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3 June 2019

Autonomous Road Vehicles: Challenges for Urban Planning in European Cities

Directorate General for Research and Innovation (DG RTD), European Commission, 1049 Brussels, Belgium

Abstract

Autonomous vehicles will significantly affect mobility conditions in the future. The changes in mobility conditions are expected to have an impact on urban development and, more specifically, on location choices, land use organisation and infrastructure design. Nowadays, there is not enough data for a real-life assessment of this impact. Experts estimate that autonomous vehicles will be available for uptake in the next decade. Therefore, urban planners should consider the possible impacts from autonomous vehicles on cities and the future challenges for urban planning. In this context, the present paper focuses on the challenges from the implementation of autonomous road vehicles for passenger transport in European cities. The analysis is based on a systematic review of research and policy. The main outcome of the analysis is a set of challenges for urban planning regarding the features of urban development, the local and European policy priorities, the current lack of data for planning and the potential for autonomous vehicles to be used by planners as data sources. The paper concludes that tackling these challenges is essential for the full exploitation of the autonomous vehicles’ potential to promote sustainable urban development.

1. Introduction

The World Economic Forum identifies three technological megatrends of the fourth industrial revolution (Industry 4.0), i.e., [1]: i. connectivity; ii. artificial intelligence; iii. flexible automation. The technology of the fully autonomous vehicle (AV) is aligned with these megatrends, especially in the case of connected and autonomous vehicles (CAV), which allow for the communication between vehicles, infrastructure and other road users (V2X connectivity) [2,3].
Scientists believe that the wide-scale implementation of AVs will bring transformative changes in mobility and accessibility, travel patterns, safety and security, energy efficiency, emissions, employment, data availability, governance and business models [4,5,6,7,8]. However, the scarcity of data for the real-life assessment of these changes often leads scientists to uncertain or even controversial conclusions. For example, the estimations regarding the possible impacts of AVs on green house gasses (GHGs) range from an 80% reduction to a threefold increase [9].
National and local governments will have to assess their transport strategy in view of the AV evolution [10]. Furthermore, planning will have to adapt to this uncertain future [11]. Taking into account that the purpose of the transport system is to provide access for people and goods to the locations where activity is conducted [12], it is evident that spatial planning and the organisation of land uses face their own challenges due to the implementation of AVs.
The objective of this paper is to present the possible impacts of AVs on cities in a comprehensive way and to outline the corresponding challenges for urban planning. In particular, the paper focuses on the challenges for urban planning from the wide-scale implementation of autonomous road vehicles for passenger transport in European cities. The analysis refers to autonomous (or driverless) road vehicles of SAE’s Level 5 of automation [13]. These vehicles may be privately owned passenger vehicles, shared-use passenger vehicles or public transport vehicles. In the case of shared-use or public transport CAVs, the vehicles can be enablers of mobility as a service (MaaS), i.e., door-to-door mobility based not on vehicle ownership, but on the integration of publically available transport services [14]. In the context of MaaS, door-to-door mobility is the seamless mobility of people and goods from the origin to the final destination of a journey using a single, integrated service [15].
The international literature does not yet sufficiently address the challenges for planning due to the implementation of AVs [16]. There is, however, a need to address these challenges in a timely manner, as experts estimate that fully autonomous road vehicles will be available for market uptake in the next decade and that they will comprise part of the vehicle fleet by 2050 [17,18,19]. Nowadays, urban planners argue about the ability of AVs to contribute to their planning objectives, while the cities of the future will probably have to find ways to adapt to the emergence of autonomous mobility, i.e., the mobility that is based on autonomous vehicles [20,21]. The thorough understanding and tackling of the challenges for urban planning is particularly relevant to Europe, where urban areas account for 70% of the population (with an estimation of an increase to 80% by 2050), 80% of the energy consumption and 85% of the gross domestic product (GDP) [22].
European cities present different features concerning the relation between urban development and transport in comparison to cities in other regions of the world. There are over 800 cities with more than 50,000 inhabitants in Europe. Approximately 85% of them have a population between 50,000 to 250,000 inhabitants. Only four cities in the European Union are included in the 80 most populated cities in the world. Asian and Latin American cities are in the top five of the specific list [23,24]. The public transport system plays a key role in the development of European cities since the 1800s. As a result, they are more compact and dense in comparison to the cities of North America and other regions of the world that relied on the private car to service their mobility needs [25]. The average population density of cities in Europe is 3000 inhabitants per km2 and equal to the minimum density to sustain efficient public transport. The average density of cities in North America is almost half this density [26]. The relatively high density of European cities is often combined with mixed land uses, which relate to shorter daily trips and higher shares of public and active transport. Furthermore, many European cities date back to classical antiquity, the Roman Empire or the Middle Ages and thus, accommodate historical centres with limited roadway capacity and areas with restricted access to private cars. The present paper outlines the challenges for urban planning in the context of the above specific features in European cities. However, these challenges can be adjusted to the characteristics of urban areas in other regions of the world.
In order to outline the challenges for urban planning due to the implementation of AVs in European cities, the present paper addresses the following questions:
  • What are the possible impacts from autonomous road vehicles on urban development?
  • How is the concept of the autonomous road vehicle integrated into the policy priorities for sustainable urban development?
  • What are the challenges linked to the lack of data about the impacts from autonomous road vehicles on urban development; what are the opportunities from the use of the autonomous road vehicles as data sources for urban planning?
The impacts from the wide-scale implementation of AVs on European cities depend on the features of each city and its transport system. They also depend on the urban development policy, either at the level of local priorities or at the level of common goals for the European Union and its member states. Furthermore, they depend on the specific type of AV to be implemented (AVs for private, shared and/or public transport, with or without V2X connectivity). Under these complex conditions, urban planners should combine different sources of data, exchange information and create strategic synergies in order to:
  • Assess the possible impacts of autonomous vehicles on urban areas.
  • Integrate autonomous mobility solutions to urban planning in order to support the specific needs of the examined city and to achieve the common goals for socio-economic and environmental sustainability.

