Városképi változások és önvezető járművek: a fiatal városlakók öt perszóna típusa Magyarországon
DOI:
https://doi.org/10.32976/stratfuz.2024.25Kulcsszavak:
önvezető jármű, városképi preferenciák, full profile conjoint, szegmentálásAbsztrakt
Egyre több tudományos és gyakorlati forgatókönyv lát napvilágot arról, hogy miképpen hat majd az önvezető járművek (Autonomous Vehicles, AV) tömeges megjelenése a városi közlekedésre és ezen keresztül a városlakók egyéni életére. Egyre többen fogadják el azt a logikát, hogy a saját autó tulajdonlással szembeni önvezetőflotta-használat jelentősen csökkentheti az utakon levő járművek számát is, amelynek fontos területhasználati és városképi következményei lehetnek. Egyre többet tudunk már ezekről a lehetőségekről, ugyanakkor jóval kevesebbet tudunk még arról, hogy mindezt miképpen fogadnák el a városlakók. Ráadásul a városi lakosság preferenciáit vizsgáló kutatások többsége a teljes alapsokaságra fogalmaz meg állításokat, nem pedig annak egyes részeire, így kevés információval rendelkezünk az önvezetőjármű-vezérelt jövőbeni mobilitásnak kimagaslóan kitett fiatalok városképi preferenciáiról.
Tanulmányunk célja annak megismerése, hogy a magyar fiatal városlakók különböző szegmentumai mennyire fogadnák el az önvezető járművek hatására potenciálisan bekövetkező konkrét városképi változásokat. Kutatásunk során a vizuálisan könnyen áttekinthető, a felhasználók számára leginkább vonzó attribútumszint kombinációinak meghatározására alkalmas módszertant alkalmazzuk. Teljes profilú conjoint elemzésünk során 1015 fiatal személyes adatfelvétel során 18 db nyomtatott kártya több lépésben történő értékelésével fejezte ki preferenciáit, melynek eredményeképpen a fiatal városlakók 5 perszóna típusát azonosítottuk: AV fanatikusok, Visszafogott AV szimpatizánsok, Fontolva haladók, Tech ambivalensek és Tech szkeptikus zöldek.
Hivatkozások
G-PPP Automotive Working Group. (2018). A study 5G V2X deployment. 5G PPP. https://5g-ppp.eu/wp-content/uploads/2018/02/5G-PPP-Automotive-WG-White-Paper_Feb.-2018.pdf
Addelman, S. (1962). Orthogonal main-effect plans for asymmetrical factorial experiments. Technometrics, 4(1), 21–46. https://doi.org/10.1080/00401706.1962.10489985
Alam, M. J., & Habib, M. A. (2018). Investigation of the impacts of shared autonomous vehicle operation in Halifax, Canada, using a dynamic traffic microsimulation model. Procedia Computer Science, 130, 496–503. https://doi.org/10.1016/j.procs.2018.04.066
Alazzawi, S., Hummel, M., Kordt, P., Sickenberger, T., Wieseotte, C., & Wohak, O. (2018). Simulating the impact of shared, autonomous vehicles on urban mobility: A case study of Milan. In E. Wießner, L. Lücken, R. Hilbrich, Y.-P. Flötteröd, J. Erdmann, L. Bieker-Walz, & M. Behrisch (Eds.), SUMO 2018 – Simulating Autonomous and Intermodal Transport Systems (pp. 94–110). https://doi.org/10.29007/2n4h
Alfonso, J., Naranjo, J. E., Menéndez, J. M., & Alonso, A. (2018). Vehicular communications. In Intelligent Vehicles (pp. 103–139). Elsevier. https://doi.org/10.1016/B978-0-12-812800-8.00003-5
Atzori, L., Floris, A., Girau, R., Nitti, M., & Pau, G. (2018). Towards the implementation of the social Internet of vehicles. Computer Networks, 147, 132–145. https://doi.org/10.1016/j.comnet.2018.10.001
Bateman, I. J., Day, B. H., Jones, A. P., & Jude, S. (2009). Reducing gain–loss asymmetry: A virtual reality choice experiment valuing land use change. Journal of Environmental Economics and Management, 58(1), 106–118. https://doi.org/10.1016/j.jeem.2008.05.003
Baccarella, C. V., Wagner, T. F., Scheiner, C. W., Maier, L., & Voigt, K.-I. (2020). Investigating consumer acceptance of autonomous technologies: The case of self-driving automobiles. European Journal of Innovation Management, 24(4), 1210–1323. https://doi.org/10.1108/EJIM-09-2019-0245
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. https://doi.org/10.1016/j.trc.2016.01.019
