The DOI matches its Crossref record; 51 of the 52 references it cites were found in a registry or an index.
Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles
Open accessAbstract
Experts predict that new automobiles will be capable of driving themselves under limited conditions within 5–10 years, and under most conditions within 10–20 years. Automation may affect road vehicle energy consumption and greenhouse gas (GHG) emissions in a host of ways, positive and negative, by causing changes in travel demand, vehicle design, vehicle operating profiles, and choices of fuels. In this paper, we identify specific mechanisms through which automation may affect travel and energy demand and resulting GHG emissions and bring them together using a coherent energy decomposition framework. We review the literature for estimates of the energy impacts of each mechanism and, where the literature is lacking, develop our own estimates using engineering and economic analysis. We consider how widely applicable each mechanism is, and quantify the potential impact of each mechanism on a common basis: the percentage change it is expected to cause in total GHG emissions from light-duty or heavy-duty vehicles in the U.S. Our primary focus is travel related energy consumption and emissions, since potential lifecycle impacts are generally smaller in magnitude. We explore the net effects of automation on emissions through several illustrative scenarios, finding that automation might plausibly reduce road transport GHG emissions and energy use by nearly half – or nearly double them – depending on which effects come to dominate. We also find that many potential energy-reduction benefits may be realized through partial automation, while the major energy/emission downside risks appear more likely at full automation. We close by presenting some implications for policymakers and identifying priority areas for further research.
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 [820]
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
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
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
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
The future mobility of the world population
Schafer, A., & Victor, D. G. (2000) · Transportation Research Part A Policy and Practice · doi:10.1016/s0965-8564(98)00071-8 · Cited by 674
Energy and emissions impacts of a freeway-based dynamic eco-driving system
Barth, M., & Boriboonsomsin, K. (2009) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2009.01.004 · Cited by 630
Environmental assessment of passenger transportation should include infrastructure and supply chains
Chester, M. V., & Horvath, A. (2009) · Environmental Research Letters · doi:10.1088/1748-9326/4/2/024008 · Cited by 592
Autonomous Vehicle Technology: A Guide for Policymakers
Anderson, J. M., Kalra, N., Stanley, K. D., Sorensen, P. A., Samaras, C., & Oluwatola, O. A. (2014) · RAND Corporation eBooks · doi:10.7249/rr443 · Cited by 590
Greenhouse Gas Emission Impacts of Carsharing in North America
Martin, E. W., & Shaheen, S. (2011) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2011.2158539 · Cited by 528
Spieser, K., Treleaven, K., Zhang, R., Frazzoli, E., Morton, D., & Pavone, M. (2014) · Lecture notes in mobility · doi:10.1007/978-3-319-05990-7_20 · Cited by 442
Anthropological invariants in travel behavior
Marchetti, C. (1994) · Technological Forecasting and Social Change · doi:10.1016/0040-1625(94)90041-8 · Cited by 384
Flagged first, then by citations
1 of the 52 references couldn’t be matched to a known paper.
Research works printed but not linked: 7
- AAA, 2012. Your Driving Costs, 2012 edition, Heathrow, FL.
- Cambridge Systematics, 2009. Assessment of Fuel Economy Technologies for Medium and Heavy Duty Vehicles: Commissioned Paper on Indirect Costs and Alternative Approaches, Draft final paper, Cambridge Systematics Inc. (revised 21.09.09).
- Gladwell, M., 2004. Big and Bad: How the SUV ran over Automotive Safety. The New Yorker, Jan 12, pp. 28–33.
- IEEE, 2012. News release on Intelligent Transportation System. Available: <http://www.ieee.org/about/news/2012/5september_2_2012.html> (accessed Jan 2014).
- Tsugawa, S., 2013. Energy and Environmental Implications of Automated Truck Platooning within Energy ITS Project. TRB Road Vehicle Automation Workshop, Stanford, CA (16.07.13).
- Underwood, S., 2014. Automated Vehicles Forecast: Vehicle Symposium Opinion Survey. Automated Vehicles Symposium 2014, Burlingame, CA (15.07.14).
- White, 2010, Why 70 miles per hour is the new 55, The Wall Street J.
