Adoption of partially automated vehicle technology features and impacts on vehicle miles of travel (VMT)

AAA, 2019. Advanced driver assistant technology names, https://www.aaa.com/AAA/common/AAR/files/ADAS-Technology-Names-Research-Report.pdf. Accessed December 23, 2021. Abraham, H., Lee, C., Brady, S., Fitzgerald, C., Mehler, B., Reimer, B., and Coughlin, J. F., 2017. Autonomous vehicles and alternatives to driving: Trust, preferences, and effects of age. InTransportation Research Board 96th Annual Meeting Compendium of Papers, Washington D.C., January. Acheampong, 2019, Capturing the behavioural determinants behind the adoption of autonomous vehicles: Conceptual frameworks and measurement models to predict public transport, sharing and ownership trends of self-driving cars, Transp. Res. Part F, 62, 349, 10.1016/j.trf.2019.01.009 Acheampong, 2021, Can autonomous vehicles enable sustainable mobility in future cities? Insights and policy challenges from user preferences over different urban transport options, Cities, 112, 103134, 10.1016/j.cities.2021.103134 Ajzen, 1991, The theory of planned behavior, Organ. Behav. Hum. Decis. Process., 50, 179, 10.1016/0749-5978(91)90020-T Asgari, 2019, Incorporating attitudinal factors to examine adoption of and willingness to pay for autonomous vehicles, Transport. Res. Record J. Transport. Res. Board, 2673, 418, 10.1177/0361198119839987 Asmussen, 2020, A socio-technical model of autonomous vehicle adoption using ranked choice stated preference data, Transp. Res. Part C, 121, 102835, 10.1016/j.trc.2020.102835 Beck, 2007, Motor vehicle crash injury rates by mode of travel, United States: using exposure-based methods to quantify differences, Am. J. Epidemiol., 166, 212, 10.1093/aje/kwm064 Benedettini, 2012, The costs of avoiding accidents: Selective compliance and the ‘Peltzman effect in Italy, Int. Rev. Law Economics, 32, 256, 10.1016/j.irle.2012.02.001 Berkowsky, 2017, Factors predicting decisions about technology adoption among older adults, Innovat. Aging, 1, 1 Berliner, 2019, Uncovering early adopter’s perceptions and purchase intentions of automated vehicles: Insights from early adopters of electric vehicles in California, Transp. Res. Part F, 60, 712, 10.1016/j.trf.2018.11.010 Bhat, 2014, The composite marginal likelihood (CML) inference approach with applications to discrete and mixed dependent variable models, Found. Trends Econometrics, 7, 1, 10.1561/0800000022 Bhat, 2015, A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables, Transp. Res. Part B, 79, 50, 10.1016/j.trb.2015.05.017 Bhat, 2016, On accommodating spatial interactions in a generalized heterogeneous data model (GHDM) of mixed types of dependent variables, Transp. Res. Part B, 94, 240, 10.1016/j.trb.2016.09.002 Bhat, 2020, A multiple discrete extreme value choice model with grouped consumption data and unobserved budgets, Transp. Res. Part B, 141, 196, 10.1016/j.trb.2020.09.008 Blazanin, 2022, E-scooter sharing and bikesharing systems: An individual-level analysis of factors affecting first-use and use frequency, Transp. Res. Part C, 135, 103515, 10.1016/j.trc.2021.103515 Bomey, N., 2018. Backup cameras now required in new cars in the US. CNBC. https://www.cnbc.com/2018/05/02/backup-cameras-now-required-in-new-cars-in-the-us.html. Accessed January 10, 2021. Borghans, 2009, Gender differences in risk aversion and ambiguity aversion, J. European Economic Assoc., 7, 649, 10.1162/JEEA.2009.7.2-3.649 Brown, 2017, Car-less or car-free? Socioeconomic and mobility differences among zero-car households, Transp. Policy, 60, 152, 10.1016/j.tranpol.2017.09.016 Chan, 2017, Advancements, prospects, and impacts of automated driving systems, Int. J. Transp. Sci. Technol., 6, 208, 10.1016/j.ijtst.2017.07.008 Charness, 2018, Predictors of attitudes toward autonomous vehicles: The roles of age, gender, prior knowledge, and personality, Front. Psychol., 9, 25, 