Ubiquitous computation in internet of vehicles for human-centric transport systems

The Internet of Vehicles (IoV) has the potential to bring about a revolutionary transformation in transportation through its influence on human behavior and interactions between users and vehicles. However, interoperability challenges between retailer organizations and manufacturers present a barrier to decision-making processes and impact the human-centric nature of the IoV. Ethical dilemmas arise as a result of the IoV's inability to prevent accidents, particularly in critical situations. This study aims to enhance the IoV's effectiveness by carefully selecting and improving essential attributes from various data sources, including sensors, GPS, 5G or 6G communication networks, and real-time data provisioning. To achieve the aim of the proposed study, a Multi-criterion Decision-making (MCDM) approach is proposed, which allows for the analysis and selection of optimal choices while taking into account various quantitative and qualitative factors. Despite the challenges posed by complex models and ambiguous data, MCDM remains an indispensable technique for aligning transportation systems with current expectations. The CRITIC and TOPSIS MCDM-enabled methodologies are employed to analyze IoV architecture, prioritizing significant elements that impact system performance and identifying optimal solutions by considering complications from worst-case scenarios. The study will assist engineers, scientists, and organizations to develop smart IoV systems that will cater to human needs by improving mobility and inspiration among users.