Bayart, C., Havet, N., Bonnel, P., & Bouzouina, L. (2020). Young people and the private car: A love-hate relationship. Transportation Research Part D: Transport and Environment, 80, 102235. https://doi.org/10.1016/j.trd.2020.102235
Bazilinskyy, P., Kyriakidis, M., Dodou, D., & de Winter, J. (2019). When will most cars be able to drive fully automatically? Projections of 18,970 survey respondents. Transportation Research Part F: Traffic Psychology and Behaviour, 64, 184–195. https://doi.org/10.1016/j.trf.2019.05.008
Bezai, N. E., Medjdoub, B., Al-Habaibeh, A., Chalal, M. L., & Fadli, F. (2021). Future cities and autonomous vehicles: Analysis of the barriers to full adoption. Energy and Built Environment, 2(1), 65–81. https://doi.org/10.1016/j.enbenv.2020.05.002
Brovarone, E. V., Scudellari, J., & Staricco, L. (2021). Planning the transition to autonomous driving: A policy pathway towards urban liveability. Cities, 108, 102996. https://doi.org/10.1016/j.cities.2020.102996
Buckley, L., Kaye, S.-A., & Pradhan, A. K. (2018). Psychosocial factors associated with intended use of automated vehicles: A simulated driving study. Accident Analysis & Prevention, 115, 202–208. https://doi.org/10.1016/j.aap.2018.03.021
Cai, L., Yuen, K. F., & Wang, X. (2023). Public acceptance of autonomous buses: An integrated model of UTAUT, TTF, and trust. Travel Behaviour and Society, 31, 120–130. https://doi.org/10.1016/j.tbs.2022.11.010
Chapin, T., Stevens, L., Crute, J., Crandall, J., Rokyta, A., & Washington, A. (2016). Envisioning Florida’s future: Transportation and land use in an automated vehicle world. Florida State University Department of Urban & Regional Planning.
Chen, C.-F. (2019). Factors affecting the decision to use autonomous shuttle services: Evidence from a scooter-dominant urban context. Transportation Research Part F, 67, 195–204. https://doi.org/10.1016/j.trf.2019.10.016
Chen, H.-K., & Yan, D.-W. (2019). Interrelationships between influential factors and behavioral intention with regard to autonomous vehicles. International Journal of Sustainable Transportation, 13(7), 511–527. https://doi.org/10.1080/15568318.2018.1488021
Cho, Y., Park, J., Park, S., & Jung, E. S. (2017). Technology acceptance modeling based on user experience for autonomous vehicles. Journal of the Ergonomics Society of Korea, 36(2), 87–108.
Choi, S., & Mokhtarian, P. L. (2020). How attractive is it to use the internet while commuting? A work-attitude-based segmentation of Northern California commuters. Transportation Research Part A, 138, 37–50. https://doi.org/10.1016/j.tra.2020.05.007
Choi, J. K., & Ji, Y. G. (2015). Investigating the importance of trust on adopting an autonomous vehicle. International Journal of Human-Computer Interaction, 31(10), 692–702. https://doi.org/10.1080/10447318.2015.1070549
Cohen, T., Stilgoe, J., Stares, S., Akyelken, N., Cavoli, C., Day, J., Dickinson, J., Fors, V., Hopkins, D., Lyons, G., Marres, N., Newman, J., Reardon, L., Sipe, N., Tennant, C., Wadud, Z., & Wigley, E. (2020). A constructive role for social science in the development of automated vehicles. Transportation Research Interdisciplinary Perspectives, 6, 100133. https://doi.org/10.1016/j.trip.2020.100133
Dai, J., Wang, X. C., Ma, W., & Li, R. (2023). Future transport vision propensity segments: A latent class analysis of autonomous taxi market. Transportation Research Part A, 173, 103699. https://doi.org/10.1016/j.tra.2023.103699
Delbosc, A. (2017). Delay or forgo? A closer look at youth driver licensing trends in the United States and Australia. Transportation, 44(5), 919–926. https://doi.org/10.1007/s11116-016-9685-7
Dong, X., DiScenna, M., & Guerra, E. (2017). Transit user perceptions of driverless buses. Transportation, 1-16. https://doi.org/10.1007/s11116-017-9786-y
DuPuis, N., Cooper, M., & Brooks, R. (2015). City of the future: Technology & mobility. National League of Cities, Center for City Solutions and Applied Research.