10.3389/fpsyg.2018.02589 Chesters, 2019, Young adulthood in uncertain times: The association between sense of personal control and employment, education, personal relationships and health, J. Sociol., 55, 389, 10.1177/1440783318800767 Chirinko, 1993, Buckle up or slow down? New estimates of offsetting behavior and their implications for automobile safety regulation, J. Policy Anal. Manage., 12, 270, 10.2307/3325236 Cicchino, 2017, Effects of rearview cameras and rear parking sensors on police-reported backing crashes, Traffic Inj. Prev., 18, 859, 10.1080/15389588.2017.1317758 Cicchino, 2018, Effects of lane departure warning on police-reported crash rates, J. Saf. Res., 66, 61, 10.1016/j.jsr.2018.05.006 Cicchino, 2018, Effects of blind spot monitoring systems on police-reported lane-change crashes, Traffic Inj. Prev., 19, 615, 10.1080/15389588.2018.1476973 Ciciolla, 2019, Invisible household labor and ramifications for adjustment: Mothers as captains of households, Sex Roles, 81, 467, 10.1007/s11199-018-1001-x Covington, T., 2021. Average miles driven per year by Americans. The Zebra. https://www.thezebra.com/resources/driving/average-miles-driven-per-year/#infographic. Accessed May 17, 2021. Craig, 2010, Parenthood, gender and work-family time in the United States, Australia, Italy, France, and Denmark, J. Marriage Family, 72, 1344, 10.1111/j.1741-3737.2010.00769.x Crump, 2016, Differing perceptions of advanced driver assistance systems (ADAS), 861 Cugurullo, 2021, The transition to autonomous cars, the redesign of cities and the future of urban sustainability, Urban Geography, 42, 833, 10.1080/02723638.2020.1746096 Dannemiller, 2021, Investigating autonomous vehicle impacts on individual activity-travel behavior, Transp. Res. Part A, 148, 402 Davis, 1989, Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 319, 10.2307/249008 de Miguel, M. Á., Fuchshuber, D., Hussein, A., and Olaverri-Monreal, C., 2019. Perceived pedestrian safety: Public interaction with driverless vehicles. 2019 IEEE Intelligent Vehicles Symposium (IV), Paris, France, 90-95. https://doi.org/10.1109/IVS.2019.8814145. Demuro, D., 2019. Buying a car: How long can you expect a car to last? Autotrader. https://www.autotrader.com/car-shopping/buying-car-how-long-can-you-expect-car-last-240725. Accessed January 11, 2021. Ding, 2017, Investigating the impacts of built environment on vehicle miles traveled and energy consumption: Differences between commuting and non-commuting trips, Cities, 68, 25, 10.1016/j.cities.2017.05.005 Duarte, 2018, The impact of autonomous vehicles on cities: A review, J. Urban Technol., 25, 3, 10.1080/10630732.2018.1493883 Edmonds, E., 2020. AAA finds active driving assistance systems do less to assist drivers and more to interfere. AAA Newsroom. https://newsroom.aaa.com/2020/08/aaa-finds-active-driving-assistance-systems-do-less-to-assist-drivers-and-more-to-interfere/. Accessed July 5th, 2021. Elliot, 2018, Lifetime trauma, perceived control, and all-cause mortality: Results from the Midlife in the United States Study, Health Psychol., 37, 262, 10.1037/hea0000585 Federal Highway Administration, 2018. Average annual miles per driver by age group. Federal Highway Administration. https://www.fhwa.dot.gov/ohim/onh00/bar8.htm. Accessed May 17, 2021. Fernandes, 2017, Characteristics and human factors of older drivers: Improvement opportunities in automotive interior design, Int. J. Veh. Des., 74, 167, 10.1504/IJVD.2017.086418 Fountas, 2019, The effects of driver fatigue, gender, and distracted driving on perceived and observed aggressive driving behavior: A correlated grouped random parameters bivariate probit approach, Analytic Meth. Accident Res., 22, 10.1016/j.amar.2019.100091 Fraedrich, 2019, Autonomous driving, the built environment and policy implications, Transp. Res. Part A, 122, 162 Freeman, 2010, Self-control depletion leads to increased risk taking, Social Psycholog. Personality