Developing Policy for Urban Autonomous Vehicles: Impact on Congestion
Open accessAbstract
An important problem for surface transport is road traffic congestion, which is ubiquitous and difficult to mitigate. Accordingly, a question for policymakers is the possible impact on congestion of autonomous vehicles. It seems likely that the main impact of vehicle automation will not be seen until driverless vehicles are sufficiently safe for use amid general traffic on urban streets. Shared use driverless vehicles could reduce the cost of taxis and a wider range of public transport vehicles could be economic. Individually owned autonomous vehicles would have the ability to travel unoccupied and may need to be regulated where this might add to congestion. It is possible that autonomous vehicles could provide mobility services at lower cost and wider scope, such that private car use in urban areas could decline and congestion reduce. City authorities should be alert to these possibilities in developing transport policy.
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The safety of AVs for use in congested metropolitan streets is acknowledged, underscoring the requirement for restrictions to ensure their safety and dependability before integration into regular city traffic.
“The safety of AVs for use in congested metropolitan streets is acknowledged, underscoring the requirement for restrictions to ensure their safety and dependability before integration into regular city traffic [66].”
From Assessing the Role of Autonomous Vehicles in Urban Areas: A Systematic Review of Literature (2024) · cites this paper as [66]
The Introduction says AV models must demonstrate safe operation and that authorities are expected to set safety standards before general use. Section 3 adds that demonstrating safe operation on urban streets may be demanding. The paper does not establish that AVs are already safe for congested metropolitan streets; its proposed regulation of AV use in congested urban areas in the Conclusions concerns traffic, not safety or dependability. (LLM, conf=0.84)
Experimental — accuracy not yet measuredShared-use AVs present opportunities to lower taxi costs and enhance economic effectiveness in public transportation.
“Shared-use AVs present opportunities to lower taxi costs and enhance economic effectiveness in public transportation [66].”
From Assessing the Role of Autonomous Vehicles in Urban Areas: A Systematic Review of Literature (2024) · cites this paper as [66]
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Research works printed but not linked: 26
- Atkins. Research on the Impacts of Connected and Autonomous Vehicles on Traffic Flow: Evidence Review; Atkins Ltd. & Department for Transport: London, UK, 2016.
- Cavoli, C.; Phillips, B.; Cohen, T.; Jones, P. Social and Behavioural Questions Associated with Automated Vehicles. A Literature Review; Department for Transport: London, UK, 2017.
- Clark, B.; Parkhurst, G.; Ricci, M. Understanding the Socioeconomic Adoption Scenarios for Autonomous Vehicles: A Literature Review; Project Report; University of the West of England: Bristol, UK, 2016.
- Fagnant, D.; Kockelman, K. Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendation. Transp. Res. Part A 2015, 77, 167-181. [CrossRef] · DOI · Paper page
- Lipson, H.; Kurman, M. Driverless: Intelligent Cars and the Road Ahead; The MIT Press: Cambridge, MA, USA, 2016.
- Milakis, D.; van Arem, B.; van Wee, B. Policy and society related implications of automated driving: A review of literature and directions for future research. J. Intell. Transp. Syst. 2017, 21, 324-348. [CrossRef] · DOI · Paper page
- Nikitas, A.; Kougias, I.; Alyavina, E.; Njoya Tchouamou, E. How Can Autonomous and Connected Vehicles, Electromobility, BRT, Hyperloop, Shared Use Mobility and Mobility-As-A-Service Shape Transport Futures for the Context of Smart Cities? Urban Sci. 2017, 1, 36. [CrossRef] · DOI
- Papa, E.; Ferreira, A. Sustainable Accessibility and the Implementation of Automated Vehicles: Identifying Critical Decisions. Urban Sci. 2018, 2, 5. [CrossRef] · DOI · Paper page
- Thomopoulos, N.; Givoni, M. The autonomous car-A blessing or a curse for low carbon mobility? An exploration of likely vs. desirable outcomes. Eur. J. Futures Res. 2015, 3, 14. [CrossRef] · DOI
- Givoni, M. Re-assessing the Results of the London Congestion Charging Scheme. Urban Stud. 2012, 49, 1089-1105. [CrossRef] · DOI
- Milam, R.; Birnbaum, M.; Ganson, C.; Handy, S.; Walters, J. Closing the induced vehicle travel gap between research and practice. Transp. Res. Rec. J. Transp. Res. Board 2017, 2653, 10-16. [CrossRef] · DOI
- Duranton, G.; Turner, M. The Fundamental Law of Road Congestion: Evidence from US Cities. Am. Econ. Rev. 2011, 101, 2616-2652. [CrossRef] · DOI
- Metz, D. The Myth of Travel Time Saving. Transp. Rev. 2008, 28, 321-336. [CrossRef] · DOI
- Mokhtarian, P.; Chen, C. TTB or not TTB, that is the question: A review of the empirical literature on travel time (and money) budgets. Transp. Res. Part A 2004, 38, 643-675. [CrossRef] · DOI
- Schafer, A. Regularities in travel demand: An international perspective. J. Transp. Stat. 2000, 3, 1-31.