Elia, G., et al. (2019). Connected transports, V2X and 5G: Standard, services and the TIM - Telecom Italia experiences. AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE), Turin, Italy, 2019, 1–6. https://doi.org/10.23919/EETA.2019.8804510
Ellis, K., Lyon-Hill, S., Tilashalski, M., & Travis, E. (2020). Measuring the effects of drone delivery in the United States. VTechWorks. https://vtechworks.lib.vt.edu/bitstream/handle/10919/100104/Effects%20of%20Drone%20Delivery%20US_September%202020.pdf
Engelhardt, M. (2023). Who is willing-to-pay for sustainable last mile innovations? Transportation Research Procedia, 69, 910–917. https://doi.org/10.1016/j.trpro.2023.02.252
ERTRAC. (2019). Connected automated driving roadmap. ERTRAC Working Group "Connectivity and Automated Driving." https://www.ertrac.org/wp-content/uploads/2022/07/ERTRAC-CAD-Roadmap-2019.pdf
Fayyaz, M., González-González, E., & Nogués, S. (2022). Autonomous vehicles in sustainable cities: Re-claiming public spaces for people. SUPTM 2022 Conference Proceedings. https://doi.org/10.31428/xxxxx
Figliozzi, M. A. (2020). Carbon emissions reductions in last mile and grocery deliveries utilizing air and ground autonomous vehicles. Transportation Research Part D, 85, 102443. https://doi.org/10.1016/j.trd.2020.102443
Figliozzi, M. A., & Jennings, D. (2020). Autonomous delivery robots and their potential impacts on urban freight energy consumption and emissions. Transportation Research Procedia, 46, 21–28. https://doi.org/10.1016/j.trpro.2020.03.159
Foroughi, B., Nhan, P. V., Iranmanesh, M., Ghobakhloo, M., Nilashi, M., & Yadegaridehkordi, E. (2023). Determinants of intention to use autonomous vehicles: Findings from PLS-SEM and ANFIS. Journal of Retailing and Consumer Services, 70, 103158. https://doi.org/10.1016/j.jretconser.2022.103158
Fagnant, D. J., & Kockelman, K. M. (2016). Dynamic ride-sharing and fleet sizing for a system of shared autonomous vehicles in Austin, Texas. Transportation, 45, 143–158. https://doi.org/10.1007/s11116-016-9729-z
Fraedrich, E., Heinrichs, D., Bahamonde-Birke, F. J., & Cyganski, R. (2019). Autonomous driving, the built environment and policy implications. Transportation Research Part A: Policy and Practice, 122, 162–172. https://doi.org/10.1016/j.tra.2018.02.018
Groth, S., & Kuhnimhof, T. (2021). Multimodality in transportation. In R. Vickerman (Ed.), International Encyclopedia of Transportation (Vol. 5, pp. 118–126). Elsevier Ltd. https://doi.org/10.1016/B978-0-08-102671-7.10414-2
Grindsted, T. S., Christensen, T. H., Freudendal-Pedersen, M., Friis, F., & Hartmann-Petersen, K. (2022). The urban governance of autonomous vehicles – In love with AVs or critical sustainability risks to future mobility transitions? Cities, 120, 103504. https://doi.org/10.1016/j.cities.2021.103504
Hakak, S., Gadekallu, T. R., Maddikunta, T. K. R., Ramu, S. P., De Alwis, P. M. C., & Liyanage, M. (2023). Autonomous vehicles in 5G and beyond: A survey. Vehicular Communications, 39, 100551. https://doi.org/10.1016/j.vehcom.2022.100551
Hakeem, S. A., Hady, A. A., & Kim, H. (2020). 5G-V2X: Standardization, architecture, use cases, network-slicing, and edge-computing. Wireless Networks, 26, 6015–6041. https://link.springer.com/article/10.1007/s11276-020-02419-8
Hardman, S., Berliner, R., & Tal, G. (2019). Who will be the early adopters of automated vehicles? Insights from a survey of electric vehicle owners in the United States. Transportation Research Part D: Transport and Environment, 71, 248–264. https://doi.org/10.1016/j.trd.2018.12.001
Hegner, S. M., Beldad, A. D., & Brunswick, G. J. (2019). In automatic we trust: Investigating the impact of trust, control, personality characteristics, and extrinsic and intrinsic motivations on the acceptance of autonomous vehicles. International Journal of Human-Computer Interaction, 35(19), 1769–1780. https://doi.org/10.1080/10447318.2019.1572353
Herrenkind, B., Brendel, A. B., Nastjuk, I., Greve, M., & Kolbe, L. M. (2019). Investigating end-user acceptance of autonomous electric buses to accelerate diffusion. Transportation Research Part D: Transport and Environment, 74, 255–276. https://doi.org/10.1016/j.trd.2019.08.003
Herrenkind, B., Nastjuk, I., Brendel, A. B., Trang, S., & Kolbe, L. M. (2019b). Young people’s travel behavior – Using the life-oriented approach to understand the acceptance of autonomous driving. Transportation Research Part D: Transport and Environment, 74, 214–233. https://doi.org/10.1016/j.trd.2019.07.023
