Abstract
Artificial intelligence (AI) is a powerful concept still in its infancy that has the potential, if utilised responsibly, to provide a vehicle for positive change that could promote sustainable transitions to a more resource-efficient livability paradigm. AI with its deep learning functions and capabilities can be employed as a tool which empowers machines to solve problems that could reform urban landscapes as we have known them for decades now and help with establishing a new era; the era of the “smart city”. One of the key areas that AI can redefine is transport. Mobility provision and its impact on urban development can be significantly improved by the employment of intelligent transport systems in general and automated transport in particular. This new breed of AI-based mobility, despite its machine-orientation, has to be a user-centred technology that “understands” and “satisfies” the human user, the markets and the society as a whole. Trust should be built, and risks should be eliminated, for this transition to take off. This paper provides a novel conceptual contribution that thoroughly discusses the scarcely studied nexus of AI, transportation and the smart city and how this will affect urban futures. It specifically covers key smart mobility initiatives referring to Connected and Autonomous Vehicles (CAVs), autonomous Personal and Unmanned Aerial Vehicles (PAVs and UAVs) and Mobility-as-a-Service (MaaS), but also interventions that may work as enabling technologies for transport, such as the Internet of Things (IoT) and Physical Internet (PI) or reflect broader transformations like Industry 4.0. This work is ultimately a reference tool for researchers and city planners that provides clear and systematic definitions of the ambiguous smart mobility terms of tomorrow and describes their individual and collective roles underpinning the nexus in scope.
Highlights
In a time that is dictated, more than ever before, by a need to shift to a more sustainable techno-social paradigm to avoid the adverse repercussions of a resource-intensive and unthoughtfully opportunistic livability philosophy that does not look far in the future, Artificial Intelligence (AI) has the potential to provide a vehicle for transformation
Despite an abundance of quality research studies with a conceptual character that have tried over time to express, describe and prioritise the diverse, versatile and dynamic dimensions incorporated in each of the themes presented in our paper, including AI (e.g., [96,97,98,99,100]), smart city (e.g., [101,102,103,104,105]), Connected and Autonomous Vehicles (CAVs) (e.g., [106,107,108,109]), Unmanned Aerial Vehicles (UAVs) and Personal Aerial Vehicles (PAVs) (e.g., [110,111,112,113]), MaaS (e.g., [114,115,116,117]), Internet of Things (IoT) (e.g., [118,119,120,121]), Physical Internet (PI) (e.g., [122,123,124,125]) and Industry 4.0 (e.g., [126,127,128,129]), there is as yet no clear and universally approved set of definitions that critically underpins the nexus of AI, transport and the smart city
The present work recognises the transformative ability of AI when it comes to the smart city context and how it can be a paradigm-shifting force that will revolutionise mobility in an unprecedented way
Summary
In a time that is dictated, more than ever before, by a need to shift to a more sustainable techno-social paradigm to avoid the adverse repercussions of a resource-intensive and unthoughtfully opportunistic livability philosophy that does not look far in the future, Artificial Intelligence (AI) has the potential to provide a vehicle for transformation. The paper thoroughly discusses the nexus of AI, transportation and the smart city by covering interventions referring to Connected and Autonomous Vehicles (CAVs), Unmanned and Personal Aerial Vehicles (UAVs and PAVs) and Mobility-as-a-Service (MaaS), and the Internet of Things (IoT), Physical Internet (PI) and Industry 4.0, which are three initiatives that may impact transport in direct or indirect ways and are critical parts of the smart city agenda. The paper provides the framework of the research methodology employed, a description of the aforementioned initiatives (a section for each of them) and a final section that serves as a lexicon for the concepts considered in the previous sections This last part of the paper is about elaborating conclusions that bring all the different pieces of the complicated smart urban mobility’s puzzle together and deliver some key recommendations for city scientists, policymakers, transport and urban planners and an agenda for future research directions
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