Sci., 1, 175, 10.1177/1948550609360421 Ghasri, 2021, The potential impact of media commentary and social influence on consumer preferences for driverless cars, Transp. Res. Part C, 127, 10.1016/j.trc.2021.103132 Gish, 2017, Driving with advanced vehicle technology: A qualitative investigation of older drivers’ perceptions and motivations for use, Accid. Anal. Prev., 106, 498, 10.1016/j.aap.2016.06.027 Gkartzonikas, 2019, What have we learned? A review of stated preference and choice studies on autonomous vehicles, Transp. Res. Part C, 98, 323, 10.1016/j.trc.2018.12.003 Gomez, 2021, Adoption and frequency of use of ride-hailing services in a European city: The case of Madrid, Transp. Res. Part C, 131, 10.1016/j.trc.2021.103359 González Gutiérrez, 2005, Personality and subjective well-being: Big five correlates and demographic variables, Personality Individ. Differ., 38, 1561, 10.1016/j.paid.2004.09.015 Gorzelany, J., 2020. Safety last? Driver-assist features that are most often switched off. Forbes. https://www.forbes.com/sites/jimgorzelany/2020/07/07/safety-last-driver-assist-features-that-are-most-likely-switched-off/?sh=3b714fb25d0e. Accessed January 11, 2021. Goulias, 2013, Keynote - Total design data needs for the new generation large-scale activity microsimulation models, 21 Guo, 2015, Smart devices and travel time use by bus passengers in Vancouver, Canada, Int. J. Sustain. Transport., 9, 335, 10.1080/15568318.2013.784933 Haboucha, 2017, User preferences regarding autonomous vehicles, Transp. Res. Part C, 78, 37, 10.1016/j.trc.2017.01.010 Harb, 2018, Projecting travelers into a world of self-driving vehicles: Estimating travel behavior implications via a naturalistic experiment, Transportation, 45, 1671, 10.1007/s11116-018-9937-9 Hardman, S., 2020. Travel behavior changes among users of partially automated vehicles. Technical Report UC-ITS-2019-04. Institute of Transportation Studies, University of California, Davis. Hardman, 2019, Who will be the early adopters of automated vehicles? Insights from a survey of electric vehicle owners in the United States, Transp. Res. Part D, 71, 248, 10.1016/j.trd.2018.12.001 Hardman, 2021, A quantitative investigation into the impact of partially automated vehicles on vehicle miles travelled in California Harvey, 2011, The categorisation of drivers in relation to boredom, Transport. Planning Technol., 34, 51, 10.1080/03081060.2011.530829 Hill, 2007, Driver stress as influenced by driving maneuvers and roadway conditions, Transp. Res. Part F, 10, 177, 10.1016/j.trf.2006.09.002 IEEE Innovation at Work, 2020. New level 3 autonomous vehicles hitting the road in 2020. IEEE. https://innovationatwork.ieee.org/new-level-3-autonomous-vehicles-hitting-the-road-in-2020/. Accessed January 11, 2021. Jiang, 2019, Capturing ownership behavior of autonomous vehicles in Japan based on a stated preference survey and a mixed logit model with repeated choices, Int. J. Sustain. Transport., 13, 788, 10.1080/15568318.2018.1517841 Johnson, 2021, Self-control and need satisfaction in primetime: Television, social media, and friends can enhance regulatory resources via perceived autonomy and competence, Psychol. Popular Media, 10, 212, 10.1037/ppm0000286 Kamalanathsharma, 2015, Survey on in-vehicle technology use: Results and findings, Int. J. Transp. Sci. Technol., 4, 135, 10.1260/2046-0430.4.2.135 Ke, 2017, Regional differences in the determinants of Oregon VMT, Res. Transport. Economics, 62, 2, 10.1016/j.retrec.2017.03.002 Keseru, 2018, Travel-based multitasking: Review of the empirical evidence, Transport Rev., 38, 162, 10.1080/01441647.2017.1317048 Kessler, 2009, Experience enlargement: Age differences and development chances across adulthood and old age. Produktivität in Alternden Gesellschaften (Altern in Deutschland, Bd. 4), Nova Acta Leopoldina NF Bd, 102, 105 Kim, 2020, How, and for whom, will activity patterns be modified by self-driving