New methods of evaluating railway capacity

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1 A Source of Future New methods of evaluating railway capacity Xiaolu Rao Swiss Federal Institute of Technology (ETH Zurich) & Systransis AG 24/03/15 1

2 Content! Motivation! Classification of capacity definitions! New 4-quadrant capacity model! Conclusion 24/03/15 2

3 Content! Motivation! Classification of capacity definitions! New 4-quadrant capacity model! Conclusion 24/03/15 3

4 Motivation Case study! To prove the potential capacity benefit of a commercial Traffic Management System (TMS) product for two infrastructure areas.! Two major functions of the TMS product:! Train re-ordering! Train re-routing! Operational log files for two cases:! Case 1: operation without TMS INT FR INT SA Biy Sae SyS Frl Area Sy INT GU SyW Giy Sy SyE Est Dod Sps Ban INT DO Apy INT AP Ary WoW Hok INT WEY CoyW WhlE CoyE Cot INT CO Area Les Ene Legend: WhlW INT XX INT AR INT AB LesW INT HOK Small station Main station Interlocking subarea XX for case study Les LesE! Case 2: operation with TMS 24/03/15 4

5 ! Area 1: INT SA INT FR INT AP INT DO INT GU Legend: Signal Route! Area 2: INT CO INT HOK INT WEY INT AB INT AR Legend: Signal Route 24/03/15 5

6 Motivation Question 1! Increasing capacity is a main target of railway optimisation. Experts from different backgrounds are making their own efforts to increase capacity.! There are confusions about the definitions of capacity and the methods to increase capacity, especially when the discussion of capacity involves different experts.! Question 1: Is it feasible to classify the definitions of capacity systematically? 24/03/15 6

7 Motivation Question 2! Currently, many existing capacity studies focus on estimating the maximum theoretical capacity in different conditions.! The topic of evaluating the dynamic capacity influenced by different optimisation methods has not been fully discussed in the latest capacity study.! Question 2: Is it feasible to build a quantified model to evaluate the trade-off between capacity and operational quality in different operational scenarios? 24/03/15 7

8 Content! Motivation! Classification of capacity definitions! New 4-quadrant capacity model! Conclusion 24/03/15 8

9 Proposal of classifying different capacity definitions! Capacity is the maximum number of trains per time the infrastructure can handle under specified condition. capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity 24/03/15 9

10 Proposal of classifying different capacity definitions! Capacity is the maximum number of trains per time the infrastructure can handle under specified condition. capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity Estimate the maximum number of trains Count the number of trains in timetable Count the number of trains in operational log file 24/03/15 10

11 Proposal of classifying different capacity definitions! Capacity is the maximum number of trains per time the infrastructure can handle under specified condition. capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity Estimate the maximum number of trains Analyse the trade-off between capacity and quality 24/03/15 11

12 Proposal of classifying different capacity definitions capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity Traffic pattern Reserve time / buffers Disturbance/ conflicts Optimisation methods 24/03/15 12

13 Proposal of classifying different capacity definitions capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity Traffic pattern Reserve time / buffers Disturbance/ conflicts Optimisation methods 24/03/15 13

14 Proposal of classifying different capacity definitions capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity Traffic pattern Reserve time / buffers Disturbance/ conflicts Optimisation methods 24/03/15 14

15 Proposal of classifying different capacity definitions capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity Traffic pattern Reserve time / buffers Disturbance/ conflicts Optimisation methods 24/03/15 15

16 Proposal of classifying different capacity definitions capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity Traffic pattern Reserve time / buffers Disturbance/ conflicts Optimisation methods 24/03/15 16

17 Proposal of classifying different capacity definitions capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity Traffic pattern Reserve time / buffers Disturbance/ conflicts Optimisation methods 24/03/15 17

18 Proposal of classifying different capacity definitions capacity Level capacity with traffic pattern capacity with optimised conflict resolution Close to Traffic Planning Level Optimised timetable capacity Generate Traffic Operating Level Optimised operational capacity Non-optimised timetable capacity or Non-optimised operational capacity Traffic pattern Reserve time / buffers Disturbance/ conflicts Optimisation methods 24/03/15 18