Hjorthol, R. (2016). Decreasing popularity of the car? Changes in driving licence and access to a car among young adults over a 25-year period in Norway. Journal of Transport Geography, 51, 140–146. https://doi.org/10.1016/j.jtrangeo.2015.12.006
Huang, G., Hung, Y.-H., Proctor, R. W., & Pitts, B. J. (2022). Age is more than just a number: The relationship among age, non-chronological age factors, self-perceived driving abilities, and autonomous vehicle acceptance. Accident Analysis and Prevention, 178, 106850. https://doi.org/10.1016/j.aap.2022.106850
Hudson, J., Orviska, A., & Hunady, J. (2019). People’s attitudes to autonomous vehicles. Transportation Research Part A: Policy and Practice, 121, 164–176. https://doi.org/10.1016/j.tra.2018.08.018
Janatabadi, F., & Ermagun, A. (2022). Empirical evidence of bias in public acceptance of autonomous vehicles. Transportation Research Part F: Traffic Psychology and Behaviour, 84, 330–347. https://doi.org/10.1016/j.trf.2021.12.005
Jiang, L., Chen, H., & Chen, Z. (2022). City readiness for connected and autonomous vehicles: A multi-stakeholder and multi-criteria analysis through analytic hierarchy process. Transport Policy, 128, 13–24. https://doi.org/10.1016/j.tranpol.2022.09.012
Johnson, C. (2017). Readiness of the road network for connected and autonomous vehicles. RAC Foundation - Royal Automobile Club for Motoring Ltd., London.
Kapser, S., & Abdelrahman, M. (2020). Acceptance of autonomous delivery vehicles for last-mile delivery in Germany – Extending UTAUT2 with risk perceptions. Transportation Research Part C: Emerging Technologies, 111, 210–225. https://doi.org/10.1016/j.trc.2019.12.016
Katoshevski, R., & Timmermans, H. (2001). Using conjoint analysis to formulate user-centred guidelines for urban design: The example of new residential development in Israel. Journal of Urban Design, 6(1), 37–53. https://doi.org/10.1080/13574800120032888
Kaye, S.-A., Nandavar, S., Yasmin, S., Lewis, I., & Oviedo-Trespalacios, O. (2022). Consumer knowledge and acceptance of advanced driver assistance systems. Transportation Research Part F: Traffic Psychology and Behaviour, 90, 300–311. https://doi.org/10.1016/j.trf.2022.09.004
Keszey, T. (2020). Behavioural intention to use autonomous vehicles: Systematic review and empirical extension. Transportation Research Part C: Emerging Technologies, 119, 1–16. https://doi.org/10.1016/j.trc.2020.10273
Koul, S., & Eydgahi, A. (2018). Utilizing technology acceptance model (TAM) for driverless car technology adoption. Journal of Technology Management and Innovation, 13(4), 37–46. https://doi.org/10.4067/S0718-27242018000400037
Kovács, P., & Lukovics, M. (2022). Factors influencing public acceptance of self-driving vehicles in a post-socialist environment: Statistical modelling in Hungary. Regional Statistics, 12(2), 149–176. https://doi.org/10.15196/RS120206
Lavieri, P. S., Garikapati, V. M., Bhat, C. R., Pendyala, R. M., Astroza, S., & Dias, F. F. (2017). Modeling individual preferences for ownership and sharing of autonomous vehicle technologies. Transportation Research Record: Journal of the Transportation Research Board, 2665, 1–10. https://doi.org/10.3141/2665-01
Lee, J., Lee, D., Park, Y., Lee, S., & Ha, T. (2019). Autonomous vehicles can be shared, but a feeling of ownership is important: Examination of the influential factors for intention to use autonomous vehicles. Transportation Research Part C: Emerging Technologies, 107, 411–422. https://doi.org/10.1016/j.trc.2019.08.020
Lengyel, H., Tettamanti, T., & Szalay, Z. (2020). Conflicts of automated driving with conventional traffic infrastructure. IEEE Access, 8, 163280–163297. https://doi.org/10.1109/ACCESS.2020.3020653
Liao, B., van den Berg, P. E. W., van Wesemael, P. J. V., & Arentze, T. A. (2022). Individuals' perception of walkability: Results of a conjoint experiment using videos of virtual environments. Cities, 125, 103650. https://doi.org/10.1016/j.cities.2022.103650
Liljamo, T., Liimatainen, H., Pöllänen, M., & Viri, R. (2021). The effects of Mobility as a Service and autonomous vehicles on people’s willingness to own a car in the future. Sustainability, 13(4), 1962. https://doi.org/10.3390/su13041962
Lipson, H., & Kurman, M. (2016). Driverless: Intelligent cars and the road ahead. MIT Press.
