Track geometry defect rectification based on track deterioration modelling and derailment risk assessment

Qing He, Hongfei Li, Debarun Bhattacharjya, Dhaivat P Parikh and Arun Hampapur
Additional contact information
Qing He: University at Buffalo, The State University of New York, Buffalo, NY, USA
Hongfei Li: IBM T J Watson Research Center, Yorktown Heights, NY, USA
Debarun Bhattacharjya: IBM T J Watson Research Center, Yorktown Heights, NY, USA
Dhaivat P Parikh: IBM Global Business Service, Coppell, TX, USA
Arun Hampapur: IBM T J Watson Research Center, Yorktown Heights, NY, USA

Journal of the Operational Research Society, 2015, vol. 66, issue 3, 392-404

Abstract: Analysing track geometry defects is critical for safe and effective railway transportation. Rectifying the appropriate number, types and combinations of geo-defects can effectively reduce the probability of derailments. In this paper, we propose an analytical framework to assist geo-defect rectification decision making. Our major contributions lie in formulating and integrating the following three data-driven models: (1) A track deterioration model to capture the degradation process of different types of geo-defects; (2) A survival model to assess the dynamic derailment risk as a function of track defect and traffic conditions; (3) An optimization model to plan track rectification activities with two different objectives: a cost-based formulation (CF) and a risk-based formulation (RF). We apply these approaches to solve the optimal rectification planning problem for a real-world railway application. We show that the proposed formulations are efficient as well as effective, as compared with existing strategies currently in practice.

Date: 2015
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