Mobility   
in the Gauteng City-Region 

Edited by Chris Wray and Graeme Gotz
Chapter contributions by Christo Venter, Willem Badenhorst,  

Guy Trangoš and Christina Culwick



Published by the Gauteng City-Region Observatory (GCRO), 
a partnership of the University of Johannesburg, the 

University of the Witwatersrand, Johannesburg, and the 
Gauteng Provincial Government.

Mobility in the Gauteng City-Region

July 2014

ISBN 978-0-602-620105-2

Edited by: 

Chris Wray and Graeme Gotz

Chapter contributions:

Graeme Gotz and Chris Wray
Christo Venter and Willem Badenhorst
Guy Trangoš
Christina Culwick

Other contributions:

Background report commissioned from University of Johannesburg staff and 
students and contracted specialists: Tracey McKay, Zach Simpson, Kerry Chipp, 
Naeem Patel, Alutious Sithole and Ruan van den Berg

Photographic images by Potsiso Phasha, Christina Culwick, ITL Communication 
& Design and various contributors to a photographic competition run by the 
Gauteng City-Region Observatory (GCRO) in 2013 (credits given with images)

The image on page 104 is the copyright of Media Club South Africa and Gautrain; 
it may not be used for any promotional, advertising or merchandising use, and 
may not be materially altered, nor may its editorial integrity be compromised.

Copyright © Gauteng City-Region Observatory (GCRO)

Design and layout: www.itldesign.co.za

Cover image: easterly view of the new rea vaya Bus rapid transit 
route along Kingsway avenue in JohannesBurg, linKing the university 
of JohannesBurg and the university of the witwatersrand



Contents

anthony gotz

Chapter 1 Introduction: A new ‘golden era’ for transport planning? 1

Chapter 2 2011 GCRO Quality of Life Survey: Analysis of transport data 15

Chapter 3 Constructing a Quality of Transport Index: Gauteng’s priority townships 59

Chapter 4 New spaces of transport in the Gauteng City-Region: A Gautrain analysis 85

Chapter 5 Transitions to non-motorised transport in Gauteng  131

Chapter 6 A photo essay: Non-motorised transport – forging connections  
across space and society  153

References 170

Tables 172

Figures 172



original photo: theo  Khuvutlu



CHAPTER 1 IntroductIon: A new ‘Golden erA’ for trAnsport plAnnInG?

1

Introduction: 
A new ‘golden era’ for transport planning?
graeme gotz and Chris wray

A key factor in understanding a functional city-region is the daily flows of people between its constituent parts. The Organisation 
for Economic Co-operation and Development (OECD), for example, regards the commuter field as a key criterion for defining 
the extent of a metro-region (OECD, 2011). Traffic flow is also an important urban efficiency concern, as congestion impacts the 
costs of doing business, which in turn affects regional competitiveness. Congestion is furthermore a key social issue, as long 
commutes on poorly maintained transit infrastructure affect the quality of life of residents. Transport affordability and access 
are critical development concerns: high day-to-day costs of travel, the unavailability of public transport in many peripheral 
areas, and poor home-to-work connections because of badly defined routes and weak intermodal integration all impact severely 
on the poor, especially in a sprawling city-region where poverty and spatial dislocation are often synonymous. In addition, 
transport can be a major driver of environmental problems such as air pollution and climate change if road-based modes lead 
to high carbon emissions. Alternatively, transport can lead to greater urban sustainability if, for example, a city’s metabolic 
rate of liquid fuel consumption can be reduced though measures that reduce car-based travel. Lastly, transport infrastructure, 
especially that developed for public transport, can have important symbolic and cultural effects, either working productively to 
bring people together in shared public space, or negatively to further entrench societal divisions. 

For all of these reasons it is important to delineate the existing flows of traffic across the Gauteng City-Region (GCR); to 
understand the challenges of transport efficiency, access and affordability; and to gauge the impact of key transport interventions 
like the Gautrain Rapid Rail Link, the Gauteng Freeway Improvement Programme and associated e-tolling, and municipal Bus 
Rapid Transit (BRT) infrastructure. 

