Development and transport implications of automated vehicles in the Netherlands: scenarios for 2030 and 2050
Open accessAbstract
Automated driving technology is emerging. Yet, little is known in the literature about when automated vehicles will reach the market, how penetration rates will evolve and to what extent this new transport technology will affect transport demand and planning. This study uses scenario analysis to identify plausible future development paths of automated vehicles in the Netherlands and to estimate potential implications for traffic, travel behaviour and transport planning on a time horizon up to 2030 and 2050. The scenario analysis was performed through a series of three workshops engaging a group of diverse experts. Sixteen key factors and five driving forces behind them were identified as critical in determining future development of automated vehicles in the Netherlands. Four scenarios were constructed assuming combinations of high or low technological development and restrictive or supportive policies for automated vehicles (AV …in standby, AV …in bloom, AV …in demand, AV …in doubt). According to the scenarios, fully automated vehicles are expected to be commercially available between 2025 and 2045, and to penetrate the market rapidly after their introduction. Penetration rates are expected to vary among different scenarios between 1% and 11% (mainly conditionally automated vehicles) in 2030 and between 7% and 61% (mainly fully automated vehicles) in 2050. Complexity of the urban environment and unexpected incidents may influence development path of automated vehicles. Certain implications on mobility are expected in all scenarios, although there is great variation in the impacts among the scenarios. Measures to curb growth of travel and subsequent externalities are expected in three out of the four scenarios.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Scenario planning: a tool for strategic thinking
(1995) · Long Range Planning · doi:10.1016/0024-6301(95)91604-0 · Cited by 1,554 · see citing works
The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics
van Arem, B., van Driel, C. J. G., & Visser, R. (2006) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2006.884615 · Cited by 1,516 · see citing works
Self-citationKyriakidis, M., Happee, R., & de Winter, J. C. F. (2015) · Transportation Research Part F: Traffic Psychology and Behaviour · doi:10.1016/j.trf.2015.04.014 · Cited by 1,383 · see citing works
Scenario Planning: a Tool for Conservation in an Uncertain World
Peterson, G., Cumming, G. S., & Carpenter, S. R. (2003) · Conservation Biology · doi:10.1046/j.1523-1739.2003.01491.x · Cited by 1,382 · see citing works
The origins and evolution of scenario techniques in long range business planning
Bradfield, R., Wright, G., Burt, G., Cairns, G., & Van Der Heijden, K. (2005) · Futures · doi:10.1016/j.futures.2005.01.003 · Cited by 1,204 · see citing works
Fagnant, D. J., & Kockelman, K. M. (2014) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2013.12.001 · Cited by 1,177 · see citing works
The Art of the Long View: Planning for the Future in an Uncertain World
Schwartz, P. (1996) · Cited by 1,164 · see citing works
Amer, M., Daim, T. U., & Jetter, A. J. M. (2012) · Futures · doi:10.1016/j.futures.2012.10.003 · Cited by 1,024 · see citing works
Impacts of cooperative adaptive cruise control on freeway traffic flow
Shladover, S. E., Su, D., & Lu, X.-Y. (2012) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.3141/2324-08 · Cited by 887 · see citing works
(2015) · Transportation Research Board 94th Annual MeetingTransportation Research Board · Cited by 854 · see citing works
The current state of scenario development: an overview of techniques
Bishop, P. C., Hines, A., & Collins, T. (2007) · foresight · doi:10.1108/14636680710727516 · Cited by 815 · see citing works
Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems
On-Road Automated Driving (ORAD) Committee (2017) · doi:10.4271/j3016_201401 · Cited by 675 · see citing works
Autonomous Vehicle Technology: A Guide for Policymakers
Anderson, J., Kalra, N., Stanley, K., Sorensen, P., Samaras, C., & Oluwatola, O. (2016) · doi:10.7249/rr443-2 · Cited by 653 · see citing works
A formal framework for scenario development in support of environmental decision-making
Mahmoud, M. I., Liu, Y., Hartmann, H. C., Stewart, S. A., Wagener, T., Semmens, D. J., Stewart, R., Gupta, H. V., Dominguez, D., Domínguez, F., et al. (2009) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2008.11.010 · Cited by 380 · see citing works
Effects of Adaptive Cruise Control Systems on Highway Traffic Flow Capacity
Werf, J. V., Shladover, S. E., Miller, M. A., & Kourjanskaia, N. (2002) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/1800-10 · Cited by 267 · see citing works
An experimental comparative study of autonomous and co-operative vehicle-follower control systems
Rajamani, R., & Shladover, S. E. (2001) · Transportation Research Part C Emerging Technologies · doi:10.1016/s0968-090x(00)00021-8 · Cited by 251 · see citing works
Does the intuitive logics method – and its recent enhancements – produce “effective” scenarios?