19 Content! Motivation! Classification of capacity definitions! New 4-quadrant capacity model! Conclusion 24/03/15 19

20 UIC 4-quadrant capacity model Average speed Number of trains Heterogeneity Stability Mixed-train working Metro-train working It is a qualitative model! There is no standard measurement of each parameter yet It is inappropriate to compare mixed traffic with metro via this model! This comparison is based on an experience rather than a detailed calculation! The infrastructure situation of mixed traffic line is very different from metro.! A large number of trains operated in metro does not indicate that mixed traffic line can operate the same number of trains by changing into a similar homogeneous traffic pattern or by operating in a lower train speed. Only for single line! This model is only suitable for single line, but not for nodes (such as interlocking areas and stations). 24/03/15 20

21 New 4-quadrant capacity model Saturation of trains 1 Each parameter of the model can be quantified with the value ranged from 0 to 1. Speed Performance Stability It can be used to evaluate the influence of different optimisation methods using in traffic planning or operation for the same infrastructure area. 1 Heterogeneity It can be used for single line and interlocking area. Non-optimised operation Optimised operation 24/03/15 21

22 Measure of saturation! The saturation measures how close the planned or observed number of trains is to the capacity with optimised conflict resolution. 24/03/15 22

23 capacity with optimised conflict resolution! Step 1: Count the number of trains N in the operational log file,! Step 2: Statistics of each delay case: case 1,..., case m,! Step 3: Estimate the saved time if each delay case is resolved perfectly: t case1,..., t casem, m t! Step 4: Calculate the sum of saved time saving = t case i, i=1! Step 5: Find out the minimum train running time t min,! Step 6: Calculate the maximum additional number of trains K = t saving / t min! Step 7: Calculate the theoretical capacity with optimised conflict resolution: = N + K 24/03/15 23

24 Measure of speed performance! The speed performance measure how close the average speed is to the optimal speed. 24/03/15 24

25 Optimal train speed! The optimal speed assumes that each train is in good physical conditions to behave perfectly and correspond to the minimum headway time. 1600" Headway time according to the speed of train Headway time (s) 1400" 1200" 1000" 800" 600" 400" 200" train speed-headway time optimal speed with min headway time 0" 0" 50" 100" 150" 200" 250" 300" Train speed (km/h) 24/03/15 25

26 Measure of heterogeneity! The heterogeneity measures the flexibility of the infrastructure to handle different proportional mix or trains (different train types, different train sequence and different departure/arrival time).! The measure is from Dr. Landex. 24/03/15 26 Landex, A. (2008). Methods to estimate railway capacity and passenger delay. PhD thesis, Technical University of Denmark.

27 Measure of stability! The stability measures the ability of the traffic network to handle potential disturbances. It is determined by three factors:! Complexity of the infrastructure layout. The more complex of the infrastructure layout is, the more disturbances might happen, then the less stability will be.! Conflict frequency. The higher frequency for disturbance happens, then the less stability will be.! Headway time. The longer headway time of each route has, the less buffer time to handle disturbance, then the less stability will be. 24/03/15 27

28 Measure of stability step 1 Build a route conflict table and calculate the conflict rate A C E B D 24/03/15 28

29 Measure of stability step 2 Determine the conflict frequency or route pairs Train Sequence (Train sequence id, Train route) Train Compare (Determine a conflict route pair or not) 1, AE 2, AE 3, BA 1, AE 2, AE 3, BA Is route pair "AE AE" a conflict? Yes! 4, BA 5, AE 6, CD 4, BA 5, AE 6, CD Conflict route pair name AE AE Count +1 7, BA 7, BA 8, BC 8, BC 9, BA 9, BA 10, AE 10, AE 11, AE 11, AE 12, AE 12, AE 13, BA 13, BA 24/03/15 29

30 Measure of stability step 2 Determine the conflict frequency or route pairs Train Compare (Determine a conflict route pair or not) 1, AE 1, AE 2, AE 2, AE 3, BA 3, BA 4, BA 4, BA 5, AE 6, CD Is route pair "AE CD" a conflict? No!! 5, AE 6, CD Is route pair "AE BA" a conflict? Yes! 7, BA 7, BA 8, BC 9, BA 8, BC 9, BA Conflict route pair name Count 10, AE 10, AE AE AE 1 11, AE 11, AE AE BA , AE 12, AE BA BA 1 13, BA 13, BA BA AE 1 24/03/15 30

