Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

References

• Anable, J., & Gatersleben, B. (2005). All work and no play? The role of instrumental and affective factors in work and leisure journeys by different travel modes. Transportation Research Part A: Policy and Practice, 39(2–3), 163–181. doi: 10.1016/j.tra.2004.09.008
   Web of Science ®Google Scholar
• Auld, J., Sokolov, V., & Stephens, T. S. (2017). Analysis of the effects of connected–automated vehicle technologies on travel demand. Transportation Research Record: Journal of the Transportation Research Board, 2625, 1–8. doi: 10.3141/2625-01
   Web of Science ®Google Scholar
• Bahamonde-Birke, F. J., Kickhöfer, B., Heinrichs, D., & Kuhnimhof, T. (2016). A systemic view on autonomous vehicles: Policy aspects for a sustainable transportation planning. German Aerospace Center. Retrieved from http://elib.dlr.de/108647/
   Google Scholar
• Bansal, P., Kockelman, K. M., & Singh, A. (2016). Assessing public opinions of and interest in new vehicle technologies: An Austin perspective. Transportation Research Part C: Emerging Technologies, 67, 1–14. doi: 10.1016/j.trc.2016.01.019
   Web of Science ®Google Scholar
• Becker, G. S. (1965). A theory of the allocation of time. The Economic Journal, 75(299), 493–517. doi: 10.2307/2228949
   Web of Science ®Google Scholar
• Bertoncello, M., & Wee, D. (2015). Ten ways autonomous driving could redefine the automotive world. New York: McKinsey & Company. Retrieved from https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/ten-ways-autonomous-driving-could-redefine-the-automotive-world https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/ten-ways-autonomous-driving-could-redefine-the-automotive-world
   Google Scholar
• Chase, R. (2017). Shared mobility principles for liveable cities. Retrieved from https://www.sharedmobilityprinciples.org/
   Google Scholar
• Childress, S., Nichols, B., Charlton, B., & Coe, S. (2015). Using an activity-based model to explore the potential impacts of automated vehicles. Transportation Research Record: Journal of the Transportation Research Board, 2493, 99–106. doi: 10.3141/2493-11
   Web of Science ®Google Scholar
• Circella, G., Mokhtarian, P. L., & Poff, L. K. (2012). A conceptual typology of multitasking behavior and polychronicity preferences. electronic International Journal of Time Use Research, 9(1), 59–107. doi: 10.13085/eijtur.9.1.59-107
   Google Scholar
• Cohen, B., & Kietzmann, J. (2014). Ride on! mobility business models for the sharing economy. Organization & Environment, 27(3), 279–296. doi: 10.1177/1086026614546199
   Web of Science ®Google Scholar
• Cyganski, R., Fraedrich, E., & Lenz, B. (2015). Travel-time valuation for automated driving: A use-case-driven study. Presented at the 94th annual meeting of the transportation research board, Washington, DC. Retrieved from https://trid.trb.org/view.aspx?id=1338518
   Google Scholar
• Davidson, P., & Spinoulas, A. (2015). Autonomous vehicles: What could this mean for the future of transport?Presented at the Australian institute of traffic planning and management national conference, 2015, Brisbane, AU. Retrieved from https://trid.trb.org/view.aspx?id=1371459
   Google Scholar