Wright, G., Bradfield, R., & Cairns, G. M. (2012) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2012.09.003 · Cited by 208 · see citing works
Correia, G. H. D. A., & van Arem, B. (2016) · Transportation Research Part B Methodological · doi:10.1016/j.trb.2016.03.002 · Cited by 171 · see citing works
Self-citationAssessing the Long-term Effects of Autonomous Vehicles: A Speculative Approach
Gruel, W., & Stanford, J. M. (2016) · Transportation Research Procedia · doi:10.1016/j.trpro.2016.05.003 · Cited by 166 · see citing works
(1997) · Springer eBooks · doi:10.1007/978-1-4757-4573-3 · Cited by 154 · see citing works
Lessons from using scenarios for strategic foresight
Bezold, C. (2010) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2010.06.012 · Cited by 129 · see citing works
Strategic learning with scenarios
Bood, R. P., & Postma, T. J. B. M. (1997) · European Management Journal · doi:10.1016/s0263-2373(97)00047-9 · Cited by 116 · see citing works
Supported driving: impacts on motorway traffic flow
Minderhoud, M. M. (1999) · Research Repository (Delft University of Technology) · Cited by 80 · see citing works
Travel-Time Valuation for Automated Driving: A Use-Case-Driven Study
Cyganski, R., Fraedrich, E. M., & Lenz, B. (2015) · elib (German Aerospace Center) · Cited by 69 · see citing works
Fagnant, D. J., & Kockelman, K. M. (2014) · Cited by 65 · see citing works
Arnaout, G. M., & Bowling, S. R. (2011) · Journal of Industrial Engineering and Management · doi:10.3926/jiem.344 · Cited by 54 · see citing works
Forum, I. T. (2015) · International transport forum policy papers · doi:10.1787/5jlwvzdk29g5-en · Cited by 48 · see citing works
Transport policy scenario-building
Stead, D., & Banister, D. (2003) · Transportation Planning and Technology · doi:10.1080/0308106032000167382 · Cited by 44 · see citing works
(2015) · Transportation Research Board 94th Annual MeetingTransportation Research Board · Cited by 42 · see citing works
(2014) · Cited by 36 · see citing works
Modelling cooperative driving in congestion shockwaves on a freeway network
Calvert, S. C., van den Broek, T. H. A., & van Noort, M. (2011) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2011.6082837 · Cited by 36 · see citing works
McMillin, B., & Bernhardt, K. L. S. (1998) · IEEE Potentials · doi:10.1109/45.721725 · Cited by 35 · see citing works
Environmental, safety, legal and societal implications of autonomous driving systems
Eugensson, A., Brännström, M., Frasher, D., Rothoff, M., Solyom, S., & Robertsson, A. (2013) · International Technical Conference on the Enhanced Safety of Vehicles (ESV) · Cited by 33 · see citing works
De maatschappelijke waarde van kortere en betrouwbaardere reistijden
Warffemius, P., Kouwenhoven, M., & de Jong, G. (2013) · Cited by 15 · see citing works
The ripple effect of automated driving
Milakis, D., van Arem, B., & van Wee, B. (2015) · Data Archiving and Networked Services (DANS) · Cited by 7 · see citing works
Self-citationCorreia, G. H. D. A., & van Arem, B. (2016) · RePEc: Research Papers in Economics · Cited by 4 · see citing works
Self-citationAN EXPLORATION OF THE DEVELOPMENT OF AUTOMATED VEHICLE GUIDANCE SYSTEMS
van Arem, B., & Smits, C. A. (1997) · Cited by 3 · see citing works
Self-citation
Flagged first, then by citations
3 of the 40 references couldn’t be matched to a known paper.
