Vision 2050 of the UAE in Intelligent Mobility

Mathew, Elezabeth; Mansoori, Suaad Al

doi:10.1109/ctit.2018.8649542

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…Additionally, AI-based solutions allow real-time mitigation governance [ 73 ], which can lead to more efficient public transportation models and to changes in the mobility behavior of urban dwellers. Surely, the new possibilities of connectivity; exceptional processing power; and the growing role of emerging technologies such as AI, IoT, robotics, and self-driving vehicles will advance intelligent mobility in the coming years [ 76 ].…”

Section: Resultsmentioning

confidence: 99%

“…ENC: AI can help identify areas demanding support and integrate individual actions to solve complex urban problems for the implementation of net zero policies. Artificial intelligence and neural networks are also applied in the process of learning how to optimally design building structures, with good results in shaping behaviors that save resources, such as reducing energy consumption while maintaining thermal comfort conditions [ 76 ] or climate neutrality [ 77 ]. The research cannot, however, prove that the potential of AI to shape urban circularity is already recognized.…”

Section: Discussionmentioning

confidence: 99%

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Greencoin as an AI-Based Solution Shaping Climate Awareness

Obracht-Prondzyńska

Duda

Anacka

et al. 2022

IJERPH

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Our research aim was to define possible AI-based solutions to be embedded in the Greencoin project, designed as a supportive tool for smart cities to achieve climate neutrality. We used Kamrowska-Załuska’s approach for evaluating AI-based solutions’ potential in urban planning. We narrowed down the research to the educational and economic aspects of smart cities. Furthermore, we used a systematic literature review. We propose solutions supporting the implementation process of net zero policies benefiting from single actions of urban dwellers based on the Greencoin project developed by us. By following smart city sectors, the paper introduces AI-based solutions which can enrich Greencoin by addressing the following needs: (1) shaping pro-environmental behaviors, (2) introducing instruments to reinforce the urban management process, (3) supporting bottom-up initiatives allowing to shape urban resilience, (4) enhancing smart mobility, (5) shaping local economies supporting urban circularity, and (6) allowing better communication with residents. Our research fills the gap in the limited group of studies focused on shaping climate awareness, enhancing smart governance, and supporting social participation and inclusion. It proves that AI-based educational tools can be supportive when implementing adaptation policies toward climate neutrality based on our proposed AI-based model shaping climate awareness.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Greencoin as an AI-Based Solution Shaping Climate Awareness

Obracht-Prondzyńska

Duda

Anacka

et al. 2022

IJERPH

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“…The study holds the stance that the successful and effective implementation of HMI and AV in future transportation systems can be practically realised by a careful and rational risk management associated with vehicle and user interface-related technology. The motivation is based on the notion cited in Mathew and Al Mansoori (2018) [9] . Recent studies have advocated the use of varied design frameworks to achieve this.…”

Section: Introductionmentioning

confidence: 99%

“…While the secondary objective it to evaluate the framework with regard to usability features, information parameters, situation responsiveness, user acceptance, attention and capacity. "25% of autonomous vehicles will be launched by 2030 in the UAE" (Mathew & Al Mansoori, 2018, p. 1) [9] , besides Expo 2020 and Road and Transport Authority (RTA) are operating towards Intelligent Transport System (ITS) to facilitate this (2018). If these developments are already taking place, soon enough AV vehicles will be able to interact with other vehicles including smart city system, the Internet of Things (IoT) tools, devices and ITS.…”

Section: Introductionmentioning

confidence: 99%

A framework for usability evaluation of automated driving human-machine interface in context of UAE

Mago,

Zarooni,

Finge

2023

Int. J. Comput. Artif. Intell.

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As a future mobility enabler, vehicle teleoperation offers a viable option for efficiently leveraging the benefits of driverless cars, whilst fully automated cars (SAE 5) are not completely viable. Despite the huge amount of research on self-driving technology, the notion of riding in a fully automated vehicle is still sceptical. Hence necessitating the presence of a remote operator who tele monitors the vehicle and acquire control in case of failure beyond the capabilities of vehicle automation, such as misuse, disuse or mode confusion and ensuring safety and reliability. Keeping the current inclination towards automated vehicles and the launch of the United Arab Emirates" (UAE) first driverless, autonomous 12-seater shuttle, the researcher has suggested a low-fidelity basic prototype. To connect the vehicle's automation and human teleoperation, the researcher has proposed a unique and interactive framework of Human-Machine Interface (HMI) to cater teleoperation in the context of automated vehicles (AVs) in the UAE. The design is optimised for the teleoperation of a highly automated shuttle by a public transportation control centre based on a logical and careful inquiry. After deriving a detailed analysis of requirements, a prototype is then created and refined until an interactive user-interface emerges. Fifteen control station experts are presented with a prototype for evaluation in a regular manner and solicited to work out three scenarios with disruptions in the system. The prototype is then evaluated using questionnaires and structured interviews. The results validate the suggested HMI design for the remote operation of a highly automated vehicle. Participants' feedback shows a particularly high level of satisfaction in terms of perceived capacity, feasibility, usability approval and situational responsiveness. The findings also provide valuable information for an advanced interactive HMI design and pave the way for potential future directions in further research as well.

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