The DOI matches its Crossref record; 72 of the 73 references it cites were found in a registry or an index.
On the future of transportation in an era of automated and autonomous vehicles
Open accessAbstract
Automated vehicles (AVs) already navigate US highways and those of many other nations around the world. Current questions about AVs do not now revolve around whether such technologies should or should not be implemented; they are already with us. Rather, such questions are more and more focused on how such technologies will impact evolving transportation systems, our social world, and the individuals who live within it and whether such systems ought to be fully automated or remain under some form of direct human control. More importantly, how will mobility itself change as these independent operational vehicles first share and then dominate our roadways? How will the public be kept apprised of their evolving capacities, and what will be the impact of science and the communication of scientific advances across the varying forms of social media on these developments? We look here to address these issues and to provide some suggestions for the problems that are currently emerging.
Overview
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
Verification
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“While AVs could reduce energy consumption-for example, by reducing traffic congestion and inducing efficiency through eco-driving-it is also possible that AVs will lead to an increase in overall road traffic that nullifies efficiency gains.”
From Tackling climate change with machine learning (2023) · cites this paper as [327]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Trust in Automation: Designing for Appropriate Reliance
Lee, J. D., & See, K. A. (2004) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/hfes.46.1.50_30392 · Cited by 6,605 · cited 1×
“For the former, design processes should seek to design explicitly for appropriate levels of trust by human occupants in light of the known reliability of the automation (73, 74).”
BackgroundCramming More Components onto Integrated Circuits (1965)
Moore, G. E. (2021) · The MIT Press eBooks · doi:10.7551/mitpress/12274.003.0027 · Cited by 6,274
Cramming More Components Onto Integrated Circuits
Moore, G. E. (1998) · Proceedings of the IEEE · doi:10.1109/jproc.1998.658762 · Cited by 5,954
A model for types and levels of human interaction with automation
Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195 · cited 1×
“These effects will be felt for decades and then across generations as economies adapt to the new added capacities (41).”
BackgroundPrinciples of topological psychology.
Lewin, K. (1936) · McGraw-Hill eBooks · doi:10.1037/10019-000 · Cited by 3,938
The Singularity Is near: When Humans Transcend Biology
Mead, W. R., & Kurzweil, R. (2006) · Foreign Affairs · doi:10.2307/20031996 · Cited by 3,418
Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations
Fagnant, D. J., & Kockelman, K. (2015) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2015.04.003 · Cited by 3,214
The Cambridge Handbook of Expertise and Expert Performance
Ericsson, K. A., Charness, N. H., Feltovich, P. J., Hoffman, R. R., Michelene, T. H., Hunt, E., Prietula, M. J., Amirault, R. J., Branson, R. K., Buchanan, B. G., et al. (2006) · Cambridge University Press eBooks · doi:10.1017/cbo9780511816796 · Cited by 3,160
Self-citationTrust in Automation: Integrating Empirical Evidence on Factors That Influence Trust
Hoff, K. A., & Bashir, M. (2015) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720814547570 · Cited by 2,817
A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction
Hancock, P. A., Billings, D. R., Schaefer, K. E., Chen, J. Y. C., de Visser, E. J., & Parasuraman, R. (2011) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720811417254 · Cited by 2,051 · cited 1×
“It is critical, because if there is insufficient human trust in autonomous and semiautonomous systems, there will be both little usage and chronic misuse (75).”
BackgroundSelf-citation
Research works printed but not linked: 8
- , ed PM Fitts (National Research Council, Washington, DC Human Engineering for an Effective Air Navigation and Traffic Control System, 1951).
- ST Fiske, SE Taylor Social Cognition (McGraw-Hill, New York, 1991).
- T Gilovich, R Eibach, The fundamental attribution error where it really counts. Psychol Inq 12, 23–26 (2001).
- R Brooks, The self-driving car’s people problem. IEEE Spectrum 34–37, 50–51 (2017).
- K Button Transport Economics (Edward Elgar Publishing, Cheltenham, UK, 2010).
- 10.1518/hfes.46.1.50.30392 · DOI · Paper page
- B Fischhoff, S Lichtenstein, P Slovic, SL Derby, RL Keeney Acceptable Risk (Cambridge Univ Press, New York, 1981).