Cited by
Sorted by citations
Items 301–400 of 857
IIGPTS: IoT-Based Framework for Intelligent Green Public Transportation System
Ladha, A., Bhattacharya, P., Chaubey, N. K., & Bodkhe, U. (2020) · Lecture notes in networks and systems · doi:10.1007/978-981-15-3369-3_14 · Cited by 29
Milovanoff, A., Posen, I. D., Saville, B. A., & MacLean, H. L. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.110012 · Cited by 31
Ahmed, T., Hyland, M. F., Sarma, N. J. S., Mitra, S. K., & Ghaffar, A. (2020) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2020.09.002 · Cited by 27
Tsigdinos, S., Karolemeas, C., Bakogiannis, E., & Nikitas, A. (2021) · Case Studies on Transport Policy · doi:10.1016/j.cstp.2021.03.018 · Cited by 31
Impacts of large-scale driverless truck adoption on the freight transport system
Engholm, A., Kristoffersson, I., & Pernestål, A. (2021) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2021.10.014 · Cited by 29
Climate and environmental impacts of automated minibuses in future public transportation
Huber, D., Viere, T., Nemoto, E. H., Jaroudi, I., Korbee, D., & Fournier, G. (2022) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2021.103160 · Cited by 33
Aittoniemi, E. (2022) · IET Intelligent Transport Systems · doi:10.1049/itr2.12219 · Cited by 30
Beza, A. D., Zefreh, M. M., & Török, Á. (2022) · Energies · doi:10.3390/en15186669 · Cited by 29
The case for ‘public’ transport in the age of automated mobility
Docherty, I., Stone, J., Curtis, C., Sørensen, C. H., Paulsson, A., Legacy, C., & Marsden, G. R. (2022) · Cities · doi:10.1016/j.cities.2022.103784 · Cited by 27
Consumer preferences for ride-hailing: Barriers to an autonomous, shared, and electric future
Sheldon, T. L., & Dua, R. (2023) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.140251 · Cited by 28
Life cycle greenhouse gas impacts of a connected and automated SUV and van
Kemp, N. J., Keoleian, G. A., He, X., & Kasliwal, A. (2020) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2020.102375 · Cited by 28
Impact of Driverless Vehicles on Urban Environment and Future Mobility
Agriesti, S., Brevi, F., Gandini, P., Marchionni, G., Parmar, R., Ponti, M., & Studer, L. (2020) · Transportation research procedia · doi:10.1016/j.trpro.2020.09.005 · Cited by 34
Modelling transport emissions in an uncertain future: What actions make a difference?
Craglia, M., & Cullen, J. M. (2020) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2020.102614 · Cited by 28
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
Greenhouse Gas Emission Impact of Autonomous Vehicle Introduction in an Urban Network
Conlon, J., & Lin, J. (2019) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/0361198119839970 · Cited by 28
Liu, P. Z. (2020) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2020.10.008 · Cited by 28
Modeling the Impacts of Autonomous Vehicles on Land Use Using a LUTI Model
Cordera, R., Nogués, S., González-González, E., & Moura, J. L. (2021) · Sustainability · doi:10.3390/su13041608 · Cited by 30
Estimating energy bounds for adoption of shared micromobility
Sun, B., Garikapati, V. M., Wilson, A. M., & Duvall, A. (2021) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2021.103012 · Cited by 27
A tale of two modes: Who will use single user and shared autonomous vehicles
Gkartzonikas, C., Ke, Y., & Gkritza, K. (2022) · Case Studies on Transport Policy · doi:10.1016/j.cstp.2022.05.015 · Cited by 27
Impact of New Mobility Solutions on Travel Behaviour and Its Incorporation into Travel Demand Models
Garus, A., Alonso, B., Raposo, M. A., Ciuffo, B., & dell’Olio, L. (2022) · Journal of Advanced Transportation · doi:10.1155/2022/7293909 · Cited by 29
Smart mobility projects: Towards the formalization of a policy-making lifecycle
Simonofski, A., Handekyn, P., Vandennieuwenborg, C., Wautelet, Y., & Snoeck, M. (2022) · Land Use Policy · doi:10.1016/j.landusepol.2022.106474 · Cited by 27
Assessing the impact of Autonomous Vehicles on urban noise pollution
Patella, S. M., Aletta, F., & Mannini, L. (2019) · Noise Mapping · doi:10.1515/noise-2019-0006 · Cited by 27
