Constructing a comprehensive assessment indicator set: an overview analysis of train driver performance indicators based on on-train-data-recorder (OTDR) data
Authors: 
Xiaoyu Li, Jingyu Zhang, Chenxi Zhao, Lei Shi, Han Zhang, Haiyun An, Wenlu LiAuthors Info & Claims
Xiaoyu Li, Jingyu Zhang, Chenxi Zhao, Lei Shi, Han Zhang, Haiyun An, Wenlu LiAuthors Info & ClaimsPages 223 - 227
Abstract
The rapid development and application of train data recorders have introduced new approaches for assessing train driver performance. Extracting key performance indicators from on-train-data-recorder (OTDR) data enhances performance appraisals by offering more robust metrics. The highly objective and real-time nature of OTDR data enables a comprehensive assessment of train drivers' actual operational performance under varied operating conditions. Although scholars have already explored and analyzed OTDR data for the railway transport industry, there is a relative paucity of literature on this subject, indicating a need for further research. Existing studies often present performance indicators in isolation, overlooking the benefits of a unified approach to comprehensive assessment. Moreover, the scattered distribution of indicators can lead to issues of duplication or interdependent relationships, which limits the full potential of OTDR data in assessing driver performance. This paper explores the necessity and feasibility of constructing an integrated driver performance assessment indicator system, utilizing OTDR data through a systematic literature review. Additionally, the study synthesizes findings from existing research to formulate a comprehensive set of performance indicators. The study concludes with an identification of the potential and limitations of OTDR data, providing insights essential for formulating consistent evaluation criteria, enhancing the scientific validity of the assessments, and guiding practical applications.
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August 2024
465 pages
ISBN:9798400716997
DOI:10.1145/3695652
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Published: 15 October 2024
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- the Science and Technology Research and Development Plan Project of China National Railway Group Co., Ltd
- the Natural Science Foundation of China
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IMMS 2024
IMMS 2024: 2024 the 7th International Conference on Information Management and Management Science
August 23 - 25, 2024
Beijing, China
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