Railway Infrastructure Capacity Utilization Description through Data Integration in Blocking Time Theory

Qinglun Zhong
Institut für Eisenbahnwesen und Verkehrssicherung, Technische Universität, Braunschweig, Germany

Shaoquan Ni
School of Transportation and Logistics / National Railway Train Diagram Research and Training Centre / National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation, Southwest Jiaotong University, Chengdu, China

Shengdong Li
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China / Department of Management, Technical University of Denmark, Lyngby, Denmark

Chang’an Xu
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China

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Ingår i: RailNorrköping 2019. 8th International Conference on Railway Operations Modelling and Analysis (ICROMA), Norrköping, Sweden, June 17th – 20th, 2019

Linköping Electronic Conference Proceedings 69:83, s. 1259-1277

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Publicerad: 2019-09-13

ISBN: 978-91-7929-992-7

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


We propose a method to describe capacity utilization for railway infrastructure that applies blocking time theory to managing train runs. Different from traditional capacity evaluation, infrastructure capacity utilization description shows detailed information on infrastructure utilization hidden in timetabling data instead of sheer number of trains that can be operated, or capacity consumed. Using a function system defined upon necessary operational inputs for timetabling in blocking time theory, we can obtain the feasibility condition for operating consecutive trains. Thus, the method to identify critical block section can be deduced from the feasibility condition. Structural indication determines the capacity utilization of consecutive train paths, which can be further integrated into a bi-directional graph to model infrastructure capacity utilization description followed by infrastructure time allocation. Consumed capacity of railway infrastructure by operating train runs can be formulated. Besides, a general procedure is proposed to analyse the sensitivity of consumed capacity to operational inputs. An experimental case study is conducted to demonstrate the application of this method in analysing the impact of speed and recovery time.


Blocking time theory, Capacity analysis, Infrastructure capacity utilization description, Timetabling data


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