- PA Hancock Essays on the Future of Human-Machine Systems (Banta, Eden Prairie, MN, 1997).
Cited by
Sorted by citations
Trust in Artificial Intelligence: Meta-Analytic Findings
Kaplan, A. D., Kessler, T. T., Brill, J. C., & Hancock, P. A. (2023) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211013988 · Cited by 397
Self-citationTackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336
Trusting Automation: Designing for Responsivity and Resilience
Chiou, E. K., & Lee, J. D. (2023) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211009995 · Cited by 301
Autonomous Shopping Systems: Identifying and Overcoming Barriers to Consumer Adoption
de Bellis, E., & Johar, G. V. (2020) · Journal of Retailing · doi:10.1016/j.jretai.2019.12.004 · Cited by 296
Evolving Trust in Robots: Specification Through Sequential and Comparative Meta-Analyses
Hancock, P. A., Kessler, T. T., Kaplan, A. D., Brill, J. C., & Szalma, J. L. (2020) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720820922080 · Cited by 253
Self-citationAdaptive virtual reality-based training: a systematic literature review and framework
Zahabi, M., & Abdul Razak, A. M. (2020) · Virtual Reality · doi:10.1007/s10055-020-00434-w · Cited by 233
Human Mental Workload: A Survey and a Novel Inclusive Definition
Longo, L., Wickens, C. D., Hancock, G., & Hancock, P. A. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.883321 · Cited by 222
Self-citationRahman, M. M., & Thill, J. (2023) · Sustainable Cities and Society · doi:10.1016/j.scs.2023.104649 · Cited by 194
Deep learning-based robust positioning for all-weather autonomous driving
Almalıoğlu, Y., Turan, M., Trigoni, N., & Markham, A. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00520-5 · Cited by 170
Montoro, L. V., Useche, S. A., Alonso, F., Lijarcio, I., Seguí, P. B., & Bertolín, A. M.-B. (2019) · Safety Science · doi:10.1016/j.ssci.2019.07.041 · Cited by 164
Change, I. P. O. C. (2023) · Cambridge University Press eBooks · doi:10.1017/9781009157926.012 · Cited by 212
Evaluating science communication
Fischhoff, B. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1805863115 · Cited by 159
How and why humans trust: A meta-analysis and elaborated model
Hancock, P. A., Kessler, T. T., Kaplan, A. D., Stowers, K. L., Brill, J. C., Billings, D. R., Schaefer, K. E., & Szalma, J. L. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1081086 · Cited by 168
Self-citationWill autonomous vehicles change auto commuters’ value of travel time?
Zhong, H., Li, W., Burris, M. W., Talebpour, A., & Sinha, K. C. (2020) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2020.102303 · Cited by 145
Exploring the who, what, when, where, and why of automated vehicle disengagements
Boggs, A. M., Arvin, R., & Khattak, A. J. (2019) · Accident Analysis & Prevention · doi:10.1016/j.aap.2019.105406 · Cited by 136
Multimodal Features for Detection of Driver Stress and Fatigue: Review
Němcová, A., Svozilová, V., Bucsuházy, K., Smíšek, R., Mézl, M., Hesko, B., Belák, M., Bilík, M., Maxera, P., Seitl, M., et al. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.2977762 · Cited by 128
Intrusion Detection in the Automotive Domain: A Comprehensive Review
Lampe, B., & Meng, W. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3309864 · Cited by 128
Analysis and Control of Autonomous Mobility-on-Demand Systems
Zardini, G., Lanzetti, N., Pavone, M., & Frazzoli, E. (2021) · Annual Review of Control Robotics and Autonomous Systems · doi:10.1146/annurev-control-042920-012811 · Cited by 114
A Survey of Collaborative Machine Learning Using 5G Vehicular Communications
Balkus, S. V., Wang, H., Cornet, B., Mahabal, C., Ngo, H. T., & Fang, H. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3149714 · Cited by 119
Enhanced Mobility With Connectivity and Automation: A Review of Shared Autonomous Vehicle Systems
