Public Transport in Gauteng Province: Order out of Chaos

1. Public Transport in Gauteng Province: Order out of Chaos Prof Nevhutanda Alfred Department of Transport(South Africa) Chairperson of South African License Board Forum drnevhu@telkomsa.net

2. Gauteng Map

3. Gauteng Population and Transport Usage • The most densely populated of South Africa's nine provinces, however, is Gauteng, with some 9.6-million people (20.2% of the total population) occupying just 1.4% of the country's land area. • Where one third of the province's population are public transport users • More than 70% of this one third use taxi's as their mode of transport. • It is also assumed that the section of the population that has no access at all to mobility, are most likely to walk, cycle or use a taxi.

4. An Example of a Gauteng Commute • Now we take a look at the examples below to see a typical example of how congestion is changing the amount of time we spend on the road, as well as our traveling speed. (Speeds are average speeds traveled with and without congestion.) • Pretoria to Sandton – am (55km)   Without congestion 35 minutes  at 94,2km/h With congestion 90 minutes at 36,6km/h • Sandton to Sunninghill (10km)   Without congestion 18 minutes at 33,3km/h With congestion 30 minutes at 20km/h Looking at the two trips when the roads are congested, you can see that driving time would increase by 122 minutes. If you were to drive these routes each working day of the month (21 days), you will be on the road for an additional 42,7 hours, and in the course of the working year (11 months) that’s an additional 468,7 hours!For the same number of kilometres reflected on the vehicle’s odometer, your vehicle is running for an extra 469,7 hours. And in that time, if you were traveling at an average speed of about 40km/h and there was no congestion, you could cover nearly 19 000 additional kilometres.

5. Gauteng Traffic Photos

6. Content of Presentation • Problem statement • Travel needs of communities in Gauteng • Corresponding minimum and target LOS • Development of strategic model • Calibration and sensitivity results of model • Shortcomings of the model • Policy analysis and results • Conclusions and Recommendations

7. Problem Statement • Public Transport (PT) in SA and Gauteng riddled with problems • Characterised by poor performance e.g. late arrivals, over-crowdedness, non-availability • Old and unsafe vehicles compromise safety of passengers

8. Research Questions • Is there any PT service available and accessible? • How frequently are the services provided? • I s the service affordable? • What level of service can be expected? • What are the demand and cost implications of providing an improved service?

9. Travel Needs in Gauteng • PT less convenient than private transport, need to be minimised to make service attractive. • The most pressing public transport problems in Gauteng relate to: • Available and accessibility of service • Service capacity (i.e. crowding) • Frequency of service • Cost of public transport • Safety and security issue • Forms basis for KPI development, which provide mechanism for performance evaluation

10. Status Quo Analysis for Province • Walking distances for train services by far the longest (exceed 1000m) • All models have average waiting times less than 10 mkins in AM peak period • Ave spending estimated at only 1.1% above the standard (although +60% of users spend>10% of income on PT) • Low satisfaction ratings regarding personal safety at stations and on vehicles • Nearly 64% of minibus-taxis and 50% of buses older than required lifespan of 10 mand 12 years respectively

11. Selected KPIs & Corresponding Minimum and Target LOS

12. Municipal Areas in Gauteng Average Household Income > R3 000 Average Household Income < R3 000 Average Car Ownership per household < 0.6 Average Car Ownership per household < 0.6 ZONE 1 High Public transport utilization (>50%) ZONE 2 Low Public transport utilization (<50%) Market Segmentation

13. Description of Model Components • Demand Model • Predicts shifts in modal splits due to LOS changes • Utility functions calculate mode utility from attributes • Probability of Selecting mode – LOGIT model • Results feed into resource model • Resource Model: • Determines investment level required • Capital and Operating cost • Impact prediction based on changes in : • Ridership/annum • Pass.km/annum • Cost /passengers (operating, capital , total) • Subsidy levels

14. Sensitivity Tests Highlights • To establish impact of variables on mode choice and cost • Demand most elastic in the following ranges: • Fares: R3.50 – R5.50 • Peak frequency: 5 – 15 dep/hr • Walking time : 0 – 20 mins • Resource model • Fares highest impact on income and cost (e>1) • Least impact on cost from increased service hours and security improvements

15. Calibration of Model Desired calibration goals • Inclusion of PT and car modes • Inclusion of all relevant attributes • Utility function for each mode • Good Stated Preference data required • good prediction of modal split expected Calibration results • Car mode disturbed calibration • Only walk , waiting time/frequency, fare per trip, % income spent on PT incorporated • Underestimation of possible shift in demand • One utility function,diff.ASCs (initially dominant) • Only Revealed Preference data (lack of variation ,no info on alternatives not chosen) • Modal spilt predicted with good accuracy (<0.3%)

16. Main Conclusions & Recommendations • Approach of integration demand / resource (supply) modeling techniques suitable • Minimum LOS less resource deficient • Measures to be prioritised by cost implications can be off-set against increase in fares • Data availability and quality to be improved • Inclusion of all variable in demand model • Additional research for low-income market with low PT utilisation

17. Recommendations • Planning: Ensuring effective and informed planning which prioritised public transport and good land use management. • Public Transport: Ensuring a quality public transport system that offers a realistic alternative to individual transport • Transport Infrastructure: Increasing provision of transport infrastructure with focus on public transport friendly facilities and transformation of delivery • Road Space Management : Ensuring efficiency and effectiveness of the transport system for the movement of people and goods • Regulation: Ensuring regulation of the public and private transport system so that it is efficient and safe. • Freight and Logistics: Ensuring that goods are moved efficiently and safely around the province and between the province and the sub-regions

18. Finito • THANK YOU