Peer, S., Müller, J., Naqvi, A., & Straub, M. (2023) · Transport Policy · doi:10.1016/j.tranpol.2023.12.002 · Cited by 26
Tourist’s mobilities: Walking, cycling, driving and waiting
Hannam, K., Butler, G., Witte, A., & Zuev, D. (2021) · Tourist Studies · doi:10.1177/1468797621992931 · Cited by 26
Behavior matters: A systematic review of representing consumer mobility choices in energy models
Luh, S., Kannan, R., Schmidt, T. J., & Kober, T. (2022) · Energy Research & Social Science · doi:10.1016/j.erss.2022.102596 · Cited by 26
Physical and Digital Infrastructure Readiness Index for Connected and Automated Vehicles
Cucor, B., Petrov, T., Kamencay, P., Pourhashem, G., & Dado, M. (2022) · Sensors · doi:10.3390/s22197315 · Cited by 34
Marasco, A., & Romano, A. (2018) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2018.04.018 · Cited by 26
Mixes of Policy Instruments for the Full Decarbonisation of Energy Systems: A Review
Cocker, F. G. (2025) · Energies · doi:10.3390/en18010148 · Cited by 26
Review of Trends and Potentials in the Vehicle Concept Development Process
Nicoletti, L., Brönner, M., Danquah, B., Koch, A., König, A., Krapf, S., Pathak, A., Schockenhoff, F., Sethuraman, G., Wolff, S., et al. (2020) · International Conference on Ecological Vehicles and Renewable Energies (EVER) · doi:10.1109/ever48776.2020.9243115 · Cited by 25
Dehman, A., & Farooq, B. (2021) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2021.103422 · Cited by 25
People with more misconceptions about automated vehicles might be more positive toward them
Liu, P., Du, M., Xu, Z., & Chu, Y. (2022) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2022.04.010 · Cited by 25
Understanding the value of autonomous vehicles – an empirical meta-synthesis
Huda, F. Y., Currie, G., & Kamruzzaman, M. (2023) · Transport Reviews · doi:10.1080/01441647.2023.2189324 · Cited by 26
Technological advances relevant to transport – understanding what drives them
Cohen, T., & Jones, P. (2020) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2020.03.002 · Cited by 25
Kumar, G. M. S., Guo, X., Zhou, S., Luo, H., Wu, Q., Liu, Y., Dou, Z., Pan, K., Xu, Y., Yang, H., et al. (2024) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2024.115050 · Cited by 27
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
Projecting adoption of truck powertrain technologies and CO2 emissions in line-haul networks
de la Peña, A. G., Davendralingam, N., Raz, A. K., DeLaurentis, D. A., Shaver, G. M., Sujan, V. A., & Jain, N. (2020) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2020.102354 · Cited by 25
Marzano, V., Tinessa, F., Fiori, C., Tocchi, D., Papola, A., Aponte, D., Cascetta, E., & Simonelli, F. (2022) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2022.07.001 · Cited by 24
Lane, B. W. (2019) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2019.102535 · Cited by 24
Modeling the operational and labor costs of autonomous robotaxi services
Kaplan, L. R., Nurullaeva, L., & Helveston, J. P. (2024) · Transport Policy · doi:10.1016/j.tranpol.2024.10.010 · Cited by 24
Low-Level Automated Light-Duty Vehicle Technologies Provide Opportunities to Reduce Fuel Consumption
Vasebi, S., Hayeri, Y. M., Samaras, C., & Hendrickson, C. T. (2018) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/0361198118796401 · Cited by 24
Maheshwari, T., & Axhausen, K. W. (2021) · Sustainability · doi:10.3390/su13063013 · Cited by 26
Baby, T. V., Bhattacharyya, V., Shahri, P. K., Ghasemi, A. H., & HomChaudhuri, B. (2021) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2021.103476 · Cited by 23
Demand Exploration of Automated Mobility On-Demand Services Using an Innovative Simulation Tool
Nahmias–Biran, B.-H., Dadashev, G., & Levi, Y. (2022) · IEEE Open Journal of Intelligent Transportation Systems · doi:10.1109/ojits.2022.3197709 · Cited by 23
Peng, J., Zhang, F., Coskun, S., Hu, X., Yang, Y., Langari, R., & He, J. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3305491 · Cited by 23
Autonomous taxis & public health: High cost or high opportunity cost?