Zhao, L., & Malikopoulos, A. A. (2022) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2019.2953526 · Cited by 93
Ayoub, J., Yang, X. J., & Zhou, F. (2021) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2020.12.015 · Cited by 100
Challenges to Human Drivers in Increasingly Automated Vehicles
Hancock, P. A., Kajaks, T., Caird, J. K., Chignell, M., Mizobuchi, S., Burns, P. C., Feng, J., Fernie, G. R., Lavallière, M., Noy, I. Y., et al. (2020) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720819900402 · Cited by 91
Self-citationAckermans, S., Dey, D., Ruijten, P. A. M., Cuijpers, R. H., & Pfleging, B. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376197 · Cited by 85
Mutzenich, C., Durant, S., Helman, S., & Dalton, P. (2021) · Cognitive Research Principles and Implications · doi:10.1186/s41235-021-00271-8 · Cited by 85
Corlu, C. G., de la Torre, R., Serrano-Hernández, A., Juan, A. A., & Faulín, J. (2020) · Energies · doi:10.3390/en13051115 · Cited by 74
Hancock, G. M., Longo, L., Young, M. S., & Hancock, P. A. (2021) · Wiley eBooks · doi:10.1002/9781119636113.ch7 · Cited by 70
Self-citationV2I based environment perception for autonomous vehicles at intersections
Duan, X., Jiang, H., Tian, D., Zou, T., Zhou, J., & Cao, Y. (2021) · China Communications · doi:10.23919/jcc.2021.07.001 · Cited by 68
Chen, W., Sun, X., Liu, L., Liu, X., Zhang, R., Zhang, S., Xue, J., Sun, Q., Wang, M., Li, X., et al. (2022) · One Earth · doi:10.1016/j.oneear.2022.07.005 · Cited by 68
Assessing the Role of Autonomous Vehicles in Urban Areas: A Systematic Review of Literature
Makahleh, H. Y., Ferranti, E. J. S., & Dissanayake, D. (2024) · Future Transportation · doi:10.3390/futuretransp4020017 · Cited by 55
Zhang, Q., Wallbridge, C. D., Jones, D. M., & Morgan, P. L. (2023) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2023.103887 · Cited by 54
Calibrating Trust in Automation Through Familiarity With the Autoparking Feature of a Tesla Model X
Tenhundfeld, N. L., de Visser, E. J., Haring, K. S., Ries, A. J., Finomore, V. S., & Tossell, C. C. (2019) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343419869083 · Cited by 55
A comprehensive study on lane detecting autonomous car using computer vision
Gajjar, H., Sanyal, S., & Shah, M. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.120929 · Cited by 51
Interactions and Behaviors of Pedestrians with Autonomous Vehicles: A Synthesis
Rezwana, S., & Lownes, N. (2024) · Future Transportation · doi:10.3390/futuretransp4030034 · Cited by 50
Realizing high‐energy density for practical lithium–sulfur batteries
Fang, R., Chen, K., Sun, Z., Hu, G., Wang, D., & Li, F. (2023) · Interdisciplinary materials · doi:10.1002/idm2.12118 · Cited by 49
Global Endeavors to Address the Health Effects of Urban Air Pollution
Jin, L. N., Apte, J. S., Miller, S. L., Tao, S., Wang, S., Jiang, G., & Li, X. D. (2022) · Environmental Science & Technology · doi:10.1021/acs.est.2c02627 · Cited by 46
Huang, K., Kockelman, K. M., & Gurumurthy, K. M. (2022) · Transportation Letters · doi:10.1080/19427867.2022.2070091 · Cited by 44
Wang, S., Correia, G. H. D. A., & Lin, H. X. (2019) · Journal of Advanced Transportation · doi:10.1155/2019/7878042 · Cited by 43
Avoiding adverse autonomous agent actions
Hancock, P. A. (2021) · Human-Computer Interaction · doi:10.1080/07370024.2021.1970556 · Cited by 40
Self-citationNaeem, A. B., Soomro, A. M., Saim, H. M., & Malik, H. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16950-1 · Cited by 38
Salmon, P. M., Carden, T., & Hancock, P. A. (2020) · Human Factors and Ergonomics in Manufacturing & Service Industries · doi:10.1002/hfm.20883 · Cited by 36
Self-citationPrediction-Based Reachability for Collision Avoidance in Autonomous Driving
Li, A., Sun, L., Zhan, W., Tomizuka, M., & Chen, M. (2021) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48506.2021.9560790 · Cited by 36