Liu, Y., Tight, M., Sun, Q., & Kang, R. (2019). A systematic review: Road infrastructure requirement for connected and autonomous vehicles (CAVs). Journal of Physics: Conference Series, 1187, 042073. https://doi.org/10.1088/1742-6596/1187/4/042073
Litman, T. (2017). Autonomous vehicle implementation predictions: Implications for transport planning. Victoria Transport Policy Institute.
Louviere, J. J., Flynn, T. N., & Carson, R. T. (2010). Discrete choice experiments are not conjoint analysis. Journal of Choice Modelling, 3(3), 57–72. https://doi.org/10.1016/S1755-5345(13)70014-9
Luce, R. D., & Tuckey, J. W. (1964). Simultaneous conjoint measurement: A new type of fundamental measurement. Journal of Mathematical Psychology, 1, 1–27. https://doi.org/10.1016/0022-2496(64)90015-X
Lukovics, M., Prónay, Sz., Majó-Petri, Z., Kovács, P., Ujházi, T., Volosin, M., Palatinus, Zs., & Keszey, T. (2023). Combining survey-based and neuroscience measurements in customer acceptance of self-driving technology. Transportation Research Part F: Traffic Psychology and Behaviour, 95, 46–58. https://doi.org/10.1016/j.trf.2023.03.016
Madigan, R., Louw, T., Wilbrink, M., Schieben, A., & Merat, N. (2017). What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems. Transportation Research Part F: Traffic Psychology and Behaviour, 50, 55–64. https://doi.org/10.1016/j.trf.2017.07.007
Maltese, I., & Zamparini, L. (2023). Sustainable mobility choices at home and within destinations: A survey of young Italian tourists. Research in Transportation Business & Management, 100906. https://doi.org/10.1016/j.rtbm.2022.100906
Marcheschi, E., Vogel, N., Larsson, A., Perander, S., & Koglin, T. (2022). Residents’ acceptance towards car-free street experiments: Focus on perceived quality of life and neighborhood attachment. Transportation Research Interdisciplinary Perspectives, 100585. https://doi.org/10.1016/j.trip.2022.100585
Martinez, L. M., & Viegas, J. M. (2017). Assessing the impacts of deploying a shared self-driving urban mobility system: An agent-based model applied to the city of Lisbon, Portugal. International Journal of Transportation Science and Technology, 6(1), 13–27. https://doi.org/10.1016/j.ijtst.2017.05.005
Mathews, K. E., Freeman, M. L., & Desvousges, W. H. (2006). How and how much? The role of information in stated choice questionnaires. In J. R. Bennett & R. K. Blamey (Eds.), Valuing environmental amenities using stated choice studies: A common sense approach to theory and practice (pp. 111–133). Springer. https://doi.org/10.1007/1-4020-5313-4_5
McKinsey & Company. (2016). Automotive revolution – Perspective towards 2030: How the convergence of disruptive technology-driven trends could transform the auto industry (Advanced Industries). Stuttgart: McKinsey & Company.
Menon, N., Barbour, N., Zhang, Y., Pinjari, A. R., & Mannering, F. (2018). Shared autonomous vehicles and their potential impacts on household vehicle ownership: An exploratory empirical assessment. International Journal of Sustainable Transportation, 12(2), 1–15. https://doi.org/10.1080/15568318.2018.1443178
Milakis, D., Snelder, M., van Arem, B., van Wee, G. P., & 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 and Infrastructure Research, 17(1), 63–85. https://doi.org/10.18757/ejtir.2017.17.1.3180
Mokhtarian, P. L., Ory, D. T., & Cao, X. (2009). Shopping-related attitudes: A factor and cluster analysis of Northern California shoppers. Environment and Planning B: Planning and Design, 36, 204–228. https://doi.org/10.1068/b34015t
Moorthy, A., De Kleine, R., Keoleian, G., Good, J., & Lewis, G. (2017). Shared autonomous vehicles as a sustainable solution to the last mile problem: A case study of Ann Arbor-Detroit area. SAE International Journal of Passenger Cars - Electronic and Electrical Systems, 10(1), 328–336. https://doi.org/10.4271/2017-01-1276
Moták, L., Neuville, E., Chambres, P., Marmoiton, F., Monéger, F., Coutarel, F., & Izaute, M. (2017). Antecedent variables of intentions to use an autonomous shuttle: Moving beyond TAM and TPB? European Review of Applied Psychology, 67(5), 269–278. https://doi.org/10.1016/j.erap.2017.06.001
Muraleetharan, B., Adachi, T., Uchida, K., Hagiwara, T., & Kagaya, S. (2003). A study on evaluation of pedestrian level of service along sidewalks and at intersections using conjoint analysis. Infrastructure Planning Review, 21, 727-736. https://doi.org/10.2208/journalip.21.727
NACTO. (2019). Blueprint for Autonomous Urbanism (2nd ed.). National Association of City Transportation Officials.