Research works printed but not linked: 7
- Gucwa, M. (2014). Mobility and Energy Impacts of Automated Cars. Paper presented at the Automated Vehicles Symposium 2014. San Francisco, CA: AVS14.
- Hoogendoorn, R., van Arem, B. and Hoogendoorn, S. (2014). Automated Driving, Traffic Flow Efficiency And Human Factors: A Literature Review. Transportation Research Record, 2422, 113-120.
- Maack, J. (2001). Scenario Analysis: A Tool for Task Managers. In Social Development Paper no. 36. Social Analysis: Selected Tools and Techniques (pp. 62-87). Washington DC: World Bank. EJTIR 17(1), 2017, pp.63-85
- Martelli, A. (2001). Scenario building and scenario planning: state of the art and prospects of evolution. Futures Research Quarterly, 17, 57-70.
- Milakis, D., van Arem, B. and van Wee, B. (2016). Policy and society related implications of automated driving: a review of evidence and directions for future research. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations (in review).
- Townsend, A. (2014). Re-programming mobility. The Digital Transformation of Transportation in the United States (Vol. 36). New York, NY: Rudin Center for Transportation Policy & Management. EJTIR 17(1), 2017, pp.63-85
- Underwood, S.E. (2014). Automated verhicles forecast: Vehicle Symposium Opinion Survey. Ann Arbor, MI: Graham Institute for Sustainability, University of Michigan.
Cited by
Sorted by citations
Milakis, D., van Arem, B., & van Wee, B. (2017) · Journal of Intelligent Transportation Systems · doi:10.1080/15472450.2017.1291351 · Cited by 963 · see citing works
Self-citationTaeihagh, A., & Lim, H. S. M. (2019) · Transport Reviews · doi:10.1080/01441647.2018.1494640 · Cited by 601 · see citing works
Faisal, A., Yigitcanlar, T., Kamruzzaman, M., & Currie, G. (2019) · Journal of Transport and Land Use · doi:10.5198/jtlu.2019.1405 · Cited by 427 · see citing works
A survey of models and algorithms for optimizing shared mobility
Mourad, A., Puchinger, J., & Chu, C. (2019) · Transportation Research Part B Methodological · doi:10.1016/j.trb.2019.02.003 · Cited by 314 · see citing works
Autonomous vehicles: theoretical and practical challenges
Martínez-Díaz, M., & Soriguera, F. (2018) · Transportation Research Procedia · doi:10.1016/j.trpro.2018.10.103 · Cited by 258 · see citing works
Will Automated Vehicles Negatively Impact Traffic Flow?
