An adaptive urban planning framework to support autonomous car technologies

Bezai, N.E. ORCID: 0000-0002-5982-8983, 2022. An adaptive urban planning framework to support autonomous car technologies. PhD, Nottingham Trent University.

Nacer Eddine Bezai 2022.pdf - Published version

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In the last few decades, there has been increased discussion around smart mobility and the development of autonomous vehicles (AVs). The upcoming technology of self-driving vehicles has the potential to improve the quality of urban living and enhance sustainability, but our cities are not yet ready to adopt AVs. The physical infrastructure and legislative frameworks required are not yet in place, and public attitudes towards AVs are unclear. Although a great deal of current discussion revolves around the technical aspects of self-driving vehicles and technological maturity, there is a lack of research examining the full range of barriers to AV adoption and the potential impacts on urban planning. In order to begin to fill this gap, this study explores the barriers to full AV adoption in detail and develops an adaptive urban framework to assist urban planners, citizens, politicians, and stakeholders in their planning decision-making around AVs.

To achieve this aim, the study adopts a mixed-methods research methodology following the multilevel model triangulation research design, with four distinct implementation phases. In Phase One, document analysis and content analysis is carried out to identify and analyse the barriers to the adoption of AVs in today’s cities and to analyse AV vehicle specifications and assess their potential impact on the urban transportation infrastructure. The analysis identifies key barriers in the following areas: 1) Safety; 2) User acceptance; 3) Regulations and ethics; 4) Accurate positioning & mapping; 5) Computer software & hardware; and 6) Communication Systems (Networks). The outcomes of this phase contribute to the development of a framework of barriers to the full adoption of AVs combined with the AV system architecture, tracing their interrelations, and an initial list of recommendations. In Phase Two, a semi-structured survey targeting experts in a range of disciplines associated with AVs is used to validate the framework developed in Phase One and to determine the possible impacts on city planning and transportation infrastructure of a hypothetical journey through the city of Nottingham made by a fully autonomous vehicle (Level 4). This phase reveals that the majority of experts believe that both existing design principles and design guidance will be affected, with street elements such as roundabouts/intersections, zebra crossings, charging points, on-street parking, road signs, and drop points most severely affected. For instance, 61% of experts agree that AVs’ hubs should be in each neighborhood. 19% of experts argue that manual driving should be banned. In Phase Three, a structured survey targeting members of the public in Nottingham is used to analyse current public attitudes and behaviours in respect of AVs and to begin to identify factors which might drive AV adoption in future. 57% of people are expected to share AVs and 64% are expected to own them in the city. In terms of data privacy, 46% of people disagree with sharing their data.
The final phase of the research involves combining the outcomes of the previous phases to create the final adaptive urban planning framework to support future planning decision-making around AVs. A detailed list of recommendations to address the technical, social and legislative barriers identified is also proposed. The study concludes by suggesting avenues for subsequent research to build on these outcomes and further support the adoption of AVs as part of moves to promote smart mobility and enhance the quality of life in our cities.

Item Type: Thesis
Creators: Bezai, N.E.
Date: January 2022
Rights: This work is the intellectual property of NACER EDDINE BEZAI. You may copy up to 5% of this work for private study, or personal, non-commercial research. Any reuse of the information contained within this document should be fully referenced, quoting the author, title, university degree level and pagination. Queries or requests for any other use, or if a more substantial copy is required, should be directed in the owner of the Intellectual Property Rights.
Divisions: Schools > School of Architecture, Design and the Built Environment
Record created by: Linda Sullivan
Date Added: 15 Sep 2022 09:16
Last Modified: 15 Sep 2022 09:16

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