This report on Mobility in the Gauteng City-Region has been written in a remarkable moment in the history of transport 
development in Gauteng. On the one hand the region appears to be in a new ‘golden era’ of transit infrastructure design 
and investment, as well as long-term planning for ever-growing commuter transport needs. On the other hand, the transport 
difficulties faced by the GCR’s fast-growing population, as well as the many spatial, social, economic and environmental 
challenges that flow from the region-wide architecture of this population’s daily commuting, appear to be growing ever more 
acute. 



Mobility in the GautenG city-ReGion

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1.1 A new ‘golden era’ for transport 
planning?

At various points in its history the GCR’s urban form has 
been substantially shaped by large transport infrastructure 
investments. T. J. Fair and E. W. Mallows (1959) note how the 
intersection of three railway lines from the coast in the mid 
to late-1890s gave prominence to Germiston, and provided a 
‘broad framework’ for the region’s future settlement pattern: 
“The polynuclear structure, the east-west mining axis and 
the north-south communications axis had emerged. The 
sum of these factors had produced the now clearly-defined 
cruciform nature of the structure built around these two 
dominant axes” (Fair and Mallows, 1959, p.130). Alan Mabin 
(2013, p.29) traces how in the late 1960s and 70s a decade 
of road-infrastructure focused highway planning led to “the 
demarcation of a veritable spaghetti of proposed freeway 
routes.” This intermetropolitan road network cemented the 
conception of a functional region, and shifted the region’s 
centres of gravity, providing structuring elements that by-
passed some older centres while favouring development 
along key corridors in the north (Mabin, 2013). 

In the mid to late-2000s, after decades of underinvestment, 
the GCR appeared to enter a new, dramatically more 
energetic era of transit planning and road and public-
transport infrastructure development. A host of recent major 
projects and innovative plans testify to this new ‘golden era’ 
of transport planning:

• The Gautrain Rapid Rail Link. Led by the Gauteng 
Provincial Government (GPG), with a capital cost to date 
of some R25 billion, the Gautrain fast-rail network is one 
South Africa’s largest transport infrastructure investments. 
Eighty kilometres of track, 15km of it underground, and 
ten stations now knit together the city-region’s key urban 
centres. The O.R. Tambo International Airport to Sandton 
link in the system was opened just before the 2010 FIFA 
World Cup. The final leg of this phase, to Johannesburg’s 
Park Station, was launched in mid-2012. A further set of 
links that will connect the eastern parts of Pretoria, portions 
of the West Rand and Soweto are now being planned.

• BRT. Various BRT systems – such as that illustrated on 
the front cover of this report – are being planned and 
implemented in Gauteng’s metropolitan municipalities: 
Ekurhuleni, Johannesburg and Tshwane. They are jointly 
funded by local and national government. The City of 
Johannesburg has implemented the first of these systems, 
the so-called Rea Vaya BRT. Construction started in 2007 
and phase 1A – connecting Soweto and the Johannesburg 
inner city – was completed in 2009. Phase 1B was finalised 
in early 2014. It also connects the Johannesburg inner city 
to Soweto but runs to the north past the University of the 
Witwatersrand (Wits) and the University of Johannesburg 
(UJ). Construction on phase 1C, which will link Alexandra 
and Sandton to the existing network, was launched in April 
2014. 

• Implementation of a Tshwane BRT system, to be named 
A Re Yeng, is also at an advanced stage. Construction 
started in April 2013, and a first seven kilometre leg will be 
completed in 2014. The first A Re Yeng bus was unveiled to 
the public in April 2014. 

• Passenger Rail Agency of South Africa (PRASA) rail 
modernisation. PRASA is undertaking a complete overhaul 
of its commuter rail systems in Gauteng, following many 
years of underinvestment. Indicatively, the last new trains 
procured for the South African passenger rail network 
were bought in the mid-1980s, and 98% of the current 
rolling stock is older than that (PRASA, 2012). In Gauteng, 
the modernisation programme will focus on the key 
Mabopane-Pretoria-Germiston-Johannesburg-Soweto 
corridor. It will see a combination of new rolling stock, the 
upgrading of track and signalling infrastructure and the 
redevelopment of stations. The delivery of the first of some 
1 200 new train sets (with approximately 7 000 cars) is 
expected in 2015. These trains are to be procured over a 
20-year period. A consortium, majority owned by Alstrom, 
will eventually produce the fleet locally in a new plant in 
Ekurhuleni. PRASA has also commissioned Siemens to 

upgrade the signalling system, with a R1 billion first phase 
set to be completed in 2016. Seventy-three stations in 
Gauteng will eventually be upgraded, with a number (such 
as Vereeniging, Germiston, Krugersdorp and Pretoria) 
identified for short-term investment. 