Nunes, A., & Hernandez, K. D. (2020) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2020.05.011 · Cited by 29
Impact of autonomous vehicles on long-distance travel mode and destination choices in Texas
Paithankar, P., Vellimana, M., & Kockelman, K. M. (2025) · Research in Transportation Economics · doi:10.1016/j.retrec.2025.101521 · Cited by 23
Optimal purchase subsidy design for human-driven electric vehicles and autonomous electric vehicles
Chen, S., Wang, H., & Meng, Q. (2020) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2020.102641 · Cited by 24
Guan, J., Zhang, S., D’Ambrosio, L. A., Zhang, K., & Coughlin, J. F. (2021) · Sustainability · doi:10.3390/su13147632 · Cited by 26
Saleem, M. A., Ismail, H., & Ali, R. A. (2021) · Sustainability · doi:10.3390/su13179662 · Cited by 22
Matalqah, I., Shatanawi, M., Alatawneh, A., & Mészáros, F. (2022) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/03611981221095526 · Cited by 22
Guo, L., Sun, M., Hu, Y., & Chen, H. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3269566 · Cited by 22
Khanna, N. Z., Zhang, J., Lu, H., Feng, W., Johnson-Wang, M., & Zhou, N. (2023) · Energy Research & Social Science · doi:10.1016/j.erss.2023.103115 · Cited by 23
Autonomous vehicle adoption: use phase environmental implications
Kontar, W., Ahn, S., & Hicks, A. (2021) · Environmental Research Letters · doi:10.1088/1748-9326/abf6f4 · Cited by 22
Debbaghi, F.-Z., Rombaut, E., & Vanhaverbeke, L. (2024) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2024.10.003 · Cited by 23
Operational speed strategy opportunities for autonomous trucking on highways
Bray, G., & Cebon, D. (2022) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2022.01.014 · Cited by 21
Ranking preferences towards adopting autonomous vehicles based on peer inputs and advertisements
Sharma, I., & Mishra, S. (2022) · Transportation · doi:10.1007/s11116-022-10304-w · Cited by 22
Choi, S., Kim, D., Ko, J., Park, J., & Ko, Y. (2022) · International Journal of Urban Sciences · doi:10.1080/12265934.2023.2165531 · 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
Assessing safety functionalities in the design and validation of driving automation
Coppola, A., D’Aniello, C., Pariota, L., & Bifulco, G. N. (2023) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2023.104243 · Cited by 21
Jiang, L., Chen, H., & Paschalidis, E. (2023) · Transport Policy · doi:10.1016/j.tranpol.2023.07.029 · Cited by 21
Transportation Sustainability Follows From More People in Fewer Vehicles, Not Necessarily Automation
Merlin, L. A. (2019) · Journal of the American Planning Association · doi:10.1080/01944363.2019.1637770 · Cited by 21
The role of the US in the geopolitics of climate policy and stranded oil reserves
Jaffe, A. M. (2016) · Nature Energy · doi:10.1038/nenergy.2016.158 · Cited by 21
Psychological consequences of legal responsibility misattribution associated with automated vehicles
Liu, P., Du, M., & Li, T. (2021) · Ethics and Information Technology · doi:10.1007/s10676-021-09613-y · Cited by 20
Energy Efficient Maneuvering of Connected and Automated Vehicles
