Mobility and Energy Impacts of Shared Automated Vehicles: a Review of Recent Literature

  • Susan ShaheenEmail author
  • Mohamed Amine Bouzaghrane
Transportation (T Donna Chen, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Transportation


Purpose of Review

The purpose of this review is to present findings from recent research on Shared automated vehicles (SAV) impacts on mobility and energy.

Recent Findings

While the literature on potential SAV impacts on travel behavior and the environment is still developing, researchers have suggested that SAVs could reduce transportation costs and incur minimal increases in total trip time due to efficient routing to support pooling. Researchers also speculate that SAVs would result in a 55% reduction in energy use and ~ 90% reduction in greenhouse gas (GHG) emissions.


SAV impacts on mobility and energy are uncertain. Researchers should carefully track SAV technology developments and adjust previous model assumptions based on real-world data to produce better impact estimates. SAVs could prove to be a next technological advancement that reshapes the transportation system by providing a safer, efficient, and less costly travel alternative.


Shared automated vehicles Travel behavior Mobility Greenhouse gases Energy consumption Shared automated vehicle policy 


Compliance with Ethical Standards

Conflict of Interest

Susan Shaheen and Mohamed Amine Bouzaghrane declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.


Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    Broggi A, Bertozzi M, Fascioli A, Conte G. Automatic vehicle guidance: the experience of the ARGO autonomous vehicle. World Sci. 1999. Available at: Accessed 2019 Apr 9].
  2. 2.
    Dickmanns ED. Dynamic vision for perception and control of motion: Springer; 2007.Google Scholar
  3. 3.
    Forrest A, Konca M. Autonomous cars and society. 2007. Available at: Accessed 2019 Apr 9.
  4. 4.
    EUREKA. Programme for a european traffic system with highest efficiency and unprecedented safety | EUREKA. Available at: Accessed 2019 Apr 9.
  5. 5.
    National Highway Traffic Safety Administration (NHTSA). Automated Driving Systems 2.0: A Vision For Safety. 2017. Available at: Accessed 2019 Apr 17.
  6. 6.
    Greenblatt JB, Shaheen S. Automated vehicles, on-demand mobility, and environmental impacts. Curr Sustain Energy Reports. Springer International Publishing. 2015;2:74–81. Scholar
  7. 7.
    Business Insider. Companies making driverless cars by 2020. Available at: Accessed 2019 Apr 9.
  8. 8.
    Engadget. Waymo launches its first commercial self-driving car service. Available at: Accessed 2019 Apr 9.
  9. 9.
    Wired. Elon Musk promises a really truly self-driving Tesla in 2020 | WIRED. Available at: Accessed 2019 Apr 9.
  10. 10.
    Nordhoff S, van Arem B, Happee R. Conceptual model to explain, predict, and improve user acceptance of driverless podlike vehicles. Transp Res Rec J Transp Res Board. 2016;2602:60–7. Scholar
  11. 11.
    Kyriakidis M, Happee R, de Winter JCF. Public opinion on automated driving: Results of an international questionnaire among 5000 respondents. Transp Res Part F Traffic Psychol Behav. Pergamon. 2015;32:127–40. Scholar
  12. 12.
    Schoettle B, Sivak M. A survey of public opinion about autonomous and self-driving vehicles in the U.S., the U.K., and Australia. University of Michigan, Ann Arbor, Transportation Research Institute; 2014. Available at: Accessed 2019 Mar 15.
  13. 13.
    •• Krueger R, Rashidi TH, Rose JM. Preferences for shared autonomous vehicles. Transp Res Part C Emerg Technol. Pergamon. 2016;69:343–55. article provides important insight on service characteristics that could affect the acceptability of SAVs. CrossRefGoogle Scholar
  14. 14.
    Haboucha CJ, Ishaq R, Shiftan Y. User preferences regarding autonomous vehicles. Transp Res Part C Emerg Technol. Pergamon. 2017;78:37–49. Scholar
  15. 15.
    Bansal P, Kockelman KM. Are we ready to embrace connected and self-driving vehicles? A case study of Texans. Transportation (Amst). Springer US. 2018;45:641–75. Scholar
  16. 16.