How to compete with robots by assessing job automation risks and resilient alternatives
Paolillo, A., Colella, F., Nosengo, N., Schiano, F., Stewart, W., Zambrano, D., Chappuis, I., Lalive, R., & Floreano, D. (2022) · Science Robotics · doi:10.1126/scirobotics.abg5561 · Cited by 38
Bandeira, J. M., Macedo, E., Fernandes, P., Rodrigues, M., Andrade, M., & Coelho, M. C. (2021) · IEEE Open Journal of Intelligent Transportation Systems · doi:10.1109/ojits.2021.3112904 · Cited by 34
Liu, C., Liu, Z., Xu, Z., & Li, X. S. (2024) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2024.104720 · Cited by 34
The politics of new driving technologies: Political ideology and autonomous vehicle adoption
Mack, E. A., Miller, S. R., Chang, C.-H. D., Fossen, J. A. V., Cotten, S. R., Savolainen, P. T., & Mann, J. (2021) · Telematics and Informatics · doi:10.1016/j.tele.2021.101604 · Cited by 33
Rumors in the air? Exploring public misconceptions about automated vehicles
Du, M., Zhang, T., Liu, J., Xu, Z., & Liu, P. (2022) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2022.01.003 · Cited by 33
Pande, D., & Taeihagh, A. (2023) · Journal of Economic Policy Reform · doi:10.1080/17487870.2023.2197599 · Cited by 26
Cyber security and its impact on CAV safety: Overview, policy needs and challenges
Katrakazas, C., Theofilatos, A., Papastefanatos, G., Härri, J., & Antoniou, C. (2020) · Advances in transport policy and planning · doi:10.1016/bs.atpp.2020.05.001 · Cited by 34
A Cooperative Control Framework for CAV Lane Change in a Mixed Traffic EnvironmentPreprint
Du, R., Chen, S., Li, Y., Dong, J., Ha, P. Y. J., & Labi, S. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.05439 · Cited by 32
Syncing sustainable urban mobility with public transit policy trends based on global data analysis
Ceder, A. A. (2021) · Scientific Reports · doi:10.1038/s41598-021-93741-4 · Cited by 31
Gao, Z., Wen-min, L., Liang, J., Hanxi, P. A. N., Xu, W., & Shen, M. (2021) · Advances in Psychological Science · doi:10.3724/sp.j.1042.2021.02172 · Cited by 34
Simulating a transition to autonomous mobility
Rezaei, M., & Caulfield, B. M. (2020) · Simulation Modelling Practice and Theory · doi:10.1016/j.simpat.2020.102175 · Cited by 30
ASAYAR: A Dataset for Arabic-Latin Scene Text Localization in Highway Traffic Panels
Akallouch, M., Boujemaa, K. S., Bouhoute, A., Fardousse, K., & Berrada, I. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.3029451 · Cited by 30
Zhou, X., Wang, Z., & Wang, J. (2021) · Journal of Dynamic Systems Measurement and Control · doi:10.1115/1.4051466 · Cited by 28
Traffic Scenarios for Automated Vehicle Testing: A Review of Description Languages and Systems
Ma, J., Che, X., Li, Y., & Lai, E. M.-K. (2021) · Machines · doi:10.3390/machines9120342 · Cited by 28
Human’s Intuitive Mental Models as a Source of Realistic Artificial Intelligence and Engineering
Suomala, J., & Kauttonen, J. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.873289 · Cited by 32
Human Injury-Based Safety Decision of Automated Vehicles
Wang, Q., Zhou, Q., Lin, M., & Nie, B. (2022) · iScience · doi:10.1016/j.isci.2022.104703 · Cited by 28
Assessing the Effect of Drivers’ Gender on Their Intention to Use Fully Automated Vehicles
Useche, S. A., Ortega, M. P., Gonzalez-Marin, A., & Llamazares, F. J. (2021) · Applied Sciences · doi:10.3390/app12010103 · Cited by 28
The Science of Science Communication III
Fischhoff, B., & Scheufele, D. A. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1902256116 · Cited by 27
Zaghari, N., Fathy, M., Jameii, S. M., Sabokrou, M., & Shahverdy, M. (2020) · The Journal of Supercomputing · doi:10.1007/s11227-020-03399-4 · Cited by 29
Dynamic scan paths investigations under manual and highly automated driving
Navarro, J., Lappi, O., Osiurak, F., Hernout, E., Gabaude, C., & Reynaud, E. (2021) · Scientific Reports · doi:10.1038/s41598-021-83336-4 · Cited by 27