cars? Expectations from the state of Georgia, Transp. Res. Part F, 70, 68, 10.1016/j.trf.2020.02.012 Krueger, 2019, Autonomous driving and residential location preferences: Evidence from a stated choice survey, Transp. Res. Part C, 108, 255, 10.1016/j.trc.2019.09.018 Laferton, 2018, The Beliefs About Stress Scale (BASS): Development, reliability, and validity, Int. J. Stress Manage., 25, 72, 10.1037/str0000047 Lavieri, 2019, Investigating objective and subjective factors influencing the adoption, frequency, and characteristics of ride-hailing trips, Transp. Res. Part C, 105, 100, 10.1016/j.trc.2019.05.037 Lavieri, 2017, Modeling individual preferences for ownership and sharing of autonomous vehicle technologies, Transport. Res. Record J. Transport. Res. Board, 2665, 1, 10.3141/2665-01 Lavieri, 2017, Investigation of heterogeneity in vehicle ownership and usage for the millennial generation, Transport. Res. Record J. Transport. Res. Board, 2664, 91, 10.3141/2664-10 Lee, 2019, Acceptance of vehicle automation: Effects of demographic traits, technology experience and media exposure, 2066 Leung, 2018, Man versus machine: Resisting automation in identity-based consumer behavior, J. Mark. Res., 55, 818, 10.1177/0022243718818423 Levy, V.,2020. Travel trends. AARP Research. https://www.aarp.org/content/dam/aarp/research/surveys_statistics/life-leisure/2019/2020-travel-trends.doi.10.26419-2Fres.00359.001.pdf. Accessed July 20, 2020. Li, 2003, Fragility versus excessive crash involvement as determinants of high death rates per vehicle-mile of travel among older drivers, Accid. Anal. Prev., 35, 227, 10.1016/S0001-4575(01)00107-5 Li, 2017, Evaluating the safety impact of adaptive cruise control in traffic oscillations on freeways, Accid. Anal. Prev., 104, 137, 10.1016/j.aap.2017.04.025 Liljamo, 2018, Attitudes and concerns on automated vehicles, Transp. Res. Part F, 59, 24, 10.1016/j.trf.2018.08.010 Maddala, 1986 Marikyan, 2019, A systematic review of the smart home literature: A user perspective, Technol. Forecast. Soc. Chang., 138, 139, 10.1016/j.techfore.2018.08.015 Massie, 1997, Crash involvement rates by driver gender and the role of average annual mileage, Accid. Anal. Prev., 29, 675, 10.1016/S0001-4575(97)00037-7 McFarlane, A., and Harvey, S., 2017. Trauma and its effects.In Foundations of Clinical Psychiatry Fourth Edition (S. Bloch, S.A. Green, A. Janca, P.B. Mitchell, and M. Robertson, eds.), Ch. 9, Melbourne University Press, Victoria. Meier-Pesti, 2008, Sex or gender? Expanding the sex-based view by introducing masculinity and femininity as predictors of financial risk taking, J. Econ. Psychol., 29, 180, 10.1016/j.joep.2007.05.002 Milakis, 2017, Policy and society related implications of automated driving: A review of literature and directions for future research, J. Intelligent Transport. Syst., 21, 324, 10.1080/15472450.2017.1291351 Mindell, J. S., Leslie, D., and Wardlaw, M., 2012. OP33 exposure-based assessment of modal travel risk in England using routine health data.Journal of Epidemiology & Community Health,66(1), A13-A13. Moody, 2020, Public perceptions of autonomous vehicle safety: An international comparison, Saf. Sci., 121, 634, 10.1016/j.ssci.2019.07.022 Moore, 2020, On investigating the potential effects of private autonomous vehicle use on home/work relocations and commute times, Transp. Res. Part C, 110, 166, 10.1016/j.trc.2019.11.013 Morris, 2020, Does lacking a car put the brakes on activity participation? Private vehicle access and access to opportunities among low-income adults, Transp. Res. Part A, 136, 375 Nair, 2021, Sharing the road with autonomous vehicles: Perceived safety and regulatory preferences, Transp. Res. Part C, 122, 10.1016/j.trc.2020.102885 Nair, 2018, An application of a rank ordered probit modeling approach to understanding level of interest in autonomous vehicles, Transportation, 45, 1623, 10.1007/s11116-018-9945-9 