Rengarajan, S. B., Hotz, S., Sarlashkar, J., Gankov, S., Bhagdikar, P., Gross, M. C., & Hirsch, C. J. (2020) · SAE International Journal of Advances and Current Practices in Mobility · doi:10.4271/2020-01-0583 · Cited by 20
Synthesizing neighborhood preferences for automated vehicles
Zhang, W., Wang, K., Wang, S., Jiang, Z., Mondschein, A. S., & Noland, R. B. (2020) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2020.102774 · Cited by 23
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 22
Longitudinal Vehicle Motion Prediction in Urban Settings With Traffic Light Interaction
Wegener, M., Herrmann, F., Koch, L., Savelsberg, R., & Andert, J. (2021) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2021.3114156 · Cited by 20
Higueras-Castillo, E., García-Maroto, I., Muñoz-Leiva, F., & Liébana-Cabanillas, F. J. (2022) · Research in Transportation Business & Management · doi:10.1016/j.rtbm.2022.100878 · Cited by 21
Delfa, A. L., & Han, Z. (2025) · Sustainability · doi:10.3390/su17073092 · Cited by 22
Parenting - Empirical Advances and Intervention Resources
Benedetto, L., & Ingrassia, M. (2018) · InTech eBooks · doi:10.5772/63688 · Cited by 25
Dynamic Four-Step Planning Model of Empty Repositioning Trips for Personal Autonomous Vehicles
Levin, M. W., Smith, H., & Boyles, S. D. (2019) · Journal of Transportation Engineering Part A Systems · doi:10.1061/jtepbs.0000235 · Cited by 20
Maladaptive Planning and the Pro-Innovation Bias: Considering the Case of Automated Vehicles
Ferreira, A., von Schönfeld, K. C., Tan, W. G. Z., & Papa, E. (2020) · Urban Science · doi:10.3390/urbansci4030041 · Cited by 22
Travelers’ preferences regarding autonomous mobility in the State of Qatar
Alhajyaseen, W., Adnan, M., Abuhejleh, A., Onat, N. C., & Tarlochan, F. (2020) · Personal and Ubiquitous Computing · doi:10.1007/s00779-020-01407-1 · Cited by 19
Wang, Y., Hao, H., & Wang, C. (2022) · Journal of Management in Engineering · doi:10.1061/(asce)me.1943-5479.0001021 · Cited by 19
Opportunities, Challenges, and Uncertainties in Urban Road Transport Automation
Shladover, S. E. (2022) · Sustainability · doi:10.3390/su14031853 · Cited by 19
Guo, T., Chen, J., & Liu, P. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192215077 · Cited by 19
Optimal Deployment of an Equitable Cav Platoonable Corridor On Road Networks with Mixed Traffic Flow
Zhu, D., Xie, T., Liu, Y., Zou, B., & Rujeerapaiboon, N. (2023) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2023.104399 · Cited by 19
Sabet, S., & Farooq, B. (2025) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2025.104385 · Cited by 19
Exploring the mobility and energy implications of shared versus private autonomous vehicles
Auld, J., de Souza, F., Enam, A., Javanmardi, M., Stinson, M. A., Verbas, Ö., & Rousseau, A. P. (2019) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2019.8917125 · Cited by 19
STRANDED ASSETS AND SOVEREIGN STATES
Jaffe, A. M. (2020) · National Institute Economic Review · doi:10.1017/nie.2020.4 · Cited by 21
How will vehicle automation and electrification affect the automotive maintenance, repair sector?