• Gauteng Freeway Improvement Project. Led by the 
South African National Roads Agency (SANRAL), the 
Gauteng Freeway Improvement Project is a multi-billion 
rand upgrade of Gauteng’s freeways. Initiated in 2007, 
the project has involved the widening of a number of 
highways and the redevelopment of key interchanges, 
which have historically been the cause of bottlenecks in 
traffic flow. Future phases of the project envisage further 
redevelopment and the construction of new freeway links. 
While it has already had a significant positive impact on 
congestion on the region’s highway network, the project 
has not been without controversy because of the associated 
electronic or ‘open-road’ tolling, meant to recoup the costs 
of the new infrastructure. The introduction of e-tolls has 
been marked by public protests and payment avoidance by 
many users. It might also be critiqued for being internally 
contradictory, encouraging, at the same time, more car-
based travel through its improved road infrastructure as 
well as a shift to public transport through the taxing of 
road users. 

• Municipal Integrated Transport Plans (ITPs). Matching the 
large-scale infrastructure projects underway there has been 
a series of new generation transport plans developed in 
both local and provincial spheres of government. A number 
of municipal ITPs, as required by law, were formulated for 
the period 2003-2008, but these are now well out of date. 
However, Gauteng’s metropolitan municipalities are in the 
process of formulating updated ITPs, informed by a recent 
round of household travel surveys in each metro. 

• Long-term integrated transport planning. One of the main 
initiatives of the GPG over the last five years has been 
the development of 25-year Integrated Transport Master 



CHAPTER 1 IntroductIon: A new ‘Golden erA’ for trAnsport plAnnInG?

3

Plan (ITMP25). The IMTP25 vision is for “an integrated 
and efficient transport system in Gauteng that promotes 
sustainable economic growth, skills development and 
job creation, fosters quality of life, socially includes all 
communities and preserves the environment” (GDRT, 
2013a, p.3). The plan provides a framework – although not 
an infallible blueprint, given low levels of intergovernmental 
coordination – to assist all three spheres of government to 
deliver a world class and sustainable transport system that 
prioritises public transport. 

The ITMP25 presents a paradigm shift in spatial and 
transport planning. It serves as a point of departure from 
apartheid spatial planning, land use and mobility, and 
ushers in an integrated and equitable transport value 
chain. It is underpinned by founding principles such as 
economic beneficiation; doing things in a ’smart’ and 
sustainable manner; and integrating transport networks, 
modes and services. ismael vadi, gauteng member of the 
executive council (meC) for roads and transport (gdrt, 
2013a, p.x)

 The ITMP25 sets out eight long-term interventions 
(summarised in Table 1.1). Very significantly, the first two 
interventions – subsidised housing provision in core areas 
and land use densification – are not transport interventions 
in and of themselves. Rather, they are proposals for an 
urban form that both supports and is supported by viable 
public transport networks. This is a noticeable shift from 
the private car focused freeway planning of the 1960s and 
1970s. 

Integrated transport options

Land Use Development

1 subsidised housing provision within urban core areas

2 land use densification in support of public transport

Strategic Public Transport Network

3 reinforcing passenger rail network as the backbone of the system

4 extending the integrated rapid and road-based public transport networks

Freight Transport

5 strengthening freight hubs

Road Transport

6 travel demand management

7 mainstreaming non-motorised transport

8 Continued provincial wide mobility

table 1.1: gauteng 25-year integrated transport interventions (source: gdrt, 2013a, p.x)



Mobility in the GautenG city-ReGion

4

 Rail is regarded as the backbone of an integrated public 
transportation system, with key focus areas being strategic 
modal transfer nodes and interchanges and priority 
public transport corridors (see Figure 1.1 and Figure 1.2). 
Mainstreaming non-motorised transport (NMT) is also 
identified as one of the main interventions.