2. Methodological Approach

The analysis of the present paper is based on the systematic review of research literature and policy documentation. The review was conducted in three parts:
  • First, the review of research literature was directed towards the potential impacts of the autonomous road vehicles on urban mobility and accessibility conditions. Then, the possible effects of these impacts on the features of urban development were explored.
  • Taking into account that planning is in line with specific policy goals, a review of policy documentation and relevant literature was conducted to investigate the relation between AVs and the policy priorities for urban development, with focus on sustainable development.
  • A separate part of the literature review addressed the issue of data, both in terms of the absence of sufficient data for evidence-based planning today and in terms of the future contribution of AVs to big data, i.e., large data sets that are characterised by high volume, variety, velocity and veracity [27].
The findings from each part of the literature review led to the outline of specific challenges for urban planning. These challenges are summarised in tables at the end of each subsection and synthesised in the form of conclusive remarks.

4. Conclusive Remarks

According to the literature, autonomous vehicles (AVs) are expected to be ready for market uptake in the next decade and to bring transformative changes in the mobility and accessibility conditions of urban areas. These changes will affect the features of urban development. More specifically, the wide-scale implementation of AVs will affect the location choices of households and firms, the availability of public space and the access to areas with poor roadway characteristics. This will create potential for the reorganisation of land uses. Furthermore, new opportunities are expected for the innovative design of urban infrastructure as well as for the integration of the AV network into the energy network, in the case of electric AVs, and to the telecommunication network, in the case of connected and automated driving (CAD). CAD is also related to the potential of using the AVs as sources of big data for urban planners.
The above impacts and opportunities will affect the social, economic and environmental pillars of sustainable urban development. In order for urban planners to better prepare for these changes, they should focus on the understanding of the relation between autonomous mobility and sustainable development and on the assessment of the specific impacts from AVs on their cities. In this way, they will be able to take full advantage of the potential benefits from autonomous mobility and improve the synergies between cities, AV developers and operators, data managers and the research community.

