Abstract
As urban populations grow and vehicle numbers surge, traffic congestion and road accidents continue to challenge modern transportation systems. Conventional traffic management approaches, relying on static rules and centralized control, struggle to adapt to unpredictable road conditions, leading to longer commute times, fuel wastage, and increased safety risks. Vehicle-to-Everything (V2X) communication has emerged as a transformative solution, creating a real-time, data-driven traffic ecosystem where vehicles, infrastructure, and pedestrians seamlessly interact. By enabling instantaneous information exchange, V2X enhances situational awareness, allowing traffic systems to respond proactively to accidents and congestion. A critical application of V2X technology is accident-aware traffic management, which integrates real-time accident reports, road congestion data, and predictive analytics to dynamically reroute vehicles, reducing traffic bottlenecks and improving emergency response efficiency. Advanced computational algorithms, including heuristic methods, machine learning models, and AI-driven optimization techniques, play a vital role in enhancing routing decisions within V2X networks. By leveraging these algorithms, modern traffic systems can transition from reactive congestion management to proactive traffic optimization, significantly improving urban mobility. Despite its potential, the large-scale deployment of V2X-enabled traffic management systems faces several challenges, including network reliability, data privacy, cybersecurity risks, and interoperability issues. Additionally, concerns related to algorithmic transparency, ethical decision-making, and standardization of V2X communication protocols must be addressed to ensure seamless integration into existing infrastructure. Unlike existing surveys that broadly examine V2X communication or intelligent transportation systems (ITS), this review uniquely focuses on accident-aware traffic management and route optimization. It synthesizes state-of-the-art accident detection methods, routing strategies, and optimization algorithms, while identifying research gaps and proposing future directions for integrating V2X technologies into safer, adaptive, and intelligent transportation systems. By providing these targeted insights, the study contributes to the development of smarter, safer, and more efficient road networks, offering valuable guidance for researchers, policymakers, and industry professionals working to shape the future of urban mobility.