• Short to medium-term key interventions. Within the 
ambit of the overarching ITMP25 planning process, GPG 
has devised an interim implementation plan to move on 
a number of interventions it regards as critical. This Five-
Year Gauteng Transport Implementation Plan (GTIP5), 
approved in 2012, identifies 13 urgent short-term initiatives 
(summarised in Table 1.2) that are currently in the process 
of being implemented by the Gauteng Department of 
Roads and Transport (GDRT). Examples include the 
release for public comment of a draft policy, Promoting 
Sustainable (Green) Transport in Gauteng, and the launch 
of a GoGauteng mobile application to help commuters 
access scheduling information for a number of public 
transport services, both in April 2014.

Initiatives and key focus areas

1. transport authority for gauteng

 1.1 provincial-wide public transport information Centre

 1.2 “one province one ticket”

2. integration with the Commuter rail Corridor modernisation project of prasa (passenger rail agency of south africa)

3. restructured subsidised road-based public transport

4. transformation of the taxi industry

5. greener public transport vehicles technologies

6. travel demand management, less Congestion and shorter travel times

7. access to major freight nodes

8. international and City airports

9. pedestrian paths and Cycle ways

10. Continued provincial wide mobility

11. effective management of existing transport infrastructure

12. regulation and enforcement

13. accessible transport

table 1.2: imtp5 key short-term initiatives (source: gdrt, 2013a, p.xiii)



CHAPTER 1 IntroductIon: A new ‘Golden erA’ for trAnsport plAnnInG?

5

• A Gauteng Transport Commission, en route to a Transport 
Authority. A crucial factor for the successful delivery 
of an integrated and efficient transport system is a set 
of institutional arrangements that ensure Gauteng-
wide coordinated planning. The IMTP25 proposes the 
establishment of a Gauteng Transport Commission to 
advise on how to deal with the immediate transport issues 
in the province. This has been established and has begun 
its work, hosting a Cycling Indaba to promote NMT at the 
end of March 2014. It is envisaged that the commission 
will eventually evolve into a fully-fledged unitary Transport 
Authority for the GCR. This reflects a welcome city-
regional approach to transport planning and is in line with 
the recommendations of the OECD Territorial Review of 
the GCR for a metropolitan transport authority to improve 
transport coordination and create a single ticketing system 
(OECD, 2011). 

• Integrated transport modelling. GDRT has identified the 
need for integrated land use and transportation planning 
and integrated planning tools to inform robust decision-
making. A recent report on modelling urban spatial 
change highlighted the fragmented approach to transport 
modelling within Gauteng (Wray et al., 2013). Traditionally, 
GDRT has commissioned provincial transport modelling 

from transport consultants. There has also been a varied 
response to transport modelling at a local government 
level with a combination of outsourced and internal models 
and a range of proprietary software. The result has been a 
disjointed approach, limited modelling capacity and skills 
development within government, and a mismatch of macro 
and micro-scale modelling (CSIR, 2012).

 In 2012, terms of reference were issued by GDRT for 
the establishment of the Gauteng Integrated Transport 
Modelling Centre (GITMC). Its aim is to create a fully 
operational modelling centre, co-owned, co-funded and co-
staffed by a range of provincial and municipal departments. 
It will provide high-end planning and modelling skills for a 
variety of macro and micro-modelling support services to 
role-players across the province (CSIR, 2012). The Council 
for Scientific and Industrial Research (CSIR), in conjunction 
with the University of Pretoria, have been appointed to 
set up the GITMC as a multi-year project. The centre will 
initially build on the data and models generated by the 
CSIR UrbanSim and MATSim software urban simulation 
project. It will formulate urban growth scenarios at a 
local and provincial level taking into account current and 
planned transport infrastructure initiatives. The centre is 
planned to be fully operational by 2014.

 It is widely argued that if policies towards spatial planning, 
infrastructure, and service delivery are devolved to the city-
region level and coordinated across relevant local authority 

jurisdictions, they may improve the efficiency of labour 
and housing markets, streamline transport systems, and 

generate economic spin-offs through increased productivity, 
knowledge spill overs, and innovation. 

(turok, 2009, p.846) 



Mobility in the GautenG city-ReGion

6

figure 1.2: itmp25 proposed railway network (source: gdrt, 2013a, p.42)figure 1.1: itmp25 proposed public transport network (source: gdrt, 2013a, p.39)



CHAPTER 1 IntroductIon: A new ‘Golden erA’ for trAnsport plAnnInG?