Disclaimer

The information and views set out in this article are those of the author and do not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. World Economic Forum. The Next Economic Growth. Engine Scaling Fourth Industrial Revolution Technologies in Production. White Paper. 2018. Available online: http://www3.weforum.org/docs/WEF_Technology_and_Innovation_The_Next_Economic_Growth_Engine.pdf (accessed on 23 April 2019).
  2. Nikitas, A.; Kougias, I.; Alyavina, E.; Tchouamou, E.N. 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. [Google Scholar] [CrossRef]
  3. European Commission. A European Strategy on Cooperative Intelligent Transport Systems, a Milestone towards Cooperative, Connected and Automated Mobility; European Commission: Brussels, Belgium, 2016; COM (2016) 766 final. [Google Scholar]
  4. Das, S.; Sekar, A.; Chen, R.; Kim, H.C.; Wallington, T.J.; William, E. Impacts of autonomous vehicles on consumers time-use patterns. Challenges 2017, 8, 32. [Google Scholar] [CrossRef]
  5. Charness, N.; Yoon, J.S.; Souders, D.; Stothart, C.; Yehnert, C. Predictors of attitudes toward autonomous vehicles: The roles of age, gender, prior knowledge, and personality. Front. Psychol. 2018, 9, 2589. [Google Scholar] [CrossRef] [PubMed]
  6. Pettigrew, S.; Fritschi, L.; Norman, R. The potential implications of autonomous vehicles in and around the workplace. Int. J. Environ. Res. Public Health 2018, 15, 1876. [Google Scholar] [CrossRef] [PubMed]
  7. Bonnefon, J.F.; Shariff, A.; Rahwan, I. The social dilemma of autonomous vehicles. Science 2016, 352, 1573–1576. [Google Scholar] [CrossRef] [PubMed]
  8. Papa, E.; Ferreire, A. Sustainable accessibility and the implementation of automated vehicles: Identifying critical decisions. Urban Sci. 2018, 2, 5. [Google Scholar] [CrossRef]
  9. Greenblatt, J.; Shaheen, S. Automated vehicles, on-demand mobility, and environmental. Curr. Sustain. Renew. Energy Rep. 2015, 2, 74–81. [Google Scholar] [CrossRef]
  10. Thomopoulos, N.; Givoni, M. The autonomous car—A blessing or a curse for the future of low carbon mobility? An exploration of likely vs. desirable outcomes. Eur. J. Futures Res. 2015, 3, 14. [Google Scholar] [CrossRef]
  11. Litman, T. Autonomous vehicle implementation predictions implications for transport planning. In Proceedings of the Transportation Research Board 94th Annual Meeting, Washington, DC, USA, 11–15 January 2015. [Google Scholar]
  12. Rodrigue, J.P. The Geography of Transport Systems, 4th ed.; Routledge: New York, NY, USA, 2017. [Google Scholar]
  13. SAE International. Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles; SAE International: Hong Kong, China, 2016. [Google Scholar]
  14. Door to Door: Combined Mobility and the Changing Transit Landscape. Available online: https://transitleadership.org/docs/TLS-WP-Combined-Mobility.pdf (accessed on 24 May 2019).
  15. Jittrapirom, P.; Caiati, V.; Feneri, A.; Ebrahimigharehbaghi, S.; Alonso-Gonzalez, M.J.; Narayan, J. Mobility as a service: A critical review of definitions, assessments of schemes, and key challenges. Urban Plan. 2017, 2, 13–25. [Google Scholar] [CrossRef]
  16. Riggs, W. (Ed.) Disruptive Transport: Driverless Cars, Transport Innovation and the Sustainable City of Tomorrow, 1st ed.; Routledge: New York, UY, USA, 2018. [Google Scholar]
  17. International Transport Forum. Managing the Transition to Driverless Road Freight Transport; Case Specific Policy Analysis; OECD: Paris, France, 2017. [Google Scholar]
  18. European Commission. Gear 2030. High Level Group on the Competitiveness and Sustainable Growth of the Automotive Industry in the European Union; European Union: Brussels, Belgium, 2017. [Google Scholar]