Expert elicitation on paths to advance fuel cell electric vehicles
Whiston, M. M., Azevedo, I. L., Litster, S., Samaras, C., Whitefoot, K. S., & Whitacre, J. F. (2021) · Energy Policy · doi:10.1016/j.enpol.2021.112671 · Cited by 27
Driver-Pedestrian Perceptual Models Demonstrate Coupling: Implications for Vehicle Automation
Domeyer, J. E., Lee, J. D., Toyoda, H., Mehler, B. L., & Reimer, B. (2022) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2022.3158201 · Cited by 32
Trust in Automated Parking Systems
de Visser, E. J., Phillips, E. J., Tenhundfeld, N. L., Donadio, B. T., Barentine, C., Kim, B., Madison, A., Ries, A. J., & Tossell, C. C. (2022) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2023.05.018 · Cited by 25
Impact of Pilot's Expertise on Selection, Use, Trust, and Acceptance of Automation
Navarro, J., Allali, S., Cabrignac, N., & Cegarra, J. (2021) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2021.3090199 · Cited by 27
A human factors perspective on how to keep SAE Level 3 conditional automated driving safe
Gerber, M. A., Schroeter, R., & Ho, B. S. (2023) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2023.100959 · Cited by 25
Not in Control, but Liable? Attributing Human Responsibility for Fully Automated Vehicle Accidents
Zhai, S., Wang, L., & Liu, P. (2023) · Engineering · doi:10.1016/j.eng.2023.10.008 · Cited by 25
Spatial modeling and design of smart communities
Yoshida, T., Yamagata, Y., Chang, S., de Gooyert, V., Seya, H., Murakami, D., Jittrapirom, P., & Voulgaris, G. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-816055-8.00007-5 · Cited by 25
Doole, M., Ellerbroek, J., & Hoekstra, J. M. (2022) · Aerospace · doi:10.3390/aerospace9030120 · Cited by 24
Ali, H. I., Kurunathan, H., Eldefrawy, M. H., Gruian, F., & Jönsson, M. (2025) · IEEE Access · doi:10.1109/access.2025.3537800 · Cited by 22
Liu, H., Hirayama, T., Morales, L. Y., & Murase, H. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2073006 · Cited by 22
A Novel Cooperation-Guided Warning of Invisible Danger from AR-HUD to Enhance Driver’s Perception
You, F., Zhang, J., Zhang, J., Shen, L., Fang, W., Cui, W., & Wang, J. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2233734 · Cited by 22
Driver State and Behavior Detection Through Smart Wearables
Tavakoli, A., Kumar, S., Boukhechba, M., & Heydarian, A. (2021) · IEEE Intelligent Vehicles Symposium · doi:10.1109/iv48863.2021.9575431 · Cited by 21
When both human and machine drivers make mistakes: Whom to blame?
Zhai, S., Gao, S., Wang, L., & Liu, P. (2023) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2023.103637 · Cited by 21
Intelligent Road Management System for Autonomous, Non-Autonomous, and VIP Vehicles
Naeem, A. B., Senapati, B., Sudman, M. S. I., Bashir, K., & Ahmed, A. E. M. (2023) · World Electric Vehicle Journal · doi:10.3390/wevj14090238 · Cited by 21
Neuroergonomics: Where the Cortex Hits the Concrete
Hancock, P. A. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00115 · Cited by 21
Self-citationEffect of Takeover Request Time and Warning Modality on Trust in L3 Automated Driving
Wu, Y., Yao, X., Deng, F., & Yuan, X. (2024) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208241278433 · Cited by 21
Ranjbar, P., Krishnakumari, P., Andersson, J., & Klingegård, M. (2022) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2022.100630 · Cited by 20
Osman, R. A. (2023) · Electronics · doi:10.3390/electronics12194023 · Cited by 20
Grote, G. (2023) · Ergonomics · doi:10.1080/00140139.2023.2278408 · Cited by 25
A MARL Approach for Optimizing Positions of VANET Aerial Base-Stations on a Sparse Highway
Jiang, B., Givigi, S. N., & Delamer, J.-A. (2021) · IEEE Access · doi:10.1109/access.2021.3108891 · Cited by 19
Reacting and responding to rare, uncertain and unprecedented events
Hancock, P. A. (2022) · Ergonomics · doi:10.1080/00140139.2022.2095443 · Cited by 23