Calvert, S. C., Schakel, W., & van Lint, H. (2017) · Journal of Advanced Transportation · doi:10.1155/2017/3082781 · Cited by 197 · see citing works
Correia, G. H. D. A., de Looff, E., van Cranenburgh, S., Snelder, M., & van Arem, B. (2018) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2018.11.016 · Cited by 186 · see citing works
Self-citationCohen, T., & Cavoli, C. (2019) · Transport Reviews · doi:10.1080/01441647.2018.1524401 · Cited by 180 · see citing works
Autonomous driving, the built environment and policy implications
Fraedrich, E., Heinrichs, D., Bahamonde-Birke, F. J., & Cyganski, R. (2019) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2018.02.018 · Cited by 175 · see citing works
Urban mobility scenarios until the 2030s
Miskolczi, M., Földes, D., Munkácsy, A., & Jászberényi, M. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.103029 · Cited by 178 · see citing works
Singleton, P. A. (2019) · Transport Reviews · doi:10.1080/01441647.2018.1470584 · Cited by 173 · see citing works
Nieuwenhuijsen, J., Correia, G. H. D. A., Milakis, D., van Arem, B., & van Daalen, E. (2017) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2017.11.016 · Cited by 155 · see citing works
Self-citationImplications of automated vehicles for physical road environment: A comprehensive review
Tengilimoglu, O., Carsten, O., & Wadud, Z. (2023) · Transportation Research Part E: Logistics and Transportation Review · doi:10.1016/j.tre.2022.102989 · Cited by 149 · see citing works
Environmental impacts of autonomous vehicles: A review of the scientific literature
Silva, Ó., Cordera, R., González-González, E., & Nogués, S. (2022) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2022.154615 · Cited by 150 · see citing works
Milakis, D., Kroesen, M., & van Wee, B. (2018) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2018.03.010 · Cited by 137 · see citing works
Self-citationYiğitcanlar, T., Wilson, M. I., & Kamruzzaman, M. (2019) · Journal of Open Innovation Technology Market and Complexity · doi:10.3390/joitmc5020024 · Cited by 128 · see citing works
Richter, M. A., Hagenmaier, M., Bandte, O., Parida, V., & Wincent, J. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121857 · Cited by 124 · see citing works
Automated vehicles and how they may affect urban form: A review of recent scenario studies
Stead, D., & Vaddadi, B. (2019) · Cities · doi:10.1016/j.cities.2019.03.020 · Cited by 123 · see citing works
Shared Autonomous Vehicles Effect on Vehicle-Km Traveled and Average Trip Duration
Moreno, A. T., Michalski, A., Llorca, C., & Moeckel, R. (2018) · Journal of Advanced Transportation · doi:10.1155/2018/8969353 · Cited by 116 · see citing works
Marletto, G. (2018) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2018.10.023 · Cited by 104 · see citing works
Rad, S. R., Correia, G. H. D. A., & Hagenzieker, M. (2020) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2020.01.014 · Cited by 97 · see citing works
Manivasakan, H., Kalra, R., O’Hern, S., Fang, Y., Xi, Y., & Zheng, N. (2021) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2021.07.012 · Cited by 91 · see citing works
Chen, Y., Chen, S., Ren, H., Gao, Z., & Liu, Z. (2020) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2020.3031661 · Cited by 90 · see citing works
Arooj, A., Farooq, M. S., Akram, A., Iqbal, R., Sharma, A., & Dhiman, G. (2021) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-021-09590-x · Cited by 92 · see citing works
Anticipating long-distance travel shifts due to self-driving vehicles
Perrine, K. A., Kockelman, K. M., & Huang, Y. (2019) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2019.102547 · Cited by 89 · see citing works
Ready to bully automated vehicles on public roads?
Liu, P., Du, Y. L., Wang, L., & Young, J. D. (2020) · Accident Analysis & Prevention · doi:10.1016/j.aap.2020.105457 · Cited by 88 · see citing works
Kettwich, C., Schrank, A., & Oehl, M. (2021) · Multimodal Technologies and Interaction · doi:10.3390/mti5050026 · Cited by 86 · see citing works
Kooijman, L., Happee, R., & de Winter, J. (2019) · Information · doi:10.3390/info10120386 · Cited by 83 · see citing works
Automated vehicles and the city of tomorrow: A backcasting approach
González-González, E., Nogués, S., & Stead, D. (2019) · Cities · doi:10.1016/j.cities.2019.05.034 · Cited by 81 · see citing works
Spatial and welfare effects of automated driving: Will cities grow, decline or both?
