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@article{186129,
        author = {SyedAmaanAli and ShaikRehan and Adibkhan and Lateefkhan and mr mohammed jalal uddin Asst prof and Dr khaja fareed uddin},
        title = {Accidental Ratio In Railway Engineering},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {523-526},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186129},
        abstract = {Railway systems are critical to sustainable transportation networks, yet they are exposed to various accident-risks stemming from infrastructure, operational, and human factors. This study investigates the concept of the accidental ratio—defined here as the ratio of the number of accidents (or accident events) to a selected exposure metric (such as train-km, track-km, or number of train runs) within a railway engineering context. The objectives are: (1) to quantify this ratio for a selected railway system over a defined period; (2) to identify and analyse the main contributory factors influencing variations in the accidental ratio (e.g., track condition, signalling failures, human error, maintenance regimes, traffic intensity); and (3) to propose a decision-support framework that railway engineers and managers can use to benchmark safety performance, allocate maintenance resources, and reduce accident frequency. Using a dataset of X years of accident records from a national/international railway network, we compute accidental ratios for different categories (e.g., derailments, collisions, level-crossing incidents) and correlate these ratios with exposure and risk metrics. Regression and statistical modelling indicate that higher traffic intensity, ageing infrastructure, and lower preventive maintenance frequencies are associated with elevated accidental ratios. The proposed framework demonstrates how setting target accidental-ratio thresholds—based on best-practice benchmarks—can help in prioritising safety investments. The findings inform engineering policy for rail-sector safety management and contribute to the advancement of the broader goal of resilient, low-risk railway infrastructure.},
        keywords = {railway accidents; accidental ratio; exposure metric; risk-analysis; track infrastructure condition; human factors; safety benchmarking; decision-support framework},
        month = {November},
        }