1. PLANET – A comprehensive tool for forecast and appraisal of public transport schemes in the UK 12th European EMME/2 Users’ Conference Basel, Switzerland (22-23 May 2003) Peter Bartlett (Jacobs Consultancy)

2. Presentation Summary History of PLANET Interfaces Development of PS2002 models Crowding and Assignment procedures Validation Application Appraisal Future Development

3. Jacobs Consultancy Jacobs Consultancy UK 275 staff worldwide Transport Planning Business Planning & Strategy Development Planning Jacobs Engineering Group Inc. Turnover USD 5 billion Total Staff 33,000 Consulting, Design, Construction, Operations, Maintenance Client Base: Industrial, Commercial, Government

4. Strategic Rail Authority (SRA) UK Objectives of SRA Promote use of the national rail network by letting rail passenger franchises and specifying network enhancements Sponsorship and Development of Infrastructure projects Management of Freight Grants All franchise changes and enhancements must satisfy value for money criteria and be appraised using a framework agreed with Department of Transport (DfT). www.sra.gov.uk

5. History of PLANET model development 19902000 PLANET 91 PLANET 99 PLANET MM PLANET PS2002 Time Development PLANET Model Future Development PLANET STRATEGIC

6. PLANET 91 1991 National Rail Timetable 1991 Demand Geographical area covering former Network South East (NSE) rail services Assignment Model Early attempts at Distribution Model Split (DMS) model No Underground or Bus network Developed by British Rail (NSE)

7. PLANET 99 1997/98 National Rail timetable 1997/98 Demand Trip distribution based on 1991 data Enhanced Crowding model Elasticity approach for future year forecasts Replaced early attempts at DMS model Based on relative Generalised Time

8. PLANET MM 1997/98 National Rail timetable 1997/98 Demand Geographical Extension AM and Inter-Peak Time Periods London Underground Network London Bus Network Highway Network

9. PLANET STRATEGIC Geographical coverage Northern and Southern England 250 Zones 16 Hour (all-day) model Multi-Modal Rail, Air, Car Appropriate for Strategic tests e.g. High Speed Line (London – NE England) NOT appropriate for specific detail i.e. Local flows, crowding at specific location Developed by another UK consultancy

10. PLANET PS2002 2001/2002 National Rail timetable Railtrack Train Service Database (TSDB) 2001 Demand CAPRI Ticket Sales data Segmented by Journey purpose North and South Models Geographical split of UK  North – 1600 zones  South – 1400 zones Split by Time Period  AM (07:00 – 09:59)  Inter Peak (10:00 – 15:59)

11. Planet North and South Rail Network

12. Planet South Rail Network

13. Planet North Rail Network

14. PLANET South Network Summary

15. PLANET North Network Summary

16. PLANET Interfaces INPUTS TSDB  Train Service Database CAPRI  Computer Analysis of Passenger Revenue Information ORCATS  Operational Research Computer Allocation of Tickets to Services

17. Demand matrices Processing CAPRI data October / November 2001 CAPRI data downloaded on detailed station-station basis Period demand factored to average winter weekday  Annual season ticket demand “spread” to account for monthly sales patterns  Different factors applied to season, full and reduced tickets Daily demand factored to AM / IP periods using ORCATS demand profiles, depending on  ticket type,  origin / destination station “types”,  journey length

18. Demand matrices Assigning CAPRI data to zones PLANET South station-zone distribution outside inner London based on previous PLANET models PLANET South distribution inside inner London based on iterative approach  Start with previous (1991 LATS) distribution of London trip ends from surrounding zones  Inner London trip ends factored based on LUL station entries / exits counted Autumn 2001  Surrounding zone trip ends based on CAPRI data PLANET North station-zone distribution based on “zone trip generation” model  “Size” of zone (population / employment)  Distance of zone from station

19. Demand matrices Segmentation by journey purpose Full fare Reduced fare Season tickets Business Commuting Leisure / Other Journey purpose split by ticket type Based on “dominant TOC” for each flow Derived from National Passenger Survey

20. Demand matrices (example) Segmentation by journey purpose South West Trains (TOC) Full fare Reduced fare Season tickets Business Commuting Leisure / Other 26% 40% 34% 16% 19% 65% 2% 91% 6%

21. Transit line / network details Timetable details downloaded from “TSDB” (Train Service DataBase) file More reliable than “PIF” file used previously Contains details of “pick-up / set-down only” stops Train route through network calculated by shortest path Aided by “key passing points” identified in TSDB Validation checks for correct links / nodes being used Trains allocate to AM / IP periods by time at highest “hierarchy station” served E.g. London terminus for London-based TOCs Alternative main stations for non-London services (defined by TOC)

