Optimization of Communication-Based Train Control systems deployment in rubber-tired metros based on statistical demonstration for safety-related characterizations

This study focuses completely on optimizing odometry validation campaign for a cutting-edge Communication-Based Train Control (CBTC) for a rubber-tired metro. Because the solution deployed deliberately avoids extra hardware to reduce complexity and cost, finding a dependable statistical criterion to characterize and account for slip-slide phenomena for train protection function without secondary detection sensors (axle-counters, optical barriers, etc.) is essential for the next generation of rubber-tired train networks. Extreme slip-slide events were modelled using the Generalized Extreme Value distribution. Our analysis indicates that severe rare slip-slide events cannot be ignored and shall be included in the computation of safety parameters. Return level is estimated and the uncertainty of the predictions are assessed by a bootstrap approach. At the end, a comparative analysis between the referenced project and the new project datasets reinforces their cross-applicability. The present methodology delivers a data-driven approach to optimize future CBTC deployment costs.