Benchmarking operation readiness of the high-speed rail (HSR) network

Rungskunroch, Panrawee ORCID: 0000-0001-9186-3116 (2022). Benchmarking operation readiness of the high-speed rail (HSR) network. University of Birmingham. Ph.D.

Text - Redacted Version
Available under License All rights reserved.

Download (19MB) | Preview


At present, HSR networks have been significantly extended to accommodate increased passenger demand because the service is believed to unleash social benefits. Nevertheless, the investment in the HSR project is substantially higher than in other transportation projects. Also, most of the HSR network has faced unavoidable issues during operation, such as lack of passenger demand, low operating profit, and non-safety issues. Despite issues addressed, HSR organisations could not maintain their performance to reach the standard and the globe’s directions, especially the sustainability pillar. Those issues become ineffective for HSR organisations, impacting the passenger’s quality of life and socio-economic.

This thesis aims to develop a systems-based benchmarking framework for all HSR networks to enhance operating costs, punctuality, productivity, risk and uncertainty, sustainability, and urbanisation efficiency. Those six KPIs are necessary for the sustainable development of the upcoming HSR network. The thesis has made several significant contributions to developing a benchmarking framework for long-term improvement.

First, this thesis is the world’s first to integrate a Bayesian distribution and Python programming to improve safety across the railway network. As a result, the created model shows higher accuracy than previous models due to the combination of long-term data sets. Moreover, this thesis reveals the decision tree and the Petri-net models to identify the risk level. Thus, it is an advantage for the rail authorities to evaluate and enhance safety performance.

Next, the thesis focuses on life cycle assessment (LCA) and life cycle cost (LCC) frameworks. The LCA model reflects the environmental perspectives of each rail network. This thesis provides an in-depth analysis of each life cycle stage that shows the energy consumption rate and CO2 emission rate. The outcome can point out energy consumption and CO2 emission performance. In addition, this thesis is the world's first study concerning uncertainty costs during HSR operations regarding the LCC analysis. The net present value calculation with a discount rate has been added with the Monte Carlo Simulation. In this section, the developed model allows HSR authorities to firmly manage the budget under uncertain conditions, especially during an operating stage.

Lastly, this thesis concentrates on the social impacts of HSR service, particularly on a living quality, educational benefits, and economic opportunities. The long-term datasets have been analysed by using K-nearest neighbour and Pearson correlation techniques. The result can point out the company’s performance toward social advantages. By adopting the models in practice, people can obtain more benefits from the HSR service.

By promoting the novelty framework into practice, benchmarking through diversification of current HSR networks is addressed. The selected routes and networks are chosen using a range of factors. For illustrate, the collected networks must be stable and trustworthy, as determined by their long-term operation for at least ten years. Furthermore, the selected HSR lines are mixed in geography, technology, and relevant conditions to avoid bias. The five noteworthy networks and routes consist of Beijing-Shanghai (China), Paris-Lyon (France), Tokyo-Osaka (Japan), Madrid-Barcelona (Spain), and Seoul-Busan (South Korea).

The analysis results indicate that none of the HSR networks illustrates high performance in all pillars. An overview result demonstrates that the CR’s networks perform the best performance following the Renfe, SNCF, JR Central, and Korail networks. In addition, the thesis has provided policy implications for long-term development, in particular, safety services, social impacts, environmental impacts, and technology and innovation. Those suggestions can be applied practically to both existing and upcoming HSR networks.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
Licence: All rights reserved
College/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department: School of Engineering, Department of Civil Engineering
Funders: Other
Other Funders: The Royal Thai government, European Commission H2020-RISEN Project No. 691135 ‘RISEN: Rail Infrastructure Systems Engineering Network’
Subjects: H Social Sciences > HN Social history and conditions. Social problems. Social reform
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TF Railroad engineering and operation


Request a Correction Request a Correction
View Item View Item


Downloads per month over past year