Abstract
A prototype evaluation framework has been used in railway traffic simulator benchmarking and in the quantitative evaluation and comparison of timetables and of real time traffic management decision taking for railway systems in the presence of both small and large-scale service disruption in the EU FP7 project ON-TIME. Quantified key measures allow an assessment of performance and can be used to compare timetables, control methods or delaying incidents. The resilience measures additionally provide a visualisation and information that can be analysed as an aid to the understanding of delay propagation, based on both real and simulated data.
This benchmarking and evaluation method is based on collecting data at selected observation points on train and service ID, position, and time from either simulation or from data feeds of real operations. With the addition of data on train and network characteristics, this collected data can be processed in such a way as to evaluate the key measures outlined in a previously defined Quality of Service framework. The key measures quantify the following KPIs of the model: transport volume, journey time, connectivity, punctuality, resilience, energy consumption and resource usage.
This benchmarking and evaluation method is based on collecting data at selected observation points on train and service ID, position, and time from either simulation or from data feeds of real operations. With the addition of data on train and network characteristics, this collected data can be processed in such a way as to evaluate the key measures outlined in a previously defined Quality of Service framework. The key measures quantify the following KPIs of the model: transport volume, journey time, connectivity, punctuality, resilience, energy consumption and resource usage.
Original language | English |
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Pages (from-to) | 274-293 |
Journal | Journal of Rail Transport Planning and Management |
Volume | 5 |
Issue number | 4 |
Early online date | 12 Dec 2015 |
DOIs | |
Publication status | Published - Dec 2015 |
Keywords
- Railway operations
- Robustness
- Evaluation
- Benchmarking
- Quality of service