Narayanan, S., Chaniotakis, E., & Antoniou, C. (2020). Shared autonomous vehicle services: A comprehensive review. Transportation Research Part C: Emerging Technologies, 111, 255–293. https://doi.org/10.1016/j.trc.2019.12.008
Nielsen, T. A. S., & Haustein, S. (2018). On sceptics and enthusiasts: What are the expectations towards self-driving cars? Transport Policy, 66, 49–55. https://doi.org/10.1016/j.tranpol.2018.03.004
Nieuwenhuijsen, J., de Almeida Correia, G. H., Milakis, D., van Arem, B., & van Daalen, E. (2018). Towards a quantitative method to analyze the long-term innovation diffusion of automated vehicles technology using system dynamics. Transportation Research Part C: Emerging Technologies, 86, 300–327. https://doi.org/10.1016/j.trc.2017.11.016
Overtoom, I., Correia, G., Huang, Y., & Verbraeck, A. (2020). Assessing the impacts of shared autonomous vehicles on congestion and curb use: A traffic simulation study in the Hague, Netherlands. International Journal of Transportation Science and Technology, 9(3), 195–206. https://doi.org/10.1016/j.ijtst.2020.03.009
Panagiotopoulos, I., & Dimitrakopoulos, G. (2018). An empirical investigation on consumers’ intentions towards autonomous driving. Transportation Research Part C: Emerging Technologies, 95, 773–784. https://doi.org/10.1016/j.trc.2018.08.013
Paine, G. (2019). Drones to deliver incessant buzzing noise, and packages. The Conversation. Retrieved from https://theconversation.com/drones-to-deliver-incessant-buzzing-noise-and-packages-116257
Payre, W., Cestac, J., & Delhomme, P. (2014). Intention to use a fully automated car: Attitudes and a priori acceptability. Transportation Research Part F: Traffic Psychology and Behaviour, 27(B), 252–263. https://doi.org/10.1016/j.trf.2014.04.009
Pettigrew, S., Dana, L. M., & Norman, R. (2019). Clusters of potential autonomous vehicle users according to propensity to use individual versus shared vehicles. Transport Policy, 76, 13–20. https://doi.org/10.1016/j.tranpol.2019.01.010
Phillips, A., da Schio, N., Canters, F., & Khan, A. Z. (2023). “A living street and not just green”: Exploring public preferences and concerns regarding nature-based solution implementation in urban streetscapes. Urban Forestry & Urban Greening, 86, 128034. https://doi.org/10.1016/j.ufug.2023.128034
PIARC. (2021). Automated vehicles: Challenges and opportunities for road operators and road authorities. World Road Association (PIARC).
Prónay, Sz., Lukovics, M., Kovács, P., Majó-Petri, Z., Ujházi, T., Palatinus, Zs., & Volosin, M. (2022). Pánik próbája a mérés – avagy önvezető technológiák elfogadásának valós idejű vizsgálata neurotudományi mérésekkel. Vezetéstudomány, 53(7), 48–62. https://doi.org/10.14267/VEZTUD.2022.07.05
Rahimi, A., Azimi, G., Asgari, H., & Jin, X. (2020). Adoption and willingness to pay for autonomous vehicles: Attitudes and latent classes. Transportation Research Part D: Transport and Environment, 89, 102611. https://doi.org/10.1016/j.trd.2020.102611
Rahman, M., & Thill, J.-C. (2023). Impacts of connected and autonomous vehicles on urban transportation and environment: A comprehensive review. Sustainable Cities and Society, 96, 104649. https://doi.org/10.1016/j.scs.2023.104649
Rasheed, I. (2022). Dynamic mode selection and resource allocation approach for 5G-vehicle-to-everything (V2X) communication using asynchronous federated deep reinforcement learning method. Vehicular Communications, 38, 100532. https://doi.org/10.1016/j.vehcom.2022.100532
Ravi, B., Kumar, M., Hu, Y.-C., Hassan, S., & Kumar, B. (2023). Stochastic modeling and performance analysis in balancing load and traffic for vehicular ad hoc networks: A review. International Journal of Network Management, 1–22. https://doi.org/10.1002/nem.2224
Robertson, R. D., Woods-Fry, H., & Hing, M. M. (2019). Automated vehicles and older drivers in Canada. Journal of Safety Research, 70, 193-199. https://doi.org/10.1016/j.jsr.2019.07.003
Richter, M. A., Hagenmaier, M., Bandte, O., Parida, V., & Wincent, J. (2022). Smart cities, urban mobility and autonomous vehicles: How different cities need different sustainable investment strategies. Technological Forecasting and Social Change, 184, 121857. https://doi.org/10.1016/j.techfore.2022.121857