Gelauff, G., Ossokina, I., & Teulings, C. (2019) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2019.01.013 · Cited by 79 · see citing works
Rad, S. R., Farah, H., Taale, H., van Arem, B., & Hoogendoorn, S. P. (2021) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2021.08.010 · Cited by 76 · see citing works
Self-citationAutonomous driving: a bird's eye view
Martínez‐Díaz, M., Soriguera, F., & Pérez, I. P. (2018) · IET Intelligent Transport Systems · doi:10.1049/iet-its.2018.5061 · Cited by 74 · see citing works
Li, S., Sui, P., Xiao, J., & Chahine, R. (2018) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2018.05.010 · Cited by 73 · see citing works
Overtoom, I., Correia, G. H. D. A., Huang, Y., & Verbraeck, A. (2020) · International Journal of Transportation Science and Technology · doi:10.1016/j.ijtst.2020.03.009 · Cited by 71 · see citing works
The societal dimension of the automated vehicles transition: Towards a research agenda
Milakis, D., & Müller, S. (2021) · Cities · doi:10.1016/j.cities.2021.103144 · Cited by 70 · see citing works
Self-citationE-hail (rideshare) knowledge, use, reliance, and future expectations among older adults
Vivoda, J. M., Harmon, A. C., Babulal, G. M., & Zikmund‐Fisher, B. J. (2018) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2018.03.020 · Cited by 70 · see citing works
The future of road transport : implications of automated, connected, low-carbon and shared mobility
MARIA, A. R., BIAGIO, C., PATRICIA, A. D., FULVIO, A., PHILIPPE, A. J., GIANMARCO, B., CLAUDIA, B., DARINA, B., SILVIA, B., ROBERT, B., et al. (2019) · EUR · doi:10.2760/668964 · Cited by 87 · see citing works
Fully automated vehicles: the use of travel time and its association with intention to use
Wadud, Z., & Huda, F. Y. (2019) · Proceedings of the Institution of Civil Engineers - Transport · doi:10.1680/jtran.18.00134 · Cited by 67 · see citing works
Autonomous, connected, electric shared vehicles (ACES) and public finance: An explorative analysis
Adler, M., Peer, S., & Sinozic, T. (2019) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2019.100038 · Cited by 66 · see citing works
A Systemic View on Autonomous Vehicles
Bahamonde-Birke, F. J., Kickhöfer, B., Heinrichs, D., & Kuhnimhof, T. (2018) · disP - The Planning Review · doi:10.1080/02513625.2018.1525197 · Cited by 65 · see citing works
Parking futures: Preparing European cities for the advent of automated vehicles
González-González, E., Nogués, S., & Stead, D. (2020) · Land Use Policy · doi:10.1016/j.landusepol.2019.05.029 · Cited by 63 · see citing works
Schoenmakers, M. J., Yang, D., & Farah, H. (2021) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2021.01.010 · Cited by 61 · see citing works
Tengilimoglu, O., Carsten, O., & Wadud, Z. (2023) · Transport Policy · doi:10.1016/j.tranpol.2023.02.001 · Cited by 61 · see citing works
Azmat, M., & Kummer, S. (2020) · Asian Journal of Sustainability and Social Responsibility · doi:10.1186/s41180-020-0033-7 · Cited by 59 · see citing works
User acceptance of driverless shuttles running in an open and mixed traffic environment
Nordhoff, S., van Arem, B., Merat, N., Madigan, R., Ruhrort, L., Knie, A., & Happee, R. (2017) · Cited by 57 · see citing works
Self-citationPlanning the transition to autonomous driving: A policy pathway towards urban liveability
Brovarone, E. V., Scudellari, J., & Staricco, L. (2020) · Cities · doi:10.1016/j.cities.2020.102996 · Cited by 59 · see citing works
Autonomous vehicles in mixed motorway traffic: capacity utilisation, impact and policy implications
Carrone, A. P., Rich, J., Vandet, C. A., & An, K. (2021) · Transportation · doi:10.1007/s11116-020-10154-4 · Cited by 53 · see citing works
Choi, S., & Mokhtarian, P. L. (2020) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2020.05.007 · Cited by 48 · see citing works
Acheampong, R. A., Legacy, C., Kingston, R., & Stone, J. (2023) · Transport Policy · doi:10.1016/j.tranpol.2023.03.020 · Cited by 46 · see citing works
Attributions of social interactions: Driving among self-driving vs. conventional vehicles
Lee, Y., Momen, A., & LaFreniere, J. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101631 · Cited by 46 · see citing works