Grosso, M., Raileanu, I. C., Krause, J., Raposo, M. A., Duboz, L., Garus, A., Mourtzouchou, A., & Ciuffo, B. (2021) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2021.100495 · Cited by 19
Zhou, M., & Yi, H. (2025) · Research in Transportation Business & Management · doi:10.1016/j.rtbm.2025.101352 · Cited by 18
Golbabaei, F., Yiğitcanlar, T., Paz, A., & Bunker, J. M. (2023) · Sustainability · doi:10.3390/su151511839 · Cited by 20
Liu, C., Chen, K., Bao, Z., Ng, S. T., Zhang, C., & Jiang, Z. (2023) · Sustainable Cities and Society · doi:10.1016/j.scs.2023.104904 · Cited by 18
McDonnell, K., Murphy, F., Sheehan, B., Masello, L., Castignani, G., & Ryan, C. (2021) · Sensors · doi:10.3390/s21103517 · Cited by 19
Fernandes, P., Bandeira, J. M., & Coelho, M. C. (2021) · Journal of Intelligent Transportation Systems · doi:10.1080/15472450.2021.1945453 · Cited by 20
Hosseinian, S. M., Mirzahossein, H., & Guzik, R. (2024) · Sustainability · doi:10.3390/su16146239 · Cited by 25
Effect of adaptive cruise control on fuel consumption in real-world driving conditions
Moawad, A., Zebiak, M., Han, J., Karbowski, D., Zhang, Y., & Rousseau, A. P. (2024) · Nature Communications · doi:10.1038/s41467-024-54066-8 · Cited by 17
Drive and car tourism: a perspective article
Prideaux, B. R. (2019) · Tourism Review · doi:10.1108/tr-05-2019-0162 · Cited by 17
Blas, F., Giacobone, G., Massin, T., & Touron, F. R. (2020) · Research in Transportation Business & Management · doi:10.1016/j.rtbm.2020.100566 · Cited by 18
Impact of Connected Automated Buses in a Mixed Fleet Scenario With Connected Automated Cars
Sinha, A., Bassil, D., Chand, S., Virdi, N., & Dixit, V. V. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3109142 · Cited by 17
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
Energy-Based Assessment and Driving Behavior of ACC Systems and Humans Inside Platoons
Apostolakis, T., Makridis, M., Kouvelas, A., & Ampountolas, K. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3285296 · Cited by 17
The illusion of the shared electric automated mobility transition
Milakis, D., & Seibert, D. (2024) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2024.101171 · Cited by 19
Fuel economy assessment of semi-autonomous vehicles using measured data
Pourabdollah, M., Bjärkvik, E., Fürer, F., Lindenberg, B., & Burgdorf, K. (2017) · IEEE Transportation Electrification Conference and Expo · doi:10.1109/itec.2017.7993365 · Cited by 17
Hwang, H., & Song, C. (2019) · Environmental Engineering Research · doi:10.4491/eer.2019.117 · Cited by 17
Pucihar, A., Zajc, I., Sernec, R., & Lenart, G. (2019) · Sustainability · doi:10.3390/su11154095 · Cited by 17
Traffic Simulation of Future Intelligent Vehicles in Duisburg City Inner Ring
Ma, X., Hu, X., Weber, T., & Schramm, D. H. (2020) · Applied Sciences · doi:10.3390/app11010029 · Cited by 17
Health Impact Assessment of Connected and Autonomous Vehicles in San Francisco, Bay Area
Pourrahmani, E., Jaller, M., Maizlish, N. A., & Rodier, C. J. (2020) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/0361198120942749 · Cited by 17
Zhang, Y., Shi, X., Shao, Y., Shiwakoti, N., Zhang, J., Pu, Z., & Ye, Z. (2025) · Accident Analysis & Prevention · doi:10.1016/j.aap.2025.107994 · Cited by 18
Metadata
- Authors
- Wadud, Z., MacKenzie, D., & Leiby, P.
- Affiliations
- University of Leeds (GB)
- University of Washington (US)
- Oak Ridge National Laboratory (US)
- Corresponding author
- Wadud, Zia
- Venue
- Transportation Research Part A: Policy and Practice
- Publisher
- Elsevier BV
- Published
- 2016-04
- Volume
- 86
- Pages
- 1-18
- ISSN
- 0965-8564 (ISSN-L)
- OpenAlex
- W2259684855
- Cited by
- 859
- References
- 52
- Citations by year
- 2026: 34 · 2025: 60 · 2024: 83 · 2023: 81 · 2022: 132 · 2021: 118 · 2020: 133 · 2019: 103 · 2018: 76 · 2017: 29 · 2016: 10
- FWCI
- 63.33
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Transportation Research Part A Policy and Practice (publishedVersion, cc-by-nc-nd)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- U.S. Department of Transportation
- Imperial College London
- Federal Highway Administration
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Vehicle emissions and performance
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Energy, Environment, and Transportation Policies
- Social Sciences › Transportation › Transportation and Mobility Innovations
- Keywords
- highly automated vehicles, autonomous vehicles, travel demand, vehicle energy consumption, greenhouse gas emissions, energy decomposition analysis, partial automation, full automation, vehicle design, fuel selection, heavy vehicles, light-duty vehicles, road transport emissions, energy policy
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