    Bansal P, Kockelman KM, Singh A. Assessing public opinions of and interest in new vehicle technologies: An Austin perspective. Transp Res Part C Emerg Technol. Elsevier Ltd. 2016;67:1–14. Scholar
  17. 17.
    Nazari F, Noruzoliaee M, Mohammadian A(K). Shared versus private mobility: Modeling public interest in autonomous vehicles accounting for latent attitudes. Transp Res Part C Emerg Technol. 2018;97:456–77. Scholar
  18. 18.
    Lustgarten P, Le Vine S. Public priorities and consumer preferences for selected attributes of automated vehicles. J Mod Transp. Springer. Berlin Heidelberg. 2018;26:72–9. Scholar
  19. 19.
    Liu J, Kockelman KM, Boesch PM, Ciari F. Tracking a system of shared autonomous vehicles across the Austin, Texas network using agent-based simulation. Transportation (Amst). Springer US. 2017;44:1261–78. Scholar
  20. 20.
    Gurumurthy KM, Kockelman KM. Analyzing the dynamic ride-sharing potential for shared autonomous vehicle fleets using cellphone data from Orlando. Florida. Comput Environ Urban Syst. Pergamon. 2018;71:177–85. Scholar
  21. 21.
    • Chen TD, Kockelman KM, Hanna JP. Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions. Transp Res Part A Policy Pract. Elsevier Ltd. 2016;94:243–54. article explores different operational scenarios and presents hurdles to effective SAEV operations. Google Scholar
  22. 22.
    Bauer GS, Greenblatt JB, Gerke BF. Cost, energy, and environmental impact of automated electric taxi fleets in Manhattan. Environ Sci Technol. 2018;52:4920–8. Scholar
  23. 23.
    Chen TD, Kockelman KM. Management of a shared autonomous electric vehicle fleet: implications of pricing schemes. Transp Res Rec J Transp Res Board. 2016;2572:37–46. Scholar
  24. 24.
    Pakusch C, Stevens G, Bossauer P. Shared autonomous vehicles: potentials for a sustainable mobility and risks of unintended effects. ICT4S Epic Ser Comput. 2018:258–45.Google Scholar
  25. 25.
    Shen Y, Zhang H, Zhao J. Integrating shared autonomous vehicle in public transportation system: A supply-side simulation of the first-mile service in Singapore. Transp Res Part A Policy Pract. Pergamon. 2018;113:125–36. Scholar
  26. 26.
    Harper CD, Hendrickson CT, Mangones S, Samaras C. Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions. Transp Res Part C Emerg Technol. Pergamon. 2016;72:1–9. Scholar
  27. 27.
    Harb M, Xiao Y, Circella G, Mokhtarian PL, Walker JL. Projecting travelers into a world of self-driving vehicles: estimating travel behavior implications via a naturalistic experiment. Transportation (Amst). Springer US. 2018;45:1671–85. Scholar
  28. 28.
    Singleton PA. Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively? Transp Rev. 2019;39:50–65. Scholar
  29. 29.
    Chase R. Shared Mobility Principles for Livable Cities. Available at: Accessed 2019 Apr 9.
  30. 30.
    Martin EW, Shaheen SA. Greenhouse gas emission impacts of carsharing in North America. IEEE Trans Intell Transp Syst. 2011;12:1074–86. Scholar
  31. 31.
    Menon N, Barbour N, Zhang Y, Pinjari AR, Mannering F. Shared autonomous vehicles and their potential impacts on household vehicle ownership: An exploratory empirical assessment. Int J Sustain Transp. Taylor & Francis. 2018:1–12. Scholar
  32. 32.
    Stocker A, Shaheen S. Shared automated vehicles: Review of Business Models. 2017. Available at: Accessed 2019 Apr 9.
  33. 33.
    Stocker A, Shaheen S. Shared automated mobility: early exploration and potential impacts. In: Meyer G, Beiker S, editors. Road Veh Autom 4. Cham: Springer; 2018. p. 125–39.CrossRefGoogle Scholar
  34. 34.
    Baum-Snow N. Did Highways Cause Suburbanization? Q J Econ. Narnia. 2007;122:775–805. Scholar
  35. 35.
    Gelauff G, Ossokina I, Teulings C. Spatial and welfare effects of automated driving: Will cities grow, decline or both? Transp Res Part A Policy Pract. 2019;121:277–94. Scholar
  36. 36.
    Ma Q, Kockelman K, Segal M. Making the most of curb spaces in a world of shared autonomous vehicles: a case study of Austin, Texas. Transp Res Board 97th Annu Meet. Available at: Accessed 2019 Apr 9.
  37. 37.
    Zhang W, Guhathakurta S, Fang J, Zhang G. Exploring the impact of shared autonomous vehicles on urban parking demand: An agent-based simulation approach. Sustain Cities Soc. Elsevier B.V. 2015;19:34–45. Scholar