Madadi, B., van Nes, R., Snelder, M., & van Arem, B. (2019) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/mice.12498 · Cited by 45 · see citing works
Self-citationNogués, S., González-González, E., & Cordera, R. (2020) · Land Use Policy · doi:10.1016/j.landusepol.2020.104652 · Cited by 45 · see citing works
Generative AI, learning and new literacies
Chen, S.-Y. (2023) · Journal of Educational Technology Development and Exchange · doi:10.18785/jetde.1602.01 · Cited by 44 · see citing works
Dynamic adaptive policymaking for the sustainable city: The case of automated taxis
Walker, W. E., & Marchau, V. (2017) · International Journal of Transportation Science and Technology · doi:10.1016/j.ijtst.2017.03.004 · Cited by 43 · see citing works
Are We Ready to Ride Autonomous Vehicles? A Pilot Study on Austrian Consumers’ Perspective
Wintersberger, S., Azmat, M., & Kummer, S. (2019) · Logistics · doi:10.3390/logistics3040020 · Cited by 40 · see citing works
Autonomous Vehicle Use and Urban Space Transformation: A Scenario Building and Analysing Method
Silva, D., Földes, D., & Csiszár, C. (2021) · Sustainability · doi:10.3390/su13063008 · Cited by 37 · see citing works
When will most cars be able to drive fully automatically? Projections of 18,970 survey respondents
Bazilinskyy, P., Kyriakidis, M., Dodou, D., & de Winter, J. (2019) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2019.05.008 · Cited by 37 · see citing works
Potential Impact of Autonomous Vehicles on Movement Behavior: A Scoping Review
Spence, J. C., Kim, Y.-B., Lamboglia, C. G., Lindeman, C., Mangan, A. J., McCurdy, A., Stearns, J. A., Wohlers, B., Sivak, A., & Clark, M. (2020) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2020.01.010 · Cited by 36 · see citing works
Mo, B., Wang, Q. Y., Moody, J., Shen, Y., & Zhao, J. (2021) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2021.103281 · Cited by 35 · see citing works
Autonomous Mobility: A Potential Opportunity to Reclaim Public Spaces for People
Fayyaz, M., González-González, E., & Nogués, S. (2022) · Sustainability · doi:10.3390/su14031568 · Cited by 34 · see citing works
Sustainable deployment of autonomous vehicles dedicated lanes in urban traffic networks
Pourgholamali, M., Miralinaghi, M., Ha, P. Y. J., Seilabi, S. E., & Labi, S. (2023) · Sustainable Cities and Society · doi:10.1016/j.scs.2023.104969 · Cited by 34 · see citing works
Azmat, M., Kummer, S., Moura, L. T., Gennaro, F. D., & Moser, R. (2019) · Logistics · doi:10.3390/logistics3020015 · Cited by 32 · see citing works
Simulating impacts of Automated Mobility-on-Demand on accessibility and residential relocation
Zhou, M., Le, D.-T., Nguyen-Phuoc, D. Q., Zegras, P. C., & Ferreira, J. (2021) · Cities · doi:10.1016/j.cities.2021.103345 · Cited by 30 · see citing works
Spatial impact of automated driving in urban areas
Legêne, M., Auping, W. L., Correia, G. H. D. A., & van Arem, B. (2020) · Journal of Simulation · doi:10.1080/17477778.2020.1806747 · Cited by 31 · see citing works
Self-citationImpact of autonomous vehicles on household relocation: An agent-based simulation
Llorca, C., Moreno, A. T., Ammar, G., & Moeckel, R. (2022) · Cities · doi:10.1016/j.cities.2022.103692 · Cited by 32 · see citing works
Stange, V., Kuhn, M. G., & Vollrath, M. (2022) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2022.04.019 · Cited by 31 · see citing works
Wong, W. P., Anwar, M. F., & Soh, K. L. (2024) · Operations Management Research · doi:10.1007/s12063-024-00471-7 · Cited by 30 · see citing works
Automated Vehicles: Changes in expert opinions over time
Kroesen, M., Milakis, D., & van Wee, B. (2023) · Transport Policy · doi:10.1016/j.tranpol.2023.03.005 · Cited by 30 · see citing works
Self-citationAnastasiadou, K. (2021) · Sustainability · doi:10.3390/su13094760 · Cited by 29 · see citing works
Toward Policies to Manage the Impacts of Autonomous Vehicles on the City: A Visioning Exercise
Staricco, L., Rappazzo, V., Scudellari, J., & Brovarone, E. V. (2019) · Sustainability · doi:10.3390/su11195222 · Cited by 28 · see citing works
Safe System approach for cyclists in the Netherlands: Towards zero fatalities and serious injuries?
