TSHWANE TRANSPORT DEMAND MODEL

1. Winterveld Mabopane Rooiwal Garankuwa Kameeldrift Pretoria Hartbeespoort Centurion Midrand South African Emme2 Users Conference 10-11 September 2004 TSHWANE TRANSPORT DEMAND MODEL Presented by: CM Olivier (CTMM)

2. CONTENTS • MODEL • LAND USE • TRAFFIC ZONING AND TRANSPORT NETWORKS • TRIP GENERATION AND DISRIBUTION • MODAL SPLIT • LESSONS LEARNED • CONCLUSIONS

3. CPTR ODHIS RP & SP RSI’s Traffic Counts TT Surveys MODEL DATA UTILIZATION MODEL

4. ZONES TRIP GENERATION ATTRACTION CALIBRATION CPTR PRIVATE NETWORK TRIP DISTRIBUTION ODHIS PUBLIC TRANSPORT NETWORK MODAL SPLIT Done first for free flow conditions Then for congested conditions RP & SP RSI’s EXTERNAL TRIPS Traffic Counts TRIP ASSIGNMENT TT Surveys MODEL DATA UTILIZATION MODEL ZONES TRIP GENERATION ATTRACTION CALIBRATION PRIVATE NETWORK TRIP DISTRIBUTION PUBLIC TRANSPORT NETWORK MODAL SPLIT EXTERNAL TRIPS TRIP ASSIGNMENT

5. CPTR ODHIS RP & SP RSI’s Traffic Counts TT Surveys MODEL DATA UTILIZATION MODEL ZONES TRIP GENERATION ATTRACTION CALIBRATION PRIVATE NETWORK TRIP DISTRIBUTION Land Use Network PUBLIC TRANSPORT NETWORK MODAL SPLIT Public Trans. EXTERNAL TRIPS Not app.. TRIP ASSIGNMENT

6. Population derived from: Flats, duplex, simplex & sectional titles Formal & informal houses Hostels & single people Population divided into: Economic Active = 910 800 Economic non-active=1 140 500 Age < 15 years Scholar/full time student Housewife Pensioner Other Total =2 051 300 Nett. Inflow of 69 500 workers Employment divided into: Formal = 630 200 Retail Office Industrial Ware house Local serving Other inside workers Agriculture/mining Construction Transport Informal = 103 300 Domestics Informal at home, at work Unemployed = 246 800 Unemployed at home, ?work Total = 980 300 POPULATION & EMPLOYMENT

7. TRIP CHAINS RECORDED

8. ZONES • Total zones = 756 • 704 internal & 52 external • Zones were developed according to: • Homogeneity • Maximum number of Private vehicle Public transport person trips for target year 2020 • Zones must fit within GTS2000 zones • Zones were aggregated into: • 60 int+10 ext sub regions • & 19 functional areas for modeling & reporting purposes

9. PRIVATE NETWORK • Expand network to cover area • Transfer bus only links to private network • Correct the network based on collective knowledge • Had to verify according to aerial photographs • Had to travel parts of the network • Correct network geographically

10. PUBLIC TRANPORT NETWORK (1) • Major problems were experienced with CPTR data • The route data does not cover the whole study area • Bus route data • Some routes were incomplete • Directions changes along routes • 650 routes had to be corrected by hand • Only 13% of the routes had time tables • Only 13% of the routes had passenger volumes • Taxi route data • More than two thirds of the routes were only bits & pieces – taxi data were therefore discarded • Rail data • Was not part of the CPTR data

11. PUBLIC TRANPORT NETWORK (3) • Rail • Railway lines from GIS • No operational data -> use previous model’s data • Bus • Route data based on CPTR • Aggregated • Operational data from CPTR and guessed • Taxi • Synthetic hub & spoke system • Operational data guessed • Not used – additional assignment • Walk • On all streets in residential and employment areas • At major transfer areas

12. PUBLIC TRANSPORT NETWORK (2)

13. TRIP GENERATION & ATTRACTION (1) • Start with activity based approach • Too many market segments • End with 5 trip purposes (2 two leg trip chains) • Accept statistic reliable trip generation rates: • Rates based on sub area, functional area or PDI/non-PDI areas • Separate rates for car users and non-car users • Trip generation & attraction is done in EXCEL • Reasons • Socio-economic data, rates and number of trips on one spreadsheet • Easy to balance production & attractions • Easy to determine the effect of assuming rates for external trips & secondary study area • Automate the calculation process for future scenarios

14. MODAL SPLIT (1) • Multi Nomial Logit model • Hierarchical split • Done per group and per trip purpose • Utilities are based on the following variables: • Trip distance • Personal income • Household income • Population density • Employment density • Population & employment mix • Walk time • Transfer time • Total travel time • Fare • Historical choice

15. Combine Without Car & With Car per trip purpose Home-based work person trips Non Vehicle Vehicle Car Public Transport Primary Rail Bus Taxi Secondary Tertiary MODAL SPLIT (2)

16. LESSONS LEARNT - Consultant • Expectations must be in line with the budget & available data • Don’t try to save money by scaling down on: • surveys • tasks • Don’t interrupt the process • Data collection not for modeling purposes, but to be used for modeling purposes does not work • The purpose(s) of the model must be clear • The accuracy of the model must be in line with the purpose(s) & available data • Authority must have a modeler • Simple easy to use models stand better chance to be used than complicated and clumsy models

17. LESSONS LEARNT - Client • Ensure fully committed budget before appointments • Evaluate available data in advance • Comprehensiveness • Mistakes & Format • Pilot study may be needed • Don’t be too ambiguous – start with simplified model • Data in general are expensive • Make sure that data are collected for all important processes dependant on the data • Modelers should drive the data collection process • Design model before planning data collection • A well designed public transport model needs: • Proper survey procedures (checks & balances) • Comprehensive data, including agreements & contracts • All public transport modes included • Sufficient resources

18. CONCLUSIONS In conclusion it can be stated/confirmed that: • Several draw backs were experienced throughout the project • This resulted in unexpected delays & over expenditure of the project • The negative effect of insufficient PT data were overcome to such an extend that • A reasonable model could be developed and calibrated

19. THANK YOU