• Daziano, R. A., Sarrias, M., & Leard, B. (2017). Are consumers willing to pay to let cars drive for them? Analyzing response to autonomous vehicles. Transportation Research Part C: Emerging Technologies, 78, 150–164. doi: 10.1016/j.trc.2017.03.003
   Web of Science ®Google Scholar
• DeSerpa, A. C. (1971). A theory of the economics of time. The Economic Journal, 81(324), 828–846. doi: 10.2307/2230320
   Web of Science ®Google Scholar
• De Vos, J., & Witlox, F. (2016). Do people live in urban neighbourhoods because they do not like to travel? Analysing an alternative residential self-selection hypothesis. Travel Behaviour and Society, 4, 29–39. doi: 10.1016/j.tbs.2015.12.002
   Web of Science ®Google Scholar
• Diels, C., & Bos, J. E. (2016). Self-driving carsickness. Applied Ergonomics, 53, 374–382. doi: 10.1016/j.apergo.2015.09.009
   PubMed Web of Science ®Google Scholar
• Duxbury, L., Higgins, C., Smart, R., & Stevenson, M. (2014). Mobile technology and boundary permeability. British Journal of Management, 25(3), 570–588. doi: 10.1111/1467-8551.12027
   Web of Science ®Google Scholar
• Elbanhawi, M., Simic, M., & Jazar, R. (2015). In the passenger seat: Investigating ride comfort measures in autonomous cars. IEEE Intelligent Transportation Systems Magazine, 7(3), 4–17. doi: 10.1109/MITS.2015.2405571
   Web of Science ®Google Scholar
• Ettema, D., Gärling, T., Eriksson, L., Friman, M., Olsson, L. E., & Fujii, S. (2011). Satisfaction with travel and subjective well-being: Development and test of a measurement tool. Transportation Research Part F: Traffic Psychology and Behaviour, 14(3), 167–175. doi: 10.1016/j.trf.2010.11.002
   Web of Science ®Google Scholar
• Fagnant, D. J., & Kockelman, K. (2015). Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendations. Transportation Research Part A: Policy and Practice, 77, 167–181. doi: 10.1016/j.tra.2015.04.003
   Web of Science ®Google Scholar
• Gucwa, M. (2014). Mobility and energy impacts of automated cars. Presented at the automated vehicle symposium, San Francisco, CA. Retrieved from http://www.automatedvehiclessymposium.org/avs2014/proceedings
   Google Scholar
• Guo, Z., Derian, A., & Zhao, J. (2015). Smart devices and travel time use by bus passengers in Vancouver, Canada. International Journal of Sustainable Transportation, 9(5), 335–347. doi: 10.1080/15568318.2013.784933
   Web of Science ®Google Scholar
• Hägerstrand, T. (1970). What about people in regional science? Papers of the Regional Science Association, 24(1), 6–21. doi: 10.1007/BF01936872
   Google Scholar
• Hoberock, L. L. (1977). A survey of longitudinal acceleration comfort studies in ground transportation vehicles. Journal of Dynamic Systems, Measurement, and Control, 99(2), 76–84. doi: 10.1115/1.3427093
   Google Scholar
• Jain, J., & Lyons, G. (2008). The gift of travel time. Journal of Transport Geography, 16(2), 81–89. doi: 10.1016/j.jtrangeo.2007.05.001
   Web of Science ®Google Scholar
• Jara-Díaz, S. (2002). The goods/activities framework for discrete travel choices: Indirect utility and value of time. In H. I. Mahmassani (Ed.), In perpetual motion: Travel behaviour research opportunities and application challenges (pp. 415–429). Bingley: Emerald Group Publishing Limited.