Riggs, W., Appleyard, B., & Johnson, M. (2020). A design framework for livable streets in the era of autonomous vehicles. Urban Planning and Transport Research, 8(1), 125–137. https://doi.org/10.1080/21650020.2020.1749123
Schoettle, B., & Sivak, M. (2014). A survey of public opinion about autonomous and self-driving vehicles in the US, the UK, and Australia. Tech. Rep. https://doi.org/10.1109/ICCVE.2014.7297637
Sener, I. N., & Zmud, J. (2019). Chipping away at uncertainty: Intent to use self-driving vehicles and the role of ride-hailing. Transportation Planning and Technology, 42(7), 645–661. https://doi.org/10.1080/03081060.2019.1650423
Shabanpour, R., Golshani, N., Shamshiripour, A., & Mohammadian, A. (Kouros). (2018). Eliciting preferences for adoption of fully automated vehicles using best-worst analysis. Transportation Research Part C: Emerging Technologies, 93, 463–478. https://doi.org/10.1016/j.trc.2018.06.014
Shr, Y. H., Ready, R., Orland, B., & Echols, S. (2019). How do visual representations influence survey responses? Evidence from a choice experiment on landscape attributes of green infrastructure. Ecological Economics, 156, 375–386. https://doi.org/10.1016/j.ecolecon.2018.10.015
Silva, D., Földes, D., & Csiszár, C. (2021). Autonomous vehicle use and urban space transformation: A scenario building and analyzing method. Sustainability, 13(6), 3008. https://doi.org/10.3390/su13063008
Smahó, M. (2021). Autonóm járművek a jövő városában. In Z. Csizmadia & J. Rechnitzer (Eds.), Az önvezető járművek világa: Társadalmi hatások és kihívások. Budapest: Akadémiai Kiadó.
Smeds, E., & Papa, E. (2023). The value of street experiments for mobility and public life: Citizens’ perspectives from three European cities. Journal of Urban Mobility, 4, 100055. https://doi.org/10.1016/j.urbmob.2023.100055
Solecka, I., Krajewski, P., Krzyzanek, A., & Garczynska, A. (2022). Citizens’ perceptions of landscape changes and their driving forces: Evidence from Poland. International Journal of Environmental Research and Public Health, 19(3), 1688. https://doi.org/10.3390/ijerph19031688
Soto, J. J., Cantillo, V., & Arellana, J. (2021). Market segmentation for incentivising sustainable transport policies. Transportation Research Part D: Transport and Environment, 99, 103013. https://doi.org/10.1016/j.trd.2021.103013
Spurling, N., & McMeekin, A. (2014). Interventions in practices: Sustainable mobility policies in England. In Y. Strengers & C. Maller (Eds.), Social practices, intervention and sustainability (pp. XX-XX). London: Routledge.
Stead, D., & Vaddadi, B. (2019). Automated vehicles and how they may affect urban form: A review of recent scenario studies. Cities, 92, 125–133. https://doi.org/10.1016/j.cities.2019.03.020
Storck, C. R., & Duarte-Figueiredo, F. (2020). A survey of 5G technology evolution, standards, and infrastructure associated with vehicle-to-everything communications by Internet of Vehicles. IEEE Access, 8, 117593–117614. https://doi.org/10.1109/ACCESS.2020.3004779
Straub, E. R., & Schaefer, K. E. (2019). It takes two to tango: Automated vehicles and human beings do the dance of driving – Four social considerations for policy. Transportation Research Part A: Policy and Practice, 122, 173–183. https://doi.org/10.1016/j.tra.2018.03.005
Su, Y.-S., Huang, H., Daim, T., Chien, P.-W., Peng, R.-L., & Akgul, A. K. (2023). Assessing the technological trajectory of 5G-V2X autonomous driving inventions: Use of patent analysis. Technological Forecasting and Social Change, 196, 122817. https://doi.org/10.1016/j.techfore.2023.122817
Tengilimoglu, O., Carsten, O., & Wadud, Z. (2023). Implications of automated vehicles for physical road environment: A comprehensive review. Transportation Research Part E: Logistics and Transportation Review, 169, 102989. https://doi.org/10.1016/j.tre.2022.102989
Threlfall, R. (2018). Autonomous vehicles readiness index. Klynveld Peat Marwick Goerdeler (KPMG) International.