Wegman, F., & Schepers, P. (2023) · Accident Analysis & Prevention · doi:10.1016/j.aap.2023.107396 · Cited by 28 · see citing works
Lyons, G. D. (2021) · Futures · doi:10.1016/j.futures.2021.102889 · Cited by 28 · see citing works
Mladenović, M. N. (2018) · The urban book series · doi:10.1007/978-3-319-96526-0_6 · Cited by 27 · see citing works
Assessing the travel impacts of subnetworks for automated driving: An exploratory study
Madadi, B., van Nes, R., Snelder, M., & van Arem, B. (2018) · Case Studies on Transport Policy · doi:10.1016/j.cstp.2018.11.006 · Cited by 27 · see citing works
Self-citationOwning or sharing autonomous vehicles: comparing different ownership and usage scenarios
Mourad, A., Puchinger, J., & Chu, C. (2019) · European Transport Research Review · doi:10.1186/s12544-019-0370-8 · Cited by 27 · see citing works
Chen, S.-Y., Kuo, H.-Y., & Lee, C. (2020) · Sustainability · doi:10.3390/su12197844 · Cited by 26 · see citing works
Genetic Algorithm-Based SOTIF Scenario Construction for Complex Traffic Flow
Zhao, S., Duan, J., Wu, S., Gu, X., Li, C., Yin, K., & Wang, H. (2023) · Automotive Innovation · doi:10.1007/s42154-023-00251-2 · Cited by 23 · see citing works
Yıldırım, Z. B., & Özuysal, M. (2024) · Sustainability · doi:10.3390/su16198323 · Cited by 22 · see citing works
How will the introduction of automated vehicles impact private car ownership?
Galich, A., & Stark, K. (2021) · Case Studies on Transport Policy · doi:10.1016/j.cstp.2021.02.012 · Cited by 21 · see citing works
Zhong, S., Cheng, R., Li, X., Zhong, W., & Jiang, Y. (2020) · Journal of Transport and Land Use · doi:10.5198/jtlu.2020.1692 · Cited by 20 · see citing works
Anastasiadou, K., Gavanas, N., Pitsiava-Latinopoulou, M., & Bekiaris, E. (2021) · Energies · doi:10.3390/en14175269 · Cited by 20 · see citing works
Calvert, S. C., Klunder, G. A., Steendijk, J. L. L., & Snelder, M. (2020) · Case Studies on Transport Policy · doi:10.1016/j.cstp.2020.05.011 · Cited by 16 · see citing works
Self-citationStange, V., Kuhn, M. G., & Vollrath, M. (2022) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2022.04.004 · Cited by 16 · see citing works
Effects of driverless vehicles
Pernestål, A., & Kristoffersson, I. (2019) · European journal of transport and infrastructure research · doi:10.18757/ejtir.2019.19.1.4079 · Cited by 16 · see citing works
Autonomous, Connected, Electric Shared Vehicles (ACES) and Public Finance: An Explorative AnalysisPreprint
Adler, M., Peer, S., & Sinoƶic, T. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3323618 · Cited by 16 · see citing works
Bilal, M. T., & Giglio, D. (2023) · European Transport Research Review · doi:10.1186/s12544-023-00579-0 · Cited by 15 · see citing works
Liu, A., Zhong, S., Sun, D., Gong, Y., Fan, M., & Song, Y. (2023) · Cities · doi:10.1016/j.cities.2023.104742 · Cited by 14 · see citing works
Zakeri, S., Konstantas, D., Sorooshian, S., & Chatterjee, P. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10917-w · Cited by 14 · see citing works
Gavanas, N., Anastasiadou, K., Nathanail, E., & Basbas, S. (2024) · Land · doi:10.3390/land13111807 · Cited by 14 · see citing works
Dong, J., Wang, J., & Luo, D. (2022) · Transportation Safety and Environment · doi:10.1093/tse/tdac021 · Cited by 13 · see citing works
Iterative urban design and transport simulation using Sketch MATSim
Maheshwari, T., Fourie, P. J., Ordóñez, S., & Axhausen, K. W. (2023) · Journal of Urban Design · doi:10.1080/13574809.2023.2214080 · Cited by 13 · see citing works