   Google Scholar
• Keseru, I., & Macharis, C. (2018). Travel-based multitasking: Review of the empirical evidence. Transport Reviews, 38(2), 162–183. doi: 10.1080/01441647.2017.1317048
   Web of Science ®Google Scholar
• Kim, K., Rousseau, G., Freedman, J., & Nicholson, J. (2015). The travel impact of autonomous vehicles in metro Atlanta through activity-based modeling. Presented at the 15th transportation research board National Transportation Planning Applications conference, Atlantic City, NJ. Retrieved from http://www.trbappcon.org/2015conf/program.aspx
   Google Scholar
• Kockelman, K., Boyles, S., Stone, P., Fagnant, D., Patel, R., Levin, M. W., … Hutchinson, R. (2017). An assessment of autonomous vehicles: Traffic impacts and infrastructure needs (No. FHWA/TX-17/0-6847-1). Retrieved from https://trid.trb.org/view.aspx?id=1459480
   Google Scholar
• KPMG LLP, & Center for Automotive Research (CAR). (2012). Self-driving cars: The next revolution. Ann Arbor, MI: Center for Automotive Research. Retrieved from http://www.cargroup.org/publication/self-driving-cars-the-next-revolution/
   Google Scholar
• Krueger, R., Rashidi, T. H., & Rose, J. M. (2016). Preferences for shared autonomous vehicles. Transportation Research Part C: Emerging Technologies, 69, 343–355. doi: 10.1016/j.trc.2016.06.015
   Web of Science ®Google Scholar
• LaMondia, J. J., Fagnant, D. J., Qu, H., Barrett, J., & Kockelman, K. (2016). Shifts in long-distance travel mode due to automated vehicles: Statewide mode-shift simulation experiment and travel survey analysis. Transportation Research Record: Journal of the Transportation Research Board, 2566, 1–11. doi: 10.3141/2566-01
   Web of Science ®Google Scholar
• Le Vine, S., Zolfaghari, A., & Polak, J. (2015). Autonomous cars: The tension between occupant experience and intersection capacity. Transportation Research Part C: Emerging Technologies, 52, 1–14. doi: 10.1016/j.trc.2015.01.002
   Web of Science ®Google Scholar
• Lyons, G., Jain, J., & Weir, I. (2016). Changing times – A decade of empirical insight into the experience of rail passengers in Great Britain. Journal of Transport Geography, 57, 94–104. doi: 10.1016/j.jtrangeo.2016.10.003
   Web of Science ®Google Scholar
• Lyons, G., & Urry, J. (2005). Travel time use in the information age. Transportation Research Part A: Policy and Practice, 39(2–3), 257–276. doi: 10.1016/j.tra.2004.09.004
   Web of Science ®Google Scholar
• Malokin, A., Circella, G., & Mokhtarian, P. L. (2015). How do activities conducted while commuting influence mode choice? Testing public transportation advantage and autonomous vehicle scenarios. Presented at the 94th annual meeting of the transportation research board, Washington, DC. Retrieved from http://trid.trb.org/view.aspx?id=1336974
   Google Scholar
• McDonald, N. C. (2015). Are millennials really the “go-nowhere” generation? Journal of the American Planning Association, 81(2), 90–103. doi: 10.1080/01944363.2015.1057196
   Web of Science ®Google Scholar
• Milakis, D., Snelder, M., van Arem, B., van Wee, B., & Correia, G. H. d. A. (2017). Development and transport implications of automated vehicles in the Netherlands: Scenarios for 2030 and 2050. European Journal of Transport & Infrastructure Research, 17(1), 63–85. Retrieved from https://www.tudelft.nl/tbm/over-de-faculteit/afdelingen/engineering-systems-and-services/research/ejtir/back-issues/volume17-2017/
   Web of Science ®Google Scholar
• Milakis, D., van Arem, B., & van Wee, B. (2017). Policy and society related implications of automated driving: A review of literature and directions for future research. Journal of Intelligent Transportation Systems, 21(4), 324–348. doi: 10.1080/15472450.2017.1291351
   Web of Science ®Google Scholar
• Mokhtarian, P. L., & Salomon, I. (2001). How derived is the demand for travel? Some conceptual and measurement considerations. Transportation Research Part A: Policy and Practice, 35(8), 695–719. doi: 10.1016/S0965-8564(00)00013-6
   Web of Science ®Google Scholar
• Mokhtarian, P. L., Salomon, I., & Singer, M. E. (2015). What moves us? An interdisciplinary exploration of reasons for traveling. Transport Reviews, 35(3), 250–274. doi: 10.1080/01441647.2015.1013076
   Web of Science ®Google Scholar
• Nelson, A. C. (2017). Planners & driverless cars: Perspectives on technology, timing, efficiency, & equity. Presented at the 57th annual conference of the association of collegiate schools of planning, Denver, CO.