  19. Bansal, P.; Kockelman, K.M. Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies. Transp. Res. Part A Policy Pract. 2017, 95, 49–63. [Google Scholar] [CrossRef]
  20. Bayer, M.; Frank, N.; Valerius, J. Becoming an Urban Planner; Wiley: Hoboken, NJ, USA, 2010. [Google Scholar]
  21. Chen, A.; Shaheen, S. Planning for Shared Mobility; American Planning Association: Chicago, IL, USA, 2016. [Google Scholar]
  22. Fraedrich, E.; Heinrichs, D.; Cyganski, R.; Birke, F.B. Self-driving cars and city planning: Expectations and Policy Implications. In Proceedings of the 2016 European Transport Conference, Barcelona, Spain, 5–7 October 2016. [Google Scholar]
  23. Eurostat. Urban Europe. Statistics on Cities, Towns and Suburbs; Publications Office of the European Union: Luxembourg, 2016. [Google Scholar]
  24. Cities in Europe Facts and Fgures on Cities and Urban Areas. Available online: https://ec.europa.eu/futurium/en/system/files/ged/pbl_2016_cities_in_europe_23231.pdf (accessed on 22 May 2019).
  25. Muller, P.O. Transportation and urban form: Stages in the spatial evolution of the American metropolis. In The Geography of Urban Transportation, 2nd ed.; Hanson, S., Ed.; Guilford: New York, NY, USA, 1995. [Google Scholar]
  26. European Commission, UN Habitat. The State of European Cities 2016. Cities Leading the Way to a Better Future; Publications Office of the European Union: Luxembourg, 2016. [Google Scholar]
  27. Hilbert, M. Big data for development: A review of promises and challenges. Dev. Policy Rev. 2016, 34, 135–174. [Google Scholar] [CrossRef]
  28. Mobility 2030: Transforming the Mobility Landscape. Available online: https://assets.kpmg/content/dam/kpmg/xx/pdf/2019/02/mobility-2030-transforming-the-mobility-landscape.pdf (accessed on 20 May 2019).
  29. International Transport Forum. Safer Roads with Automated Vehicles? OECD: Paris, France, 2018. [Google Scholar]
  30. Urban Development. Available online: https://ec.europa.eu/regional_policy/en/policy/themes/urban-development/ (accessed on 23 April 2019).
  31. Meyer, J.; Becker, H.; Bösch, P.; Axhausen, K.W. Autonomous vehicles: The next jump in accessibilities? Res. Transp. Econ. 2017, 62, 80–91. [Google Scholar] [CrossRef]
  32. Heinrichs, D. Autonomous driving and urban land use. In Autonomous Driving, 1st ed.; Maurer, M., Gerdes, C., Lenz, B., Winner, H., Eds.; Springer: New York, NY, USA, 2016. [Google Scholar]
  33. Piao, J.; McDonald, M.; Hounsell, N.; Graindorge, M.; Graindorge, T.; Malhene, N. Public views towards implementation of automated vehicles in urban areas. In Proceedings of the 6th Transport Research Arena, Warsaw, Poland, 18–21 April 2016. [Google Scholar]
  34. European Commission; European Environment Agency. Urban Sprawl in Europe—The Ignored Challenge; Office for Official Publications of the European Communities: Luxembourg, 2006. [Google Scholar]
  35. Hawkins, J.; Habib, K.N. Integrated models of land use and transportation for the autonomous vehicle revolution. Transp. Rev. 2019, 39, 66–83. [Google Scholar] [CrossRef]
  36. Fagnant, D.J.; Kockelman, K. Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendations. Transp. Res. Part A Policy Pract. 2015, 77, 167–181. [Google Scholar] [CrossRef]
  37. How Autonomous Vehicles Could Relieve or Worsen Traffic Congestion. Available online: https://www.here.com/sites/g/files/odxslz166/files/2018-12/HERE_How_autonomous_vehicles_could_relieve_or_worsen_traffic_congestion_white_paper.pdf (accessed on 20 May 2019).
  38. Soteropoulos, A.; Berger, M.; Ciari, F. Impacts of automated vehicles on travel behaviour and land use: An international review of modelling studies. Transp. Rev. 2019, 39, 29–49. [Google Scholar] [CrossRef]