  38. 38.
    Stocker A, Shaheen S. Shared automated vehicle (SAV) pilots and automated vehicle policy in the U.S.: current and future developments. Cham: Springer. p. 131–47. Available at:.
  39. 39.
    Shaheen S. Shared mobility and automation: empirical evidence and policy implications. Available at:
  40. 40.
    •• Shaheen S, Cohen A. Shared ride services in North America: definitions, impacts, and the future of pooling. Transp Rev. Taylor & Francis. 2018:1–16. article highlights the impacts and current understanding of shared-ride services and provides recommendations to governmental agencies for managing the future convergence of shared mobility services and automated vehicles. CrossRefGoogle Scholar
  41. 41.
    Shaheen S. Shared mobility: the potential of ridehailing and pooling. In: Sperling D, editor. Three Revolutions Steer Autom Shared, Electr Veh to a Better Futur. Washington, DC: Island Press/Center for Resource Economics; 2018. p. 55–76.CrossRefGoogle Scholar
  42. 42.
    Forscher T, Bayen A, Shaheen S. Road usage charging (RUC). ITS Berkeley Policy Briefs. 2018.
  43. 43.
    Simoni MD, Kockelman KM, Gurumurthy KM, Bischoff J. Congestion pricing in a world of self-driving vehicles: An analysis of different strategies in alternative future scenarios. Transp Res Part C Emerg Technol. Elsevier. 2019;98:167–85. Scholar
  44. 44.
    Roe M, Toochek C. Curbside management strategies for improving transit reliability crub appeal. 2017. Available at: Accessed 2019 Apr 9.
  45. 45.
    International Transportation Forum. The share-use city: managing the curb. 2018. Available at: Accessed 2019 Apr 9.
  46. 46.
    National Academies of Sciences Medicine and Engineering. Socioeconomic impacts of automated and connected vehicles. Socioecon. Impacts Autom. Connect. Veh. Washington, DC: The National Academies Press; 2019. p. 2019.Google Scholar
  47. 47.
    U.S. Energy Information Administration. Monthly energy review–April 2019. 2019. Available at: .
  48. 48.
    U.S. Environmental Protection Agency. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2017. 1990. Available at: Accessed 2019 Apr 25.
  49. 49.
    Fagnant DJ, Kockelman KM. The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios. Transp Res Part C Emerg Technol. Elsevier Ltd. 2014;40:1–13. Scholar
  50. 50.
    Alonso-Mora J, Samaranayake S, Wallar A, Frazzoli E, Rus D. On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment. Proc Natl Acad Sci. 2017;114:462–7. Scholar
  51. 51.
    Lokhandwala M, Cai H. Dynamic ride sharing using traditional taxis and shared autonomous taxis: A case study of NYC. Transp Res Part C Emerg Technol. Elsevier. 2018;97:45–60. Scholar
  52. 52.
    Zhang W, Guhathakurta S, Fang J, Zhang G. The performance and benefits of a shared autonomous vehicles based 2 dynamic ridesharing system: an agent-based simulation approach. Transp Res Board. 2015;15.Google Scholar
  53. 53.
    Martinez LM, Viegas JM. Assessing the impacts of deploying a shared self-driving urban mobility system: An agent-based model applied to the city of Lisbon. Portugal. Int J Transp Sci Technol. 2017;6:13–27. Scholar
  54. 54.
    Greenblatt JB, Saxena S. Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles. Nat Clim Chang. 2015;5:860–3. Scholar
  55. 55.
    • Wadud Z. Help or hindrance? Travel and energy implications of highly automated vehicles. Transp Res Part A. 2016;86:1–18. article presents estimates of changes in energy consumption due to different mechanisms related to vehicle automation and provides estimates of changes in energy consumption under multiple aumation scenarios. CrossRefGoogle Scholar
  56. 56.
    Lu M, Taiebat M, Xu M, Hsu S-C. Multiagent spatial simulation of autonomous taxis for urban commute: travel economics and environmental impacts. J Urban Plan Dev. 2018;144:04018033. Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Civil and Environmental Engineering and Transportation Sustainability Research CenterUniversity of CaliforniaBerkeleyUSA
  2. 2.Department of Civil and Environmental EngineeringUniversity of CaliforniaBerkeleyUSA

Personalised recommendations