   Google Scholar
• Ory, D. T., & Mokhtarian, P. L. (2009). Modeling the structural relationships among short-distance travel amounts, perceptions, affections, and desires. Transportation Research Part A: Policy and Practice, 43(1), 26–43. doi: 10.1016/j.tra.2008.06.004
   Web of Science ®Google Scholar
• Reddit. (2013, January 4). If someone from the 1950s suddenly appeared today, what would be the most difficult thing to explain to them about life today? Message posted to. Retrieved from https://redd.it/15yaap
   Google Scholar
• SAE International. (2016). Taxonomy and definitions for terms related to on-road motor vehicle automated driving systems (Standard J3016_201609). Warrendale, PA: SAE International. Retrieved from http://standards.sae.org/j3016_201609/
   Google Scholar
• Salomon, I., & Mokhtarian, P. L. (1998). What happens when mobility-inclined market segments face accessibility-enhancing policies? Transportation Research Part D: Transport and Environment, 3(3), 129–140. doi: 10.1016/S1361-9209(97)00038-2
   Web of Science ®Google Scholar
• Schwanen, T., & Mokhtarian, P. L. (2005). What if you live in the wrong neighborhood? The impact of residential neighborhood type dissonance on distance traveled. Transportation Research Part D: Transport and Environment, 10(2), 127–151. doi: 10.1016/j.trd.2004.11.002
   Web of Science ®Google Scholar
• Shanker, R., Jonas, A., Devitt, S., Huberty, K., Flannery, S., Greene, W., … Humphrey, A. (2013). Autonomous cars: Self-driving the new auto industry paradigm. New York, NY: Morgan Stanley Research. Retrieved from https://orfe.princeton.edu/~alaink/SmartDrivingCars/PDFs/Nov2013MORGAN-STANLEY-BLUE-PAPER-AUTONOMOUS-CARSEFBC%9A-SELF-DRIVING-THE-NEW-AUTO-INDUSTRY-PARADIGM.pdf
   Google Scholar
• Singleton, P. A. (2017). Exploring the positive utility of travel and mode choice (doctoral dissertation). Portland State University, Portland, OR. doi.org/10.15760/etd.3447
   Google Scholar
• Singleton, P. A. (2018). Walking (and cycling) to well-being: Modal and other determinants of subjective well-being during the commute. Travel Behaviour and Society. doi: 10.1016/j.tbs.2018.02.005
   Web of Science ®Google Scholar
• Singleton, P. A. (in progress). Multimodal travel-based multitasking during the commute: Who does what? Available from the author.
   Google Scholar
• Singleton, P. A. (in press). How useful is travel-based multitasking? Evidence from Portland, Oregon, commuters. Transportation Research Record: Journal of the Transportation Research Board.
   Google Scholar
• Singleton, P. A., & Mokhtarian, P. L. (in progress). Is there a positive utility of travel? A review of concepts, measures, and evidence. Available from the authors.
   Google Scholar
• Sivak, M., & Schoettle, B. (2016). Would self-driving vehicles increase occupant productivity? (No. SWT-2016-11). Ann Arbor, MI: Sustainable World Transportation. Retrieved from https://trid.trb.org/view.aspx?id=1480404
   Google Scholar
• Smith, B. W. (2012). Managing autonomous transportation demand. Santa Clara Law Review, 52(4), 1401–1422. Retrieved from http://digitalcommons.law.scu.edu/lawreview/vol52/iss4/8
   Google Scholar
• Spieser, K., Treleaven, K., Zhang, R., Frazzoli, E., Morton, D., & Pavone, M. (2014). Toward a systematic approach to the design and evaluation of automated mobility-on-demand systems: A case study in Singapore. In G. Meyer, & S. Beiker (Eds.), Road vehicle automation (pp. 229–245). Berlin, DE: Springer International Publishing.