7

1.2 Key transport challenges
While the current investments in transport infrastructure and 
the energy being put into new plans are both significant, 
the test of this ‘golden era’ of planning and development 
will be whether it makes a real and substantial impact on 
the GCR’s many transport, and associated social, economic 
and environmental challenges. The challenges are deep and 
structural, and in some important respects there is evidence 
of them intensifying. 

• Modal shifts to less sustainable modes of transport. The 
transport system designed in the 1960s and 1970s – based 
on the assumption that road-based transport will be the 
dominant form of commuting – is no longer optimal. 
However, over the decades it has facilitated a major shift in 
the dominant modes of transport in Gauteng. Interestingly, 
as shown in Table 1.3, the available survey evidence does 
not indicate a large proportional shift to private vehicles, 
even though the number of cars on the GCR’s roads has 
increased dramatically. In the 1970s half of all home-to-
work trips were made by private cars. The proportion has 
dropped slightly to just above 40%. The more dramatic 
shift has been out of the conventional publicly owned and 
managed pubic transport systems – bus and rail – and into 
the privately owned form of public transport offered by 
minibus taxis (see Table 1.3). The main reason for this shift 
has been the continued deterioration in the quality and 
reliability of metropolitan commuter rail and bus services 
(GDRT, 2013a). While the Gautrain and BRT infrastructure 
investments aim to arrest this drift and provide more public 
transport choice, they will for the foreseeable future only 
address the needs of a limited social and demographic 
market, and will not do much to address the needs of poor 
and peripherally located households. 

Walk Rail Taxi Bus Private

1975 pretoria-witwatersrand-vereeniging (pwv) 
transportation survey 7% 20% 3% 22% 49%

1999/2003 1998/99 tshwane survey and 2002/03 gauteng 
transport survey for the gts 2000 survey 9% 6% 31% 6% 48%

2003 national household travel survey 11% 9% 31% 6% 42%

2009 gCro’s Quality of life (Qol) survey (gauteng 
results only) 10% 4% 41% 4% 41%

2011 gCro’s Qol survey 6% 5% 42% 3% 43%

2013 national household travel survey 13% 7% 30% 5% 44%

table 1.3: modal split in mode of transport to work, 19751, 1999/20032, 20033, 20094, 20115 and 20136 (note: the surveys are not 
strictly comparable because of different samples and ways of asking questions; the results should be taken as indicative of broad 
patterns only)

1 PWV Transportation Survey, 1975. This was based on 10 080 households surveyed in the Pretoria area and a further 5 500 in the rest of the PWV area (Gauteng 
Department of Public Transport, Roads and Works, 2006).

2 The GTS 2000 data is based on two large transport surveys, a 7 569 sample Household Survey in and around Tshwane in 1998/99, combined with a 15 375 sample 
survey in the remainder of Gauteng in 2002/03. 

3 This survey was conducted across the country in 2003. Of a national sample of 45 346 completed household surveys, 7 906 were enumerated in Gauteng (National 
Department of Transport, 2007). 

4 Own workings from GCRO’s 2009 QoL Survey. These figures reflect respondents from Gauteng only. Only cases of respondents who travelled to work were selected, 
giving a working sample of 2 334 within the total Gauteng sample of 5 822. 

5 Own workings from GCRO’s 2011 QoL Survey. Only cases of respondents who travelled to work were selected giving a working sample of 5 957 within a total Gauteng 
sample of 16 729 respondents.

6 This survey was conducted in 2013, with results released in March 2014. Gauteng saw a sample of 10 683 dwelling units (StatsSA, 2014).



Mobility in the GautenG city-ReGion

8

• Ongoing sprawl and relatively low density development. 
The transport mode being used will reflect the choices 
of commuters over the quality of the services being 
offered, their affordability, and of course the ability of the 
networked services on offer to take them to their preferred 
destination. A very important consideration is overall 
access to a particular mode, usually established by means 
of data on how far a commuter needs to walk to the nearest 
service point, whether it be a bus stop, train station, or a 
taxi rank. It is conceivable that the infiltration of more agile 
minibus taxi networks into previously unserviced areas 
may be reducing average travel times for many residents. 
But the latest data from the National Household Travel 
Survey 2013 points to a worrying trend of greater walking 
times to public transport. In 2003, 11.3% of Gauteng home-
to-work commuters walked more than 15 minutes to a 
public transport stop at the start of their journey. In 2013 
this had increased to 17%. This suggests that even while 
public transport services are being improved, accessibility 
is declining (StatsSA, 2014). 

