The development of disruptive technologies such as artificial intelligence (AI), autonomous and electric vehicles, and smart grids challenges legal frameworks to remain relevant, adaptive, and coherent over time. This is evident in the transport sector, where technological innovation has the potential to fundamentally reshape transportation, logistics, and urban design, or is already doing so. Against this backdrop, the present study examines the legal ramifications of such transformations by exploring whether AI-based tools can support forward-looking legal research. Specifically, it aims to identify and map potentially complex or unclear legal situations that may arise from the deployment of disruptive technologies. This study employs two large language models (LLMs), Microsoft 365 Copilot and Claude Sonnet 4.6, to generate possible future legal scenarios for the period 2026 – 2037, using a scenario-based research design primarily situated within a Swedish and EU legal context. Several methods for engaging with the LLMs are applied, including mixed prompting, Chain-of-Thought prompting, the RACE framework, and meta-prompting. The results show that both LLMs kept well to the prompt instructions regarding output format, including the integration of future scenarios, external drivers, and potentially challenging legal themes. Additionally, while differences between the responses of the two LLMs were observed, these were primarily differences of degree rather than of kind. The overall conclusions suggest that both LLMs demonstrate potential usefulness for further research and may serve as exploratory tools in legal research as a point of departure. However, although the scenarios produced by the LLMs were grounded in contemporary legal research “hot topics”, a more thorough examination of the validity of their claims is required to support well-founded decisions regarding future research. Finally, it is recommended that researchers should inter alia continue refining their “prompt literacy” while still relying on human judgment, especially for critically evaluating the validity and robustness of LLM-assisted research.
A multi-layered safety model that integrates emerging technologies with human-centred practices, emphasising resilience engineering, adaptive training, transparent AI governance, and continuous learning across transportation ecosystems is proposed, arguing that technological innovation must be framed not as a replacement for human expertise but as an enabler of enhanced human performance.
The transition toward Software-Defined Vehicles (SDVs) is fundamentally reshaping the automotive display and Human-Machine Interface (HMI) landscape. Driven by the deep integration of Artificial Intelligence (AI), the evolution of electronic architectures, and escalating geopolitical tensions, the traditional “larger is better” display paradigm has reached its physical and functional limits. This paper proposes a novel strategic framework, “The Cockpit Decision Reset,” focusing on three critical pillars: supply chain resilience (Just-in-Case), design value prioritization, and HMI logic transformation. We analyze how these factors individually and collectively impact automotive cockpit strategies, shifting the industry from passive screens to proactive, AI-driven environments. Furthermore, this study provides quantitative market forecasts for emerging display technologies, projecting FALD/Mini LED LCD to reach 22.5 million units by 2030, and OLED to reach 11.8 million units by 2030. Concurrently, Micro LED is forecasted to emerge in 2028 with 1.0 K units, growing to 53.0 K units by 2030. New design features such as Panoramic Head-Up Displays (PHUD), Under-Display Cameras (UDC), and Smart Surfaces and Privacy Displays, are also evaluated as essential components of the next-generation cockpit. The proposed framework offers a comprehensive guide for OEMs and Tier 1 suppliers navigating the complex SDV ecosystem.
S. Wu· International Workshop on Ac...· 0 citations
The study proposes an innovative emergency signalling architecture based on two autonomous LED devices positioned outside stationary vehicles in order to improve visibility, reduce secondary collisions, and strengthen contemporary road safety governance. The study originates from the growing limitations of traditional passive warning systems, such as the retroreflective triangle, within modern mobility environments characterized by high traffic density, reduced reaction times, distracted driving, and increasingly complex operational conditions. Drawing on the conceptual framework of the Help Car Roof Project (Rufa et al., 2023), the proposed system integrates multidirectional LED conspicuity with a red-green chromatic logic, inspired by maritime and aeronautical navigation systems. The theoretical framework combines the Safe System Approach, human factors research, cognitive ergonomics, intelligent transportation systems, and contemporary road policing paradigms. The article argues that emergency signalling technologies should no longer be considered simple technical accessories, but rather active components of integrated mobility safety and preventative risk governance. Particular attention is devoted to the operational applications for road policing, emergency responders, roadside assistance personnel, and infrastructure maintenance operators, whose exposure to secondary collisions remains a critical issue worldwide. Finally, the study explores future integration with ITS and V2X systems, highlighting the potential evolution of emergency signalling into intelligent, connected, and anticipatory communication systems capable of improving infrastructural resilience and adaptive mobility safety.
Gianfranco Rufa, Abdulla Thani Alfalasi, Paolo Cestra· International Journal of Soc...· 0 citations
The European Inland Waterway Transport (E-IWT) industry is transitioning towards a new reality governed by higher levels of autonomous systems. While the E-IWT system is preparing for future changes in technical, legal and business frameworks, it is important to examine the system from a socio-technical perspective. Using a Socio-Technical System (STS) framework, the IWT system was segmented into four subsystems: Technical, Personnel, Work Design, and the Environment. Twenty-nine (29) actors covering 19 nodes within the 4 subsystems were interviewed using a pre-questionnaire survey, which was analysed employing a thematic analysis. Two themes emerged as key findings detailing the subsystems in 3 different scenarios: 1. Work as Done- (a) current conventional operation; 2. Work as Imagined- (b) manned and (c) unmanned remote-control operations. For all 3 scenarios, the results identified task, organisation, data and information for 4 subsystems, and existing or foreseeable gaps to the emergence towards higher Levels of Automation (LOA) through those scenarios. Findings forecast a shift in roles and responsibilities from the vessel to the shoreside, likely including a ‘shift in hub’ from vessel-centric operations to Remote Operation Centres (ROCs), requiring real-time communications, extended redundancies, goal-based regulatory changes, and ROC design requirements. The result further highlights misalignment among different subsystems and the necessity of integrated socio-technical approaches, including stakeholder collaboration, regulatory alignment, and system standardisation, to support the transition towards higher LOA in E-IWT.
R. Saha, M. Lundh, S. N. MacKinnon· Journal of Shipping and Trad...· 0 citations
A fully automated situational awareness framework that leverages Generative Artificial Intelligence, specifically Large Language Models (LLMs), to extract, analyse, and synthesise actionable information from social media streams for real-time monitoring and situational awareness of critical infrastructure in resource-constrained environments is proposed.
John Bosco Bwire, Godfrey M. Kibalya, G. Owomugisha et al.· East African Journal of Info...· 0 citations
Advanced Metering Infrastructure (AMI) is a key enabler of digital and intelligent power systems, particularly in microgrid environments. However, existing research often addresses AMI from fragmented perspectives, limiting a comprehensive understanding of its role within integrated and data-driven energy systems. This paper presents a structured analysis of AMI based on a bibliometric and thematic review of recent literature, identifying the main research trends, technological drivers, and emerging directions in the field. The results reveal a transition of AMI toward a data-centric platform that supports real-time monitoring, bidirectional energy management, and intelligent decision-making. Key domains include cybersecurity, data analytics, communication systems, and distributed energy integration, while emerging technologies such as artificial intelligence and the Internet of Energy play a critical role in future developments. Finally, the paper outlines key challenges and provides strategic recommendations to support the effective deployment of AMI in microgrids, contributing to the development of resilient and sustainable energy systems.
Juan Camilo Riaño-Rueda, Melisa de Jesús Barrera-Durango, N. Muñoz-Galeano et al.· Electricity· 0 citations