Narayanan, 2020, Shared autonomous vehicle services: A comprehensive review, Transp. Res. Part C, 111, 255, 10.1016/j.trc.2019.12.008 Narisada, 2016, A quintessentially American thing? The unexpected link between individualistic values and the sense of personal control, Society Mental Health, 6, 147, 10.1177/2156869316667448 Nikitas, 2018, Understanding the public acceptability of road pricing and the roles of older age, social norms, pro-social values and trust for urban policy-making: The case of Bristol, Cities, 79, 78, 10.1016/j.cities.2018.02.024 Oliveira, 2019, Perception of risk and precautionary behavior in cybersecurity: Hints for future research, 28 Owens, 2015, Cross-generational acceptance of and interest in advanced vehicle technologies: A nationwide survey, Transp. Res. Part F, 35, 139, 10.1016/j.trf.2015.10.020 Paillard-Borg, 2009, Pattern of participation in leisure activities among older people in relation to their health conditions and contextual factors: A survey in a Swedish urban area, Ageing Soc., 29, 803, 10.1017/S0144686X08008337 Paleti, 2011, A joint tour-based model of tour complexity, passenger accompaniment, vehicle type choice, and tour length Papadimitriou, 2013, Exposure data and risk indicators for safety performance assessment in Europe, Accid. Anal. Prev., 60, 371, 10.1016/j.aap.2013.04.040 Parnell, S. E., 2007. How a man’s mind REALLY works! Part 4. Fairmont Medical Center, Mayo Health System. http://www.dulcimermedicalcenter.org/documents/mans_mind4_040505.pdf. Accessed June 29, 2021. Pei, 2012, The roles of exposure and speed in road safety analysis, Accid. Anal. Prev., 48, 464, 10.1016/j.aap.2012.03.005 Peltzman, 1975, The Effects of Automobile Safety Regulation, J. Political Economy, 83, 677, 10.1086/260352 Peterson, 1995, Are drivers of air-bag-equipped cars more aggressive? A test of the offsetting behavior hypothesis, J. Law Economics, 38, 251, 10.1086/467331 Piao, 2016, Public views towards implementation of automated vehicles in urban areas, Transp. Res. Procedia, 14, 2168, 10.1016/j.trpro.2016.05.232 Rahimi, 2020, Examining human attitudes toward shared mobility options and autonomous vehicles, Transp. Res. Part F, 72, 133, 10.1016/j.trf.2020.05.001 Rogers, 2017, Envisioning the future for older adults: Autonomy, health, well-being, and social connectedness with technology support, Futures, 87, 133, 10.1016/j.futures.2016.07.002 Santamariña-Rubio, 2014, Gender differences in road traffic injury rate using time travelled as a measure of exposure, Accid. Anal. Prev., 65, 1, 10.1016/j.aap.2013.11.015 Schroeder, P., Wilbur, M., and Peña, R., 2018. National survey on distracted driving attitudes and behaviors – 2015, Report No. DOT HS 812 461, National Highway Traffic Safety Administration. Sen, 2001, An empirical test of the offset hypothesis, J. Law Economics, 44, 481, 10.1086/322051 Sener, 2019, Measures of baseline intent to use automated vehicles: A case study of Texas cities, Transp. Res. Part F, 62, 66, 10.1016/j.trf.2018.12.014 Sharma, 2020, Modeling consumers' likelihood to adopt autonomous vehicles based on their peer network, Transp. Res. Part D, 87, 10.1016/j.trd.2020.102509 Shen, 2020, Comparing distance and time as driving exposure measures to evaluate fatal crash risk ratios, Accid. Anal. Prev., 142, 10.1016/j.aap.2020.105576 Shimazaki, 2018, The public's understanding of the functionality and limitations of automatic braking in Japan, IATSS Res., 42, 221, 10.1016/j.iatssr.2017.11.002 Shin, 2015, Consumer preferences and willingness to pay for advanced vehicle technology options and fuel types, Transp. Res. Part C, 60, 511, 10.1016/j.trc.2015.10.003 Singh, 2018, Quantifying the relative contribution of factors to household vehicle miles of travel, Transp. Res. Part D, 63, 23, 10.1016/j.trd.2018.04.004 Skuladottir, 2008, Women in chronic pain: Sense of control and encounters with health professionals, Qual. Health