Authors : Dr. Harshali Patil; Aditi Singh

Volume/Issue : Volume 11 - 2026, Issue 5 - May

Google Scholar : https://tinyurl.com/mkmffa7

Scribd : https://tinyurl.com/2rpwfsey

DOI : https://doi.org/10.38124/ijisrt/26May1131

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Navigation systems have seen steady improvements over the years, especially with the inclusion of real-time traffic updates and dynamic route planning. Even so, there’s still a slight mismatch between what is computed as an optimal route and what is actually experienced during travel. Routes that appear efficient in terms of time or distance often overlook practical aspects like road surface conditions, which can affect both comfort and safety in ways that are not always immediately visible. This paper presents a literature-based review of routing methodologies, starting from classical algorithms such as Dijkstra's Algorithm and A* Search Algorithm, and extending to more recent traffic-aware routing approaches. Alongside this, it examines existing research on road condition detection, particularly methods based on Machine Learning and object detection frameworks like YOLOv8. Reported findings in the literature indicate that while these techniques can achieve reasonable levels of accuracy under specific conditions, their performance may vary when applied in diverse and dynamic environments. What becomes noticeable across the reviewed studies is that routing efficiency and road condition analysis are often treated as separate concerns. This survey, therefore, focuses on bringing these strands of research into a single perspective, not to propose a new system, but to better understand existing approaches, their limitations, and the gaps that remain. By doing so, the paper aims to provide a clearer foundation for future work in developing more comprehensive and context-aware routing solutions.

Keywords : Hybrid Routing System, Real-Time Navigation, Pothole Detection, Road Condition Analysis, Traffic-Aware Routing, Deep Learning, Machine Learning, Intelligent Transportation Systems, Graph-Based Routing, Dynamic Route Optimization.

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