22. Transit line / network details New transit line codes Based on CAPRI codes Easier identification of “service groups” YLWU03 1 st Character = TOC; Y = South West Trains 1 st /2 nd Character = Service Group; YL = 6730 (Waterloo – Hampton Ct / Chessington / Dorking / Guildford 3 rd Character = Key timing station; W = London Waterloo 4 th Character = Direction; U = Up 5 th /6 th Character = Numerical list of trains

23. PLANET Assignment Flow Diagram

24. Assignment / Crowding Procedure Business demand Scenario with total passenger volumes Overall assignment process Commuter demand Leisure demand Scenario with Business costs Scenario with Commuter costs Scenario with Leisure costs Calculation of Business costs Calculation of Commuter costs Calculation of Leisure costs Loading values accumulated in 6 iterations (50%,15%,10%, 10%,10%,5%) assign sum

25. Crowding function Demand profile Supply profile Crowd cost parameters Train capacity Modelled passenger volume (total over all journey purposes) Calculation of ratio of volume to capacity (over 18 time slices) Calculation of weighted average crowding cost factor for segment / purpose For each segment and purpose (train / link combination in four sub-models) Link type (x3) Journey purpose (x3) Service type (x5)

26. Crowding function – Supply profiles Profiles for North/South models + AM/ IP Calculated from timed provision of train service capacity As shown in passenger timetable Different profiles reflect different types of service (in peak periods) Flat profile: fixed formation, standard service interval  Long distance inter-urban service Increasing profile : higher frequency services at end of peak period  Inter-urban service with business emphasis Peaked profile: higher frequency and longer / higher- capacity train formations during peak period  Commuter services

27. Crowding function – Supply profiles

28. Crowding function – Demand profiles Profiles for North/South models + AM/ IP Calculated on the basis of ORCATS demand profiles Separate profiles for Business, Leisure, Commuter (based on profiles for Full, Reduced, Seasons) Further refinement may be possible But note that profiles are approximate anyway  Cover different flow “types” (to / from London, etc.)  Cover different flow lengths

29. Crowding function – Demand profiles

30. Crowding function – cost estimates Review of functionality of crowding model within PLANET Concluded that form of the model appears capable of ensuring modelled train loads are limited to realistic levels Higher crowding valuation would cap loads more effectively Review of valuation of crowding 1997 Passenger Demand Forecasting Handbook SRA Research– “Valuation of crowding improvements on rail services” Separate valuation for different service types  London-based inter-urban services  London commuter services  Non-London services

31. Crowding function – cost estimates Suggested crowding penalties for PLANET Factors applied to in-vehicle journey time As outlined in the Outline Model Specification Technical Note, we will be implementing different crowding cost factors for different journey purpose segments. The discussions and conclusions above lead to the following recommended values to be applied in the PLANET model. These are most strongly based on the recent MVA work, but we have attempted to ensure a reasonable rate of cost increase as load factors approach crush capacity. Table 5 ‑ ASuggested crowding penalties for PLANET

32. Validation of PLANET PS2002 models Comprehensive data collection On-train passenger counts, by TOC, direction, and time of train On station counts, by board/alight, and service time / TOC Station entering / leaving counts, by time of day Comparison between observed and modelled data Observed data processed to provide totals by AM Peak / Inter-Peak, TOC, and model link / node

33. PLANET PS2002 Model Validation Central London Termini Cordon Inner London Screenlines Underground National Rail National Rail Screenlines TOC based (e.g. GNER, Great Western)

34. PLANET PS2002 Model Validation

35. Application of PLANET Thameslink 2000 CrossRail Business Case Strategic Plan 2003 European Rail Traffic Management System (ERTMS) Great Western Route modernisation East-West Midlands Multi-Modal Study

36. PLANET Interfaces OUTPUTS ENIF  Thematic maps of time savings  Boarding/Alighting at nodes MapInfo  Thematic maps etc  Spatial Analysis Appraisal Template  Cost-Benefit Analysis

37. PLANET Output using MapInfo/ENIF

38. PLANET Output using MapInfo

39. PLANET Output : Summary Statistics

40. PLANET Output : Generalised Time Savings

41. Appraisal Template: Overview An architecture for consistent investment and policy appraisal converts model outputs, appraisal parameters and cost inputs into value for money measures which can be changed transparently by manipulating the growth and other assumptions Currently being updated for compatibility with the new SRA appraisal criteria Final (Alpha version 5) will be available in early June 2003

42. Appraisal Template: Stages Information Assumptions Costs Road benefits Planet (Interface with model output) Growth factors Growth Cash flows DCFs Summary CBA

43. Appraisal Template: Inputs & Assumptions

44. Appraisal Template: PLANET Inputs

45. Appraisal Template: Cost/Benefit Summary

46. Future PLANET model development Short Term Crowding and assignment procedure (MSA) Demand matrices (inc. LATS+CAPRI+other data sources) Medium Term Multi-modal modelling Four-stage model (Generation, Distribution, Mode Split, Assignment) Improved Appraisal Long Term Land-Use+Transport Interaction model