Tilt, J. H. (2010). Walking trips to parks: Exploring demographic, environmental factors, and preferences for adults with children in the household. Preventive Medicine, 50(Suppl.), S69–S73. https://doi.org/10.1016/j.ypmed.2009.07.026
Ujházi, T. (2023). Önvezető járművekhez kapcsolódó fogyasztói preferenciák vizsgálata. Marketing & Menedzsment, 57(EMOK 2), 65–73. https://doi.org/10.15170/MM.2023.57.KSZ.02.07
USCB. (2020). Quarterly e-commerce report 1st quarter 2020. U.S. Census Bureau News. U.S. Department of Commerce, Washington, D.C., 1–3.
Van Cauwenberg, J., Van Holle, V., De Bourdeaudhuij, I., Clarys, P., Nasar, J., Salmon, J., et al. (2014). Using manipulated photographs to identify features of streetscapes that may encourage older adults to walk for transport. PLoS ONE, 9(11), e112107. https://doi.org/10.1371/journal.pone.0112107
Van Cauwenberg, J., De Bourdeaudhuij, I., Clarys, P., et al. (2016). Street characteristics preferred for transportation walking among older adults: A choice-based conjoint analysis with manipulated photographs. International Journal of Behavioral Nutrition and Physical Activity, 13(6). https://doi.org/10.1186/s12966-016-0331-8
Vasilev, M., Pritchard, R., & Jonsson, T. (2022). Mixed-methods approach to studying multiuser perceptions of an interim Complete Streets project in Norway. Travel Behaviour and Society, 29, 12–21. https://doi.org/10.1016/j.tbs.2022.05.002
Veitch, J., Salmon, J., Deforche, B., Ghekiere, A., Van Cauwenberg, J., Bangay, S., & Timperio, A. (2017). Park attributes that encourage park visitation among adolescents: A conjoint analysis. Landscape and Urban Planning, 161, 52–58. https://doi.org/10.1016/j.landurbplan.2016.12.004
Verhoeven, H., Ghekiere, A., Van Cauwenberg, J., Van Dyck, D., De Bourdeaudhuij, I., Clarys, P., & Deforche, B. (2017). Which physical and social environmental factors are most important for adolescents' cycling for transport? An experimental study using manipulated photographs. International Journal of Behavioral Nutrition and Physical Activity, 14(1), 108. https://doi.org/10.1186/s12966-017-0566-z
Verma, M., Manoj, M., & Verma, A. (2016). Analysis of the influences of attitudinal factors on car ownership decisions among urban young adults in a developing country like India. Transportation Research Part F: Traffic Psychology and Behaviour, 42, 90–103. https://doi.org/10.1016/j.trf.2016.06.024
Wang, J., Shao, Y., Ge, Y., & Yu, R. (2019). A survey of vehicle-to-everything (V2X) testing. Sensors, 19(2), 334. https://doi.org/10.3390/s19020334
Wang, N., Tian, H., Zhou, S., & Li, Y. (2022). Analysis of public acceptance of electric vehicle charging scheduling based on the technology acceptance model. Energy, 258, 124804. https://doi.org/10.1016/j.energy.2022.124804
Wu, J., Liao, H., Wang, J. W., & Chen, T. (2019). The role of environmental concern in the public acceptance of autonomous electric vehicles: A survey from China. Transportation Research Part F: Traffic Psychology and Behaviour, 60, 37–46. https://doi.org/10.1016/j.trf.2018.09.029
Yigitcanlar, T., Wilson, M., & Kamruzzaman, M. (2019). Disruptive impacts of automated driving systems on the built environment and land use: An urban planner’s perspective. Journal of Open Innovation: Technology, Market, and Complexity, 5(2), 24. https://doi.org/10.3390/joitmc5020024
Young, F. W. (1969). Polynomial conjoint analysis of similarities: A model for constructing polynomial conjoint measurement algorithms. North Carolina University. https://doi.org/10.1037/e599692010-001
Xing, Y., Han, X., Zhang, H. M., Lu, J., & Gao, Z. Y. (2022). Do bicyclists and pedestrians support their city as an autonomous vehicle proving ground? Evidence from Pittsburgh. Case Studies on Transport Policy, 10(4), 2401–2412. https://doi.org/10.1016/j.cstp.2022.10.015
Zhao, Y., & Kockelman, K. M. (2018). Anticipating the regional impacts of connected and automated vehicle travel in Austin, Texas. Journal of Urban Planning and Development, 144(4), 04018032. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000463
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(1), 7–13. https://doi.org/10.3141/2565-07
Zuti, B., & Lukovics, M. (2023). Az önvezető járművek elfogadása viselkedés-gazdaságtani szemléletben: A nudge szerepe a fenntartható városi mobilitás kialakításában. Közgazdasági Szemle, 60(február), 149–166. https://doi.org/10.18414/KSZ.2023.2.149
##submission.downloads##
Megjelent
Hogyan kell idézni
Folyóirat szám
Rovat
License
Copyright (c) 2024 Miklós Lukovics, Tamás Ujházi
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