 A key reason for this is the ongoing spatial distortions in 
the GCR’s settlement patterns. Massive Reconstruction and 
Development Programme (RDP) housing developments 
on the fringes of the city-region have not coincided with 
the provision of public transport in these areas, leading to 
inaccessible and poor access/poor mobility townships (see 
chapters 2 and 3 of this report). In addition, a swathe of 
gated communities has redefined residential landscapes in 
Gauteng over the last decade. Densities in these estates 
are too low to support a viable public transport network, 

but too high for the road network to cope given the 
inevitable generation of car-based trips. Current land use 
patterns and resulting traffic congestion are antithetical to 
sustainable long-term economic growth and development 
in Gauteng, and it is this that key interventions in the 
ITMP25 aim to correct (Van der Merwe, 2013).

• Affordability. According to the OECD, commuting in 
GCR cities ranks as the least affordable in Africa, with 
21% of monthly income spent on transport (OECD, 2011) 
– this prior to the introduction of e-tolling on upgraded 
highways. Latest evidence from the National Household 
Travel Survey released in March 2014 indicates that train 
commuters spent an average of R466 per month on this 
mode of transport; bus commuters spent R580 per month 
and taxi commuters R625 per month. By contrast, car 
drivers spent R1 727 per month. The survey also finds 
that 44% of Gauteng households had monthly household 
expenditures of less R1 800 (StatsSA, 2014). Indicatively 
this suggests that public transport costs were upwards of 
26% of monthly household expenditures for nearly half of 
Gauteng households.

• Still inadequate resources for transport infrastructure. The 
roll out of the Gautrain system and the municipal BRT 
initiatives by the metropolitan municipalities of Ekurhuleni, 
Johannesburg and Tshwane testify to the financial 
commitment of local, provincial and national government 
to invest significantly in new transport infrastructure in 
Gauteng. Transport Minister Dipuo Peters recently reported 
that more than R5 billion would be spent in 13 South African 
cities on planning, building and operating integrated 

public transport networks in the 2013/2014 financial year 
(Venter, 2013a). However, while current funding allocated 
to transport infrastructure and operations has grown 
rapidly over the last decade, it is still far from sufficient. 
Inadequate funding is one of the key challenges identified 
in the ITMP25. According to the project manager of the 
ITMP25 process, Jack van der Merwe, transport budgets 
ideally need to be doubled in the short term and increased 
to four times the current level over 25 years (Van der 
Merwe, 2013).

• Poor intergovernmental coordination. Another constraint 
is the fact that the existing transport systems in the GCR 
are not well integrated, with overlapping roles of national, 
provincial and local transport departments and a lack of co-
ordination between municipalities, leading to a fragmented 
approach to transport planning (OECD, 2011). A recent 
example of the lack of co-ordination between the transport 
departments within the GCR is a series of household travel 
surveys conducted in the three metropolitan municipalities 
in Gauteng. Each of the metros has run separate transport 
surveys to assist with formulating revised their ITPs. While 
some effort was made to standardise questionnaires 
and sample frames between the municipalities, each 
municipality by and large took its own approach in relation 
to sampling and the definition of destination points, which 
means there are likely to be limitations on data integration 
and aggregation. This has consequences for Gauteng-wide 
modelling required by GDRT and limits the analysis of the 
immense traffic flow between the metros as highlighted in 
Figure 1.4.



CHAPTER 1 IntroductIon: A new ‘Golden erA’ for trAnsport plAnnInG?

9

figure 1.3: major transport infrastructure in the gCr (source: gauteng department of roads and transport)



Mobility in the GautenG city-ReGion

10

• Insufficient GCR-wide planning. Transport planning 
also needs to take note of the wider GCR connections 
and daily external flow of both people and goods into 
and out of Gauteng. For example, the Moloto corridor 
connects a swathe of semi-urban settlements situated 
in the Thembisile and J.R. Moroka local municipalities in 
Mpumalanga on the north-eastern border of Gauteng. This 
corridor provides a vital connection for these settlements 

to the Gauteng economy through subsidised bus transport 
routes, which have historically ferried thousands of workers 
into central Pretoria on a long-distance daily commute. 
According to the National Minister of Transport, Dipuo 
Peters, “Commuters spend long hours in transit, with some, 
in extreme cases, spending up to seven hours per day on 
buses” (Venter, 2013a, p.1). 

figure 1.4: transport flows into and within the three gauteng metros according to 2011 Qol survey data



CHAPTER 1 IntroductIon: A new ‘Golden erA’ for trAnsport plAnnInG?