Cao, W., Chen, Y., & Wang, K. (2024) · Research in Transportation Business & Management · doi:10.1016/j.rtbm.2024.101224 · Cited by 13 · see citing works
Departure Time Choice and Bottleneck Congestion with Automated Vehicles: Role of On-board Activities
Pudāne, B. (2020) · European journal of transport and infrastructure research · doi:10.18757/ejtir.2020.20.4.4801 · Cited by 13 · see citing works
Towards Artificial Intelligence: Concepts, Applications, and Innovations
Saba, D., Sahli, Y., Maouedj, R., Hadidi, A., & Benmedjahed, M. (2020) · Studies in computational intelligence · doi:10.1007/978-3-030-52067-0_6 · Cited by 14 · see citing works
Employing waterborne autonomous vehicles for museum visits: a case study in Amsterdam
Rong, H., Tu, W., Duarte, F., & Ratti, C. (2020) · European Transport Research Review · doi:10.1186/s12544-020-00459-x · Cited by 13 · see citing works
A study of the scheduling effect on shared autonomous vehicles adoption
Susilawati, S., & Lim, T. S. (2021) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2021.100394 · Cited by 13 · see citing works
Monitoring and Forecasting of Key Functions and Technologies for Automated Driving
Ulrich, C., Frieske, B., Schmid, S., & Friedrich, H. E. (2022) · Forecasting · doi:10.3390/forecast4020027 · Cited by 12 · see citing works
External effects of urban automated vehicles on sustainability
Letmathe, P., & Paegert, M. (2023) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.140257 · Cited by 12 · see citing works
van Duin, R., van Amstel, W. P., Quak, H. J., van Wee, B., Annema, J. A., & Köhler, J. (2022) · Edward Elgar Publishing eBooks · doi:10.4337/9781800373372 · Cited by 12 · see citing works
Self-citationIndustry 4.0 an empirical analysis of users’ intention in the automotive sector
Toni, M., Renzi, M. F., Pasca, M. G., Mugion, R. G., Pietro, L. D., & Ungaro, V. (2021) · International Journal of Quality and Service Sciences · doi:10.1108/ijqss-04-2020-0062 · Cited by 11 · see citing works
- Authors
- Milakis, D., Snelder, M., Arem, B. V., Wee, B. V., & Homem de Almeida Correia, G.
- Affiliations
- Delft University of Technology (NL)
- Netherlands Organisation for Applied Scientific Research (NL)
- Venue
- European Journal of Transport and Infrastructure Research
- Publisher
- TU Delft OPEN Publishing
- Published
- 2017-01-01
- Volume
- 17
- Issue
- 1
- ISSN
- 1567-7133 (ISSN-L)
- 1567-7141
- OpenAlex
- W2592807484
- Cited by
- 194
- References
- 40
- Citations by year
- 2026: 14 · 2025: 19 · 2024: 20 · 2023: 22 · 2022: 23 · 2021: 26 · 2020: 21 · 2019: 24 · 2018: 19 · 2017: 6
- FWCI
- 12.15
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- European journal of transport and infrastructure research (publishedVersion, cc-by)
- Repository hosted by TU Delft Library (TU Delft) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- TNO Repository (submittedVersion)
- Research Repository (Delft University of Technology) (submittedVersion, cc-by-nc)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Planbureau voor de Leefomgeving
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
- Social Sciences › Transportation › Transportation Planning and Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Keywords
- autonomous vehicles, autonomous driving, future scenarios, travel demand, travel behavior, transportation planning, policy scenarios, mobility impacts, Netherlands
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