- Schafer, A.; Victor, D.G. The future mobility of the world population. Transp. Res. Part A 2000, 34, 171-205. [CrossRef] · DOI
- Childress, S.; Council, P.S.R.; Nichols, B.; Charlton, B.; Coe, S. Using an Activity-Based Model to Explore Possible Impacts of Automated Vehicles. In Proceedings of the Transportation Research Board 94th Annual Meeting, Washington, DC, USA, 11-15 January 2015.
- Harper, D.; Hendrickson, C.; 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 2016, 72, 1-9. [CrossRef] · DOI
- Fagnant, D.J.; Kockelman, K.M. The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios. Transp. Res. Part C 2014, 40, 1-13. [CrossRef] · DOI · Paper page
- Fagant, D.; Kockelman, K.; Bansal, P. Operations of Shared Autonomous Vehicle Fleet for Austin, Texas, Market. Transp. Res. Rec. 2015, 2536, 98-106. [CrossRef] · DOI · Paper page
- Alonso-Mora, J.; Samaranayake, S.; Wallar, A.; Frazzoli, F.; Rus, D. On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment. Proc. Natl. Acad. Sci. USA 2017, 114, 462-467. [CrossRef] [PubMed] · DOI
- Metz, D. Peak Car in the Big City: Reducing London's greenhouse gas emissions. Case Stud. Transp. Policy 2015, 3, 367-371. [CrossRef] · DOI
- Milanes, V.; Shladover, S. Handling Cut-In Vehicles in Strings of Cooperative Adaptive Cruise Control Vehicles. J. Intell. Transp. Syst. 2016, 20, 178-191. [CrossRef] · DOI
- Talebpour, A.; Mahmassani, H.S. Influence of connected and autonomous vehicles on traffic flow stability and throughput. Transp. Res. Part C 2016, 71, 143-163. [CrossRef] · DOI · Paper page
- Zmud, J.; Goodin, G.; Moran, M.; Kalra, N.; Thorn, E. Advancing Automated and Connected Vehicles: Policy and Planning Strategies for State and Local Transportation Agencies; National Academies Press: Washington, DC, USA, 2017.
- Hensher, D. Future bus contracts under mobility as a service (MaaS) regime in the digital age. Are they likely to change? Transp. Res. Part A 2017, 98, 86-96. [CrossRef] · DOI
Cited by
Sorted by citations
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 · see citing works
Addressing EU climate targets: Reducing CO2 emissions using cooperative and automated vehicles
Pribyl, O., Blokpoel, R., & Matowicki, M. (2020) · Transportation Research Part D: Transport and Environment · doi:10.1016/j.trd.2020.102437 · Cited by 41 · see citing works
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- Authors
- Metz, D.
- Affiliations
- University College London (GB)
- Corresponding author
- Metz, David
- ORCID
- Metz, David
- Venue
- Urban Science
- Publisher
- MDPI AG
- Published
- 2018-04-13
- Volume
- 2
- Issue
- 2
- Pages
- 33
- ISSN
- 2413-8851 (ISSN-L)
- OpenAlex
- W2797522824
- Cited by
- 111
- References
- 0
- Citations by year
- 2026: 3 · 2025: 12 · 2024: 25 · 2023: 13 · 2022: 17 · 2021: 13 · 2020: 14 · 2019: 13 · 2018: 1
- FWCI
- 5.45
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Urban Science (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
- Social Sciences › Transportation › Transportation Planning and Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Keywords
- autonomous vehicles, urban traffic congestion, transport policy, shared autonomous vehicles, mobility services, vehicle automation, public transport
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