11

1.3 Overview of this report
This report is framed in the context of this remarkable 
moment, which sees enormous energy and resources being 
put into new and forward-thinking transport plans, as well 
as large-scale and often region-wide transit infrastructure, 
but also intensifying challenges. It is not within the scope of 
a report such as this to review every strategic intervention, 
nor critically assess every challenge. However, a wide-ranging 
analysis of the current ‘state of mobility’ in the GCR, and the 
impact of key infrastructures – or the consequences of their 
absence – is warranted. 

This report collects a number of papers written as part of 
a multi-year GCRO project on mobility in the GCR. The aim 
of the project was to: i) better understand the historical and 
current transport trends, based primarily on an analysis the 
GCRO’s own datasets, in particular the transport questions 
in a bi-annual QoL Survey; and ii) gauge the impact of key 
transport infrastructure interventions and the effects of a lack 
of infrastructure in some areas. 

In 2011 GCRO appointed UJ’s Department of Civil Engineering 
Science and Department of Geography, Environmental 
Management and Energy Studies, to carry out transport 
research in the GCR using the 2009 QoL Survey and previous 
transport surveys such as the GTS 2000 and the 2003 
National Household Travel Survey. Key snippets from the 
UJ research (McKay and Simpson et al., 2013) appear in this 
report as extracts and boxes, providing an insightful historical 
perspective on transport challenges in the region.

In 2012 Professor Christo Venter from the University of Pretoria 
was commissioned to develop a report for GDRT analysing 
data from the transport sections of the 2011 QoL Survey. This 

analysis is presented here as Chapter 2. The chapter examines 
transport patterns (including mode use, trip purposes, travel 
distances and speeds); satisfaction and perceived problems 
with transport; and the spatial variation of these patterns 
across the province. Data across municipalities and different 
types of urban settlement typologies are compared in order 
to identify underlying spatial factors affecting travel patterns. 
The chapter concludes by reflecting on the implications of 
the findings for transport planning and spatial development 
policy in Gauteng.

This initial broad analysis of the 2011 QoL transport data is 
further extended in Chapter 3, where Christo Venter develops 
a ‘Quality of Transport’ (QoT) Index. The intention of the index 
is to provide a single measure reflecting residents’ everyday 
lived experiences of the quality of their transport in 20 
‘priority townships’ identified by the GPG. The construction 
of the index is driven by the understanding that transport 
access and connectivity issues are key to the quality of life 
enjoyed by residents in specific areas. Transport realities vary 
considerably across the city-region and the QoT Index gives a 
useful single measure of this variation.

In Chapter 4, GCRO researcher Guy Trangoš provides a multi-
scalar analysis of four Gautrain stations, interrogating the 
quality of the public realm created by the stations’ designs and 
their integration into the immediate surrounding precincts. 
The analysis is underpinned by a brief review of the historical 
context of transport planning and the development of spatial 
policies by local government in response to the implementation 
of the Gautrain infrastructure. Recommendations for similar 
projects in the future are offered in the closing section – 

valuable research to be considered by authorities should the 
proposed extensions to the Gautrain go ahead.

An often ignored but, from a sustainability perspective, an 
increasingly important aspect of transport is NMT. This report 
concludes with two NMT chapters by GCRO researcher 
Christina Culwick. Chapter 5 explores the state of NMT in the 
GCR. It reviews the current policy environment supporting 
NMT; provides a demographic profile of typical NMT ‘users’, 
focusing on the poor who use NMT out of necessity rather 
than choice; and assesses current NMT infrastructure projects. 
In its conclusion the chapter highlights the transitions needed 
to facilitate greater uptake and a modal shift towards NMT 
as a legitimate component of an integrated transport system. 

The challenges and potential opportunities for the future of 
NMT in the city-region are visually portrayed in the form of a 
photo essay in Chapter 6, the final chapter of this report. 

Within the frame of the enormous scale of transport planning 
and infrastructure development underway, as well as the GCR’s 
many deep and enduring transport challenges, it is hoped that 
this report will make a contribution to understanding past and 
current trends, the impact of and (missed