  39. Metz, D. Developing policy for urban autonomous vehicles: Impact on congestion. Urban Sci. 2018, 2, 33. [Google Scholar] [CrossRef]
  40. Parkin, J.; Clark, B.; Clayton, W.; Ricci, M.; Parkhurst, G. Autonomous vehicle interactions in the urban street environment: A research agenda. Proc. Inst. Civ. Eng. Munic. Eng. 2018, 171, 15–25. [Google Scholar] [CrossRef]
  41. Friedrich, B. The effect of autonomous vehicles on traffic. In Autonomous Driving, 1st ed.; Maurer, M., Gerdes, C., Lenz, B., Winner, H., Eds.; Springer: New York, NY, USA, 2016. [Google Scholar]
  42. Guidelines for Road Traffic Noise Abatement. Available online: http://ec.europa.eu/environment/life/project/Projects/index.cfm?fuseaction=home.showFile&rep=file&fil=SMILE_guidelines_noise_en.pdf (accessed on 27 April 2019).
  43. Driverless Cars Increase Congestion—But Could Cut Massive Parking Times. Available online: https://www.transportenvironment.org/news/driverless-cars-increase-congestion-%E2%80%93-could-cut-massive-parking-times (accessed on 20 May 2019).
  44. Traffic Calming in Three European Cities. Lessons from Zurich, Vienna and Munich. Available online: https://www.spur.org/publications/urbanist-article/2004-09-01/traffic-calming-three-european-cities (accessed on 27 April 2019).
  45. Parking Management and Mobility Management. Available online: http://www.epomm.eu/newsletter/v2/content/2015/0615_2/doc/eupdate_en.pdf (accessed on 27 April 2019).
  46. Ruso, A.; van Ommeren, J.; Dimitropoulos, A. The Environmental and Welfare Implications of Parking Policies; Environment Working Paper No. 145; OECD: Paris, France, 2019. [Google Scholar]
  47. Nourinejad, M.; Bahram, S.; Roorda, M.J. Designing parking facilities for autonomous vehicles. Transp. Res. Part B Methodol. 2018, 109, 110–127. [Google Scholar] [CrossRef]
  48. Zhang, W.; Guhathakurta, S. Parking spaces in the age of shared autonomous vehicles: How much parking will we need and where? In Proceedings of the 96th Transportation Research Board Meeting, Washington DC, USA, 8–12 January 2017. [Google Scholar]
  49. Bösch, P.M.; Becker, F.; Becker, H.; Axhausen, K.W. Cost-based analysis of autonomous mobility services. Transp. Policy 2018, 64, 76–91. [Google Scholar] [CrossRef]
  50. Albino, V.; Berardi, U.; Dangelico, R.M. Smart cities: Definitions, dimensions, performance, and initiatives. J. Urban Technol. 2015, 22, 3–21. [Google Scholar] [CrossRef]
  51. Carreras, A.; Daura, X.; Erhart, J.; Ruehrup, S. Road infrastructure support levels for automated driving. In Proceedings of the 25th ITS World Congress, Copenhagen, Denmark, 17–21 September 2018. [Google Scholar]
  52. Russo, F.; Rindone, C.; Panuccio, P. The process of smart city definition at an EU level. WIT Trans. Ecol. Environ. 2014, 191, 979–989. [Google Scholar]
  53. Lytrivis, P.; Papanikolaou, E.; Amditis, A.; Dirnwöber, M.; Froetscher, A.; Protzmann, R.; Rom, W.; Kerschbaumer, A. Advances in road infrastructure, both physical and digital, for mixed vehicle traffic flows. In Proceedings of the 7th Transport Research Arena, Vienna, Austria, 16–19 April 2018. [Google Scholar]
  54. World Economic Forum. Electric Vehicles for Smarter Cities: The Future of Energy and Mobility. Available online: http://www3.weforum.org/docs/WEF_2018_%20Electric_For_Smarter_Cities.pdf (accessed on 24 April 2019).
  55. Christie, D.; Koymans, A.; Chanard, T.; Lasgouttes, J.M.; Kauffmann, V. Pioneering driverless electric vehicles in Europe: The City Automated Transport System (CATS). In Proceedings of the European Transport Conference 2015, Frankfurt, Germany, 28–30 September 2015. [Google Scholar]
  56. European Commission. A Sustainable Europe for a Better World: A European Union Strategy for Sustainable Development; European Commission: Brussels, Belgium, 2001; COM (2001) 264 final. [Google Scholar]
