Integrated Risk Prediction and Smart Monitoring for Safer Railway Level Crossings: A Technology and Decision-Support Framework

DOI

No DOI

Published In

Volume 5, Issue 3 (2026)

Published Online

September-December 2026

Pages

556-560

Article Type

Original Article

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At highway–rail level crossings, road traffic, train movements, warning devices and human behaviour combine to create safety risks that are difficult to address through a single measure. This manuscript develops a conceptual decision-support framework that links long-term crossing-risk prioritization with short-term obstacle observation and incident communication. Its evidence base is a focused narrative synthesis of established work on grade-crossing accident models, safety technologies and contributing risk factors. Five functions are defined: crossing inventory, relative-risk screening, sensor-based observation, alert decision, and auditing with feedback. A transparent weighted index is supplied solely as a reproducible teaching example; a three-crossing demonstration shows how candidate locations could be ranked and checked for weight sensitivity. A scenario matrix describes clear crossings, confirmed obstructions, uncertain detections and loss of communications. Proposed evaluation measures include crossing-risk ranking stability, obstacle recall, false alarms per operating hour, alert latency and reliability under adverse conditions. No experimental measurements, real-world deployment, new accident database or safety certification are claimed. The main contribution is a structured conceptual integration and a test plan that distinguishes long-term accident likelihood from immediate obstruction alerts. Before any operational use, locally representative data, independent safety assessment and authorization from railway authorities would be essential