31 Measure of stability step 2 Determine the conflict frequency or route pairs Train Compare (Is that the last train?) 1, AE 2, AE 1, AE 2, AE Is route pair "BA AE" a conflict? Yes! 3, BA 3, BA 4, BA 4, BA Conflict route pairs 5, AE 6, CD 7, BA 8, BC 9, BA 10, AE 11, AE 12, AE 13, BA Can you find next route? No! 5, AE 6, CD 7, BA 8, BC 9, BA 10, AE 11, AE 12, AE 13, BA Conflict route pair name AE AE Count 3 AE BA 3 BA BA 1 BA AE 2+1 CD BC 1 BA BC 1 BC BA 1 Frequency of conflict route pair 3/13 3/13 1/13 3/13 1/13 1/13 1/13 08/04/15 31

32 Measure of stability step 3 Calculate the average headway of each route pair 24/03/15 32

33 Measure of stability step 3 Calculate the average headway of each route pair 24/03/15 33

34 Measure of stability step 4 Calculate the weighted headway for each route pair! The weighted headway of route pair combines three factors together, 24/03/15 34

35 Measure of stability step 4 Calculate the occupation rate 24/03/15 35

36 Measure of stability step 5 Estimate the stability! The stability can be measured according to the occupation rate. Stability estimation 24/03/15 36

37 Compare the influence of different optimisation methods on the trade-off Saturation of trains Saturation of trains 1 1 Speed Performance Stability Speed Performance Stability 1 Heterogeneity 1 Heterogeneity Operation 1 Operation 2 Operation 1 Operation 2 24/03/15 37

Comparison Speed Performance Saturation of trains 1 1 0 1

38 Comparison Speed Performance Saturation of trains Stability 1 Heterogeneity Operation 1 Operation 2 24/03/15 38

39 Case study of the new 4-quadrant capacity model! Saturation vs. Stability INT FR INT SA Biy Sae SyS Frl SyW Sy SyE Dod Ban INT DO Area Sy INT GU Giy Est Sps Apy Legend: INT XX Small station Main station Interlocking area XX for case study TMS has positive effect on stability TMS has no positive effect on stability INT AP INT AR INT WEY WoW Hok Ary WhlW INT AB Les Cot CoyW CoyE WhlE Ene LesW INT HOK LesE INT CO Area Les 24/03/15 39

40 Case study of the new 4-quadrant capacity model! Saturation vs. Speed performance INT FR INT SA Biy Sae SyS Frl SyW Sy SyE Dod Ban INT DO Area Sy INT GU Giy Est Sps Apy Legend: INT XX Small station Main station Interlocking area XX for case study TMS has positive effect on speed performance TMS has no positive effect on speed performance INT AP INT AR INT WEY WoW Hok Ary WhlW INT AB Les Cot CoyW CoyE WhlE Ene LesW INT HOK LesE INT CO Area Les 24/03/15 40

41 Case study of the new 4-quadrant capacity model! Saturation vs. Heterogeneity INT FR INT SA Biy Sae SyS Frl SyW Sy SyE Dod Ban INT DO Area Sy INT GU Giy Est Sps Apy Legend: INT XX Small station Main station Interlocking area XX for case study TMS has positive effect on heterogeneity TMS has no positive effect on heterogeneity INT AP INT AR INT WEY WoW Hok Ary WhlW INT AB Les Cot CoyW CoyE WhlE Ene LesW INT HOK LesE INT CO Area Les 24/03/15 41

42 Content! Motivation! Classification of capacity definitions! New 4-quadrant capacity model! Conclusion 24/03/15 42

43 Achievements! It proposed a classification of capacity definitions, which distinguishes the analysis of dynamic capacity influenced by different optimisation methods from the analysis of theoretical capacity under different restrictions.! It proposed a new 4-quadrant capacity model, which provides a new method to evaluate the trade-off between capacity and quality in different traffic planning or operations. 24/03/15 43

44 Remaining question! Using the new 4-quadrant capacity model, it proposed a method to compare two or more different operations or planning on the trade-off between capacity and quality.! The method multiplies two quantified parameters. It is unclear whether this method is appropriate, which has to be discussed in the future study. 24/03/15 44

45 Thank you for your attention. 24/03/15 45

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