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Passenger Demand, Tactical Planning, and Service Quality Measurement for the London Overground Network Michael Frumin MIT June, 2010. 1. Outline. Tactical Planning. Passenger Demand. Automatic Data. Service Quality (Measurement). 2. Data Collection and OD Estimation. Calibration.

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  1. Passenger Demand, Tactical Planning, and Service Quality Measurement for the London Overground NetworkMichael FruminMITJune, 2010 1

  2. Outline Tactical Planning Passenger Demand Automatic Data Service Quality (Measurement) 2

  3. Data Collection and OD Estimation Calibration Estimation Expensive Manual Infrequent Cheaper Automatic Constant 3

  4. Loadweigh: Industry Experience • Sensors in airbag suspension • Average of 20 samples/second between stations • Demon Info Systems: “Accurate to within ± 20 people @ 95% for a 3 car train” →σ = 10 • Southern Railways: “± 5% @ 95%” →σ = 2.5% • ±5% of 400 passengers = ± 20 • “automatic counts more trustworthy than manual” • Nielsen, et al (2008) in Copenhagen: σ = 14 →± 28 people @ 95% • Financial implications 4

  5. Loadweigh: Exploratory Analysis 8 new Bombardier 378’s with loadweigh sensors on NLL/WLL Peak Load Point (Canonbury to Highbury) Random 10% Sample First Sample: 23 Nov, 2009 – 6 Dec, 2009 5

  6. Loadweigh: Calibration Model Weight (kg) Count (pass) All Data Terminals Only Tare (kg) kg/ pass = Estimate of standard deviation of error (in pass) 6

  7. Loadweigh: Calibration Results 7

  8. Loadweigh: Residuals 8

  9. Loadweigh: Implications • Found: σ = 10.8 → ± 21.2 @ 95% • average 4 - 5 obs for ± 10 @ 95% • Assumptions: • No error in manual counts at terminals (σ↓) – Unlikely • No error in loadweigh data processing (σ↓) – Maybe • No day-to-day variation (σ↑) – Unlikely 9

  10. Loadweigh: Recommendations • To begin with, assume: • 80kg/passenger • ±10 passengers/train @ 95% confidence level • 0 tare weight • Controlled experiment/calibration (eg as did Southern) • Better calibration – higher quality manual counts (and/or terminal counts), and processed/filtered loadweigh data • Continue manual counts on non-loadweigh-enabled portions of LO network (1 year?) • If possible, calibration of new stock

  11. Next: Origin-Destination Matrix Estimation 11

  12. Assignment of O/D flows to links Network Structure Counts of train loads on each link (now: manual future: automatic)‏ Fitting Process (Minimum Info)‏ Additional platform counts as desired (manual)‏ Origin-Destination Matrix Estimation Lots of assumptions! Path Choices‏ Oyster Seed Matrix (automatic)‏ Path choice independent of congestion Final Matrix Timebands Entry/Exits counts from LO-exclusive, gated stations (automatic)‏ Boardings, Alightings, Total Pax 12

  13. OD Result Determines Ridership Estimate OD Matrix Boardings & Alightings Link Flows X X 13

  14. OD Estimation Results 14

  15. OD: Expansion by Line

  16. OD Estimation: Validation Summary

  17. OD Estimation: Validation 17

  18. OD Estimation: Sensitivity to Loadweigh • Applied to each individual measurement (i.e. onboard link count), then re-estimate the matrix • Assume σ = 10, simulated 30 times, for 1 week and 8 weeks of measurements !