Res., 18, 891, 10.1177/1049732308318036 Society of Automotive Engineers (SAE), 2018. SAE International Releases Updated Visual Chart for Its “Levels of Driving Automation” Standard for Self-Driving Vehicles. https://www.sae.org/news/press-room/2018/12/sae-international-releases-updated-visual-chart-for-its-%E2%80%9Clevels-of-driving-automation%E2%80%9D-standard-for-self-driving-vehicles. Accessed October 5, 2020. Solon, 2015, What are we weighting for?, J. Human Resour., 50, 301, 10.3368/jhr.50.2.301 Soteropoulos, 2019, Impacts of automated vehicles on travel behaviour and land use: An international review of modelling studies, Transport Rev., 39, 29, 10.1080/01441647.2018.1523253 Souris, 2019, Attitudes of Greek drivers towards autonomous vehicles-a preliminary analysis using stated preference approach, Adv. Transp. Stud., 48, 105 Spurlock, 2019, Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area, Transp. Res. Part D, 71, 283, 10.1016/j.trd.2019.01.014 Sweet, 2020, No longer in the driver’s seat: How do affective motivations impact consumer interest in automated vehicles?, Transportation, 47, 2601, 10.1007/s11116-019-10035-5 Traynor, 1993, The Peltzman hypothesis revisited: An isolated evaluation of offsetting driver behavior, J. Risk Uncertainty, 7, 237, 10.1007/BF01065816 U.S. Census Bureau, 2018. American Community Survey 1-year estimates. Census Reporter Profile page for Austin-Round Rock, TX Metro Area. https://censusreporter.org/profiles/31000US12420-austin-round-rock-tx-metro-area/. Accessed June 20, 2020. Utriainen, 2020, The safety potential of lane keeping assistance and possible actions to improve the potential, IEEE Trans. Intell. Veh., 5, 556, 10.1109/TIV.2020.2991962 Venkatesh, 2000, A theoretical extension of the technology acceptance model: Four longitudinal field studies, Manage. Sci., 46, 186, 10.1287/mnsc.46.2.186.11926 Veterník, 2017, Examining of correlation between demographic development of population and their travel behaviour, Procedia Eng., 192, 929, 10.1016/j.proeng.2017.06.160 Voinescu, 2020, The utility of psychological measures in evaluating perceived usability of automated vehicle interfaces–A study with older adults, Transp. Res. Part F, 72, 244, 10.1016/j.trf.2020.05.003 Wali, 2021, Modeling consumer affinity towards adopting partially and fully automated vehicles-The role of preference heterogeneity at different geographic levels, Transp. Res. Part C, 129, 10.1016/j.trc.2021.103276 Ward, C., Raue, M., Lee, C., D’Ambrosio, L., and Coughlin, J. F., 2017. Acceptance of automated driving across generations: The role of risk and benefit perception, knowledge, and trust. In Kurosu M. (eds) Human-Computer Interaction. User Interface Design, Development and Multimodality. HCI 2017. Lecture Notes in Computer Science, 10271. Springer, Cham. https://doi.org/10.1007/978-3-319-58071-5_20. Winkle, 2016, Safety benefits of automated vehicles: Extended findings from accident research for development, validation and testing, 335 Winston, 2006, An exploration of the offset hypothesis using disaggregate data: The case of airbags and antilock brakes, J. Risk Uncertainty, 32, 83, 10.1007/s11166-006-8288-7 Wooldridge, 1995, Selection corrections for panel data models under conditional mean independence assumptions, J. Econometrics, 68, 115, 10.1016/0304-4076(94)01645-G Wu, 2020, Analysis of consumer attitudes towards autonomous, connected, and electric vehicles: A survey in China, Res. Transport. Economics, 80, 10.1016/j.retrec.2020.100828 Xiao, 2020, Exploring the correlations between spatiotemporal daily activity-travel patterns and stated interest and perception of risk with self-driving cars, AGILE: GIScience Series, 1, 1 Yue, 2020, The practical effectiveness of advanced driver assistance systems at different roadway facilities: System limitation, adoption, and usage, IEEE Trans. Intell. Transp. Syst., 21, 3859, 10.1109/TITS.2019.2935195