  57. Report of the World Commission on Environment and Development: Our Common Future. Available online: https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf (accessed on 25 April 2019).
  58. European Commission. A Framework Strategy for a Resilient Energy Union with a Forward-Looking Climate Change Policy; European Commission: Brussels, Belgium, 2015; COM (2015) 80 final. [Google Scholar]
  59. Paris Agreement. Available online: https://unfccc.int/sites/default/files/english_paris_agreement.pdf (accessed on 25 April 2019).
  60. United Nations. Transforming Our World. The 2030 Agenda for Sustainable Development. Available online: https://sustainabledevelopment.un.org/content/documents/21252030%20Agenda%20for%20Sustainable%20Development%20web.pdf (accessed on 25 April 2019).
  61. European Commission. Europe 2020. A Strategy for Smart, Sustainable and Inclusive Growth; European Commission: Brussels, Belgium, 2010; COM (2010) 2020 final. [Google Scholar]
  62. European Commission. White Paper. European Transport Policy for 2010: Time to Decide; European Commission: Brussels, Belgium, 2001; COM (2001) 370 final. [Google Scholar]
  63. European Commission. White Paper. Roadmap to a Single European Transport Area: Towards a Competitive and Resource Efficient Transport System; European Commission: Brussels, Belgium, 2011; COM (2011) 144 final. [Google Scholar]
  64. European Commission. Green Paper. Towards a New Culture for Urban Mobility; European Commission: Brussels, Belgium, 2007; COM (2007) 551 final. [Google Scholar]
  65. European Commission. Together towards Competitive and Resource Efficient Urban Mobility; European Commission: Brussels, Belgium, 2013; COM (2013) 913 final. [Google Scholar]
  66. Establishing the Urban Agenda for the EU. Pact of Amsterdam. Available online: https://ec.europa.eu/futurium/en/system/files/ged/pact-of-amsterdam_en.pdf (accessed on 25 April 2019).
  67. European Commission. On the Road to Automated Mobility: An EU Strategy for Mobility of the Future; European Union: Brussels, Belgium, 2018; COM (2018) 283 final. [Google Scholar]
  68. Wise-Act. Available online: https://wise-act.eu/ (accessed on 25 April 2019).
  69. New Mobility Services. Available online: https://eu-smartcities.eu (accessed on 25 April 2019).
  70. Innovation and Networks Executive Agency; European Commission. ITS Projects Supported by the Connecting Europe Facility & Horizon 2020. Available online: https://ec.europa.eu/inea/sites/inea/files/its_cefh2020_projects_2017.pdf (accessed on 25 April 2019).
  71. European Commission. STRIA Roadmap on Connected and Automated Transport: Road, Rail and Waterborne; European Commission: Brussels, Belgium, 2019. [Google Scholar]
  72. European Commission. Reflection Paper towards a Sustainable Europe by 2030; European Commission: Brussels, Belgium, 2019; COM (2019) 22 final. [Google Scholar]
  73. Heinelt, H. The Role of Cities in the Institutional Framework of the European Union Study for the AFCO Committee; European Parliament: Brussels, Belgium, 2017. [Google Scholar]
  74. European Committee of the Regions. State of Play of Connected and Automated Driving and Future Challenges and Opportunities for Europe’s Cities and Regions. Available online: https://cor.europa.eu/en/engage/studies/Documents/State-of-play-CAM.PDF (accessed on 25 April 2019).
  75. Trilateral Impact Assessment Framework for Automation in Road Transportation. Available online: https://connectedautomateddriving.eu/publication/trilateral-impact-assessment-framework-for-automation-in-road-transportation-2/ (accessed on 21 May 2019).