   Google Scholar
• Steck, F., Kolarova, V., Bahamonde-Birke, F., Trommer, S., & Lenz, B. (2018). How autonomous driving may affect the value of travel time savings for commuting. Presented at the 97th annual meeting of the transportation research board, Washington, DC. Retrieved from http://elib.dlr.de/115497/
   Google Scholar
• Steg, L. (2005). Car use: Lust and must. Instrumental, symbolic and affective motives for car use. Transportation Research Part A: Policy and Practice, 39(2), 147–162. doi:10.1016/j.tra.2004.07.001.
   Web of Science ®Google Scholar
• Susilo, Y., Lyons, G., Jain, J., & Atkins, S. (2012). Rail passengers’ time use and utility assessment: 2010 findings from Great Britain with multivariate analysis. Transportation Research Record: Journal of the Transportation Research Board, 2323, 99–109. doi:10.3141/2323-12.
   Web of Science ®Google Scholar
• Thompson, C. (2016, December 14). 8 ways self-driving cars will drastically improve our lives. Business Insider. Retrieved from http://www.businessinsider.com/how-driverless-cars-will-change-lives-2016-12
   Google Scholar
• van den Berg, V. A., & Verhoef, E. T. (2016). Autonomous cars and dynamic bottleneck congestion: The effects on capacity, value of time and preference heterogeneity. Transportation Research Part B: Methodological, 94, 43–60. doi: 10.1016/j.trb.2016.08.018
   Web of Science ®Google Scholar
• van der Waerden, P. J., Kemperman, A., Timmermans, H., & van Hulle, R. (2010). The influence of facilities for multitasking on individual’s travel decisions in the context of work trips. Presented at the 89th annual meeting of the transportation research board, Washington, DC. Retrieved from http://trid.trb.org/view.aspx?id=910535
   Google Scholar
• Wadud, Z., MacKenzie, D., & Leiby, P. (2016). Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles. Transportation Research Part A: Policy and Practice, 86, 1–18. doi: 10.1016/j.tra.2015.12.001
   Web of Science ®Google Scholar
• Watts, L., & Urry, J. (2008). Moving methods, travelling times. Environment and Planning D: Society and Space, 26(5), 860–874. doi: 10.1068/d6707
   Web of Science ®Google Scholar
• Waymo. (2017). Waymo. Retrieved from https://waymo.com/
   Google Scholar
• Willumsen, L., & Kohli, S. (2016). Traffic forecasting and autonomous vehicles. Presented at the 44th European Transport Conference, Barcelona, ES. Retrieved from https://abstracts.aetransport.org/paper/index/id/4789/confid/21
   Google Scholar
• Xing, Y., Handy, S. L., & Mokhtarian, P. L. (2010). Factors associated with proportions and miles of bicycling for transportation and recreation in six small US cities. Transportation Research Part D: Transport and Environment, 15(2), 73–81. doi: 10.1016/j.trd.2009.09.004
   Web of Science ®Google Scholar
• Yap, M. D., Correia, G., & Van Arem, B. (2016). Preferences of travellers for using automated vehicles as last mile public transport of multimodal train trips. Transportation Research Part A: Policy and Practice, 94, 1–16. doi: 10.1016/j.tra.2016.09.003
   Web of Science ®Google Scholar
• Zhao, Z., & Zhao, J. (2015). Car pride: Psychological structure and behavioral implications. Presented at the 94th annual meeting of the transportation research board, Washington, DC. Retrieved from https://trid.trb.org/view.aspx?id=1336944
   Google Scholar
• Zmud, J., Sener, I. N., & Wagner, J. (2016). Self-driving vehicles: Determinants of adoption and conditions of usage. Transportation Research Record: Journal of the Transportation Research Board, 2565, 57–64. doi: 10.3141/2565-07
   Web of Science ®Google Scholar