  19. OD Estimation: Recommendations • Worth doing for tactical planning at the OD level • If platform counts are conducted (for direct boarding & alighting measurement), can be added to OD estimation: • 11 largest stations (out of 56) have 52% of boardings & alightings (5 are LO-only and gated) • 24 largest have 75% (9 are LO-only and gated) • Extend to East London Line – all new loadweigh-enabled stock, many stations gated & exclusive

  20. OD Estimation: Implementation • In-house implementation by LU S&SD • Prototype uses RODS network data files • Completed updates for existing LO network • Forthcoming updates for ELL • Updates to RODS network assignment model • OD estimation algorithm is simple • First step towards in-house London-wide Rail/Tube OD estimation • S&SD (Gerry W., Geoffrey M.)? 20

  21. Next: Service Quality Measurement and Tactical Planning 21

  22. Service Quality Measurement and Tactical Planning for the North London Line Summer, 2008: Oyster-based service quality and waiting time analysis + Operations analysis (consultant) and operator input April, 2009: Tactical “3 + 3” service plan revision Now: Service plan evaluation 22

  23. NLL Service Plan: Before Uneven AM Peak headways from SRA: 16,4,10,15,15,8,7,15,9,6,15,11,5,15,9,6,15 23

  24. The Case for a New Service Plan • Uneven headways on core segment between Stratford and Camden Road • Mismatch with “random” passenger arrivals • Contribute to overloading trains and extending dwell times • Congestion from shuttle turns at Camden Road • Freight interference on short intervals • Complex service plan for both operators and passengers • From OD Matrix: 25% Cross Willesden Jn on NLL 24

  25. Oyster + Schedule = SWT & EJT (an Example) • One Oyster journey: Stratford → Camden Road • Scheduled Waiting Time (SWT): Pax. Behavior • Tap in: 08:01 • Next scheduled departure: 08:06 • SWT = 08:06 – 08:01 = 5 minutes • Excess Journey Time (EJT): Service Quality • 08:06 train scheduled to arrive at Camden at 08:29 • Tap out: 08:36 • EJT = 08:36 – 08:29 = 7 minutes • Fundamentally relative measures, each with respect to the published timetable 25

  26. Oyster + Schedule = SWT & EJT (Visually) 26

  27. Spring 2008: Arrival Behavior 1 - SWT/headway 27

  28. Spring 2008: EJT by Scheduled Service Total EJT = Avg. EJT x Market Size (Oyster) 28

  29. New “3 + 3” Service Plan: 20 April, 2009 1-2 minutes less running time 5-6 minutes extra running time en-route Even AM Peak headways from SRA (at new platform): 10,10,10,8,12,10,10,10,10,10,10,10,10,13,15,15,15 29

  30. “3 + 3” Evaluation: North London Line • Shorter overall journey times • Improved on-time terminal departures (SRA, RMD) • Reduced dwell times (SRA → RMD) Observed Journey Times ↓ (good) + Scheduled Journey Times ↑ = EJT ↓↓(better?) + Scheduled Journey Times ↓↓ = EJT ↑ (bad?) 30

  31. EJT/3+3: Recommendation • Maintain even intervals on NLL • Use Oyster (via OXNR) to assess passenger arrival behavior (ie SWT) at National Rail stations • EJT: Still a measure of relative performance – useful for improving schedules (a primary tactical planning activity), less so for longitudinal evaluation • Implement EJT? • For the Overground? • For National Rail in London? • For Crossrail?

  32. EJT: Open Source/Standards Implementation • Perl script: MOIRA timetables → Google Transit Feed Spec (GTFS) (easy) • GTFS → GraphServer open source trip-planner for efficient schedule-based routing (hard, free!) • Perl script: Query GraphServer with Oyster data (easy) • SQL: Link to assignment model to filter non-LO trips (easy) 32

  33. Questions? Comments?mfrumin@mtahq.org (as of 6 July) 33

  34. Appendix: “3 + 3” Comparative Evaluation • Shorter overall journey times • Improved on-time terminal departures (SRA, RMD) • Reduced dwell times (SRA → RMD) • Fewer customer complaints of being “left behind” Decrease in observed journey times + increase in scheduled journey times = less EJT (good!) Decrease in observed journey times + greater decrease in scheduled journey times = more EJT (bad?) 34

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