & Liu, Yimin & Feit, Elea McDonnell & Fuchs, Erica & Klampfl, Erica & Michalek, Jeremy J., 2015. "Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 73(C), pages 96-112.
    9. Kitamura, Ryuichi, 1984. "A model of daily time allocation to discretionary out-of-home activities and trips," Transportation Research Part B: Methodological, Elsevier, vol. 18(3), pages 255-266, June.
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