Self-citationROMR: A ROS-based open-source mobile robot
Nwankwo, L. E., Fritze, C., Bartsch, K., & Rueckert, E. (2023) · HardwareX · doi:10.1016/j.ohx.2023.e00426 · Cited by 19
Zhang, X., Robson, E. N., & Waller, S. T. (2020) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/mice.12611 · Cited by 21
Transduction between magnets and ions
Wang, Y., Xie, S., Bai, Y., Suo, Z., & Jia, K. (2021) · Materials Horizons · doi:10.1039/d1mh00418b · Cited by 19
Interactions of Automated Vehicles with Road Users
Dey, D., Ackermans, S., Martens, M., Pfleging, B., & Terken, J. M. B. (2022) · Studies in computational intelligence · doi:10.1007/978-3-030-77726-5_20 · Cited by 19
Navarro, J., & Hancock, P. (2022) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2022.2076954 · Cited by 9
Self-citationLiu, C., Xu, Z., Liu, Z., Li, X., & Zhang, Y. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2024.3467091 · Cited by 18
Road safety, health inequity and the imminence of autonomous vehicles
Nunes, A., & Axhausen, K. W. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-021-00382-3 · Cited by 18
Du, R., Chen, S., Li, Y., Alinizzi, M., & Labi, S. (2022) · Electronics · doi:10.3390/electronics11091350 · Cited by 18
Is it OK to bully automated cars?
Liu, P., Zhai, S., & Li, T. (2022) · Accident Analysis & Prevention · doi:10.1016/j.aap.2022.106714 · Cited by 20
A fully-actuated quadcopter representation using quaternions
Escobar, J. C., Abaunza, H., & Castillo, P. (2022) · International Journal of Control · doi:10.1080/00207179.2022.2129789 · Cited by 18
Understanding common human driving semantics for autonomous vehicles
Xia, Y., Geng, M., Chen, Y., Sun, S., Liao, C., Zhu, Z., Li, Z., Ochieng, W. Y., Angeloudis, P., Elhajj, M., et al. (2023) · Patterns · doi:10.1016/j.patter.2023.100730 · Cited by 18
Cai, J., Fu, X., Gu, Z., & Wu, R. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2212224 · Cited by 18
Liu, H., Hirayama, T., Saiki, L. Y. M., & Murase, H. (2020) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc45102.2020.9294696 · Cited by 18
Cegarra, J., Unrein, H., André, J., Mouton, O., & Navarro, J. (2025) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2025.03.023 · Cited by 18
Human and machine drivers: Sharing control, sharing responsibility
Zhai, S., Wang, L., & Liu, P. (2023) · Accident Analysis & Prevention · doi:10.1016/j.aap.2023.107096 · Cited by 18
Hancock, P. A. (2023) · Ergonomics · doi:10.1080/00140139.2023.2236822 · Cited by 18
Self-citationHancock, P. A. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.574097 · Cited by 18
Self-citationImproving single-stage object detectors for nighttime pedestrian detection
Devi, S., Thopalli, K., Malarvezhi, P., & Thiagarajan, J. J. (2022) · International Journal of Pattern Recognition and Artificial Intelligence · doi:10.1142/s0218001422500343 · Cited by 15
Metadata
- Authors
- Hancock, P. A., Nourbakhsh, I., & Stewart, J.
- Affiliations
- University of Central Florida (US)
- Carnegie Mellon University (US)
- Wired Magazine, San Francisco, CA 94107
- Corresponding author
- Hancock, P. A.
- ORCID
- Hancock, P. A.
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2019-01-14
- Volume
- 116
- Issue
- 16
- Pages
- 7684-7691
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC6475395
- OpenAlex
- W2908550123
- Cited by
- 312
- References
- 73
- Citations by year
- 2026: 30 · 2025: 41 · 2024: 40 · 2023: 47 · 2022: 61 · 2021: 49 · 2020: 33 · 2019: 10
- FWCI
- 17.43
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Transportation › Transportation and Mobility Innovations
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Keywords
- autonomous vehicles, future of transport, mobility, public understanding of technology, science communication, social media, societal impact of automation
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