  76. Joint Research Centre. An Analysis of Possible Socio-Economic Effects of a Cooperative, Connected and Automated Mobility (CCAM) in Europe; Publications Office of the European Union: Luxembourg, 2018. [Google Scholar]
  77. Tettamanti, T.; Varga, I.; Szalay, Z. Impacts of autonomous cars from a traffic engineering perspective. Periodica Polytecnica Transp. Eng. 2016, 44, 244–250. [Google Scholar] [CrossRef]
  78. Betancur, J.J. History and theory of urban planning. In Handbook on Transport and Urban Planning in the Developed World, 1st ed.; Bliemer, M.C.J., Mulley, C., Moutou, C., Eds.; Edward Elgar: Cheltenham, UK; Northampton, MA, USA, 2016. [Google Scholar]
  79. Bessen, J. Toil and technology. Finan. Dev. 2015, 52, 16–19. [Google Scholar]
  80. Hewitt, C.; Amanatidis, T.; Politis, I.; Sarkar, A. Assessing public perception of self-driving cars: The autonomous vehicle acceptance model. In Proceedings of the ACM IUI 2019 Conference, Los Angeles, CA, USA, 16–20 March 2019. [Google Scholar]
  81. Horizon 2020. Work Programme 2018–2020. Smart, Green and Integrated Transport. Available online: https://ec.europa.eu/research/participants/data/ref/h2020/wp/2018-2020/main/h2020-wp1820-transport_en.pdf (accessed on 26 April 2019).
  82. Voege, T.; Zhivov, N. Cooperative mobility systems and automated driving. In Proceedings of the Summary and Conclusions of the ITF Roundtable on Cooperative Mobility Systems and Automated Driving, Ottawa, ON, Canada, 6–7 December 2016. [Google Scholar]
  83. En Route pour la Smart Mobility. Available online: http://www.cjg.be/wp-content/uploads/2016/10/CJG-ETUDE-Smart-Mobility-Site.pdf (accessed on 20 May 2019).
  84. Ranft, F.; Adler, M.; Diamond, P.; Guerrero, E.; Laza, M. Freeing the Road: Shaping the Future for Autonomous Vehicles; Policy Network: London, UK, 2016. [Google Scholar]
  85. Medina, A.; Maulana, A.; Thompson, D.; Shandilya, N.; Almeida, S.; Aaapaoja, A.; Kutila, M.; Merkus, E.; Vervoort, K. Public Support Measures for Connected and Automated Driving; European Commission: Brussels, Belgium, 2017. [Google Scholar]
  86. Future Trends in Mobility: The Rise of the Sharing Economy and Automated Transport. Annex A. Deliverable no. 3.3 of project MIND-sets. Available online: http://www.mind-sets.eu/wordpress/wp-content/uploads/2015/11/D3.3-Future_Trends_in_Mobility_The_rise_of_the_sharing_economy_and_automated_transport_Annex_A.pdf (accessed on 21 May 2019).
  87. Joint Research Centre. The R-Evolution of Driving: From Connected Vehicles to Coordinated Automated Road Transport (C-ART); Publications Office of the European Union: Luxembourg, 2017. [Google Scholar]
  88. Lim, C.; Kim, K.-J.; Maglio, P.P. Smart cities with big data: Reference models, challenges, and considerations. Cities 2018, 82, 86–99. [Google Scholar] [CrossRef]
  89. Eurocities. Integrating Transport Automation in the Urban System. Available online: http://nws.eurocities.eu/MediaShell/media/EUROCITIES_Statement_on_Transport_Automation_in_Urban_Areas_final.pdf (accessed on 25 April 2019).
  90. Funding the Future of Mobility. Available online: https://www2.deloitte.com/insights/us/en/deloitte-review/issue-23/transportation-funding-future-of-mobility.html (accessed on 25 April 2019).
  91. Nikitas, A.; Njoya, E.T.; Dani, S. Examining the myths of connected and autonomous vehicles: Analysing the pathway to a driverless mobility paradigm. Int. J. Automot. Technol. Manag. 2019, 19, 10–30. [Google Scholar] [CrossRef]
  92. Bagloee, S.A.; Tavana, M.; Asadi, M.; Oliver, T. Autonomous vehicles: Challenges, opportunities, and future implications for transportation policies. J. Mod. Transp. 2016, 24, 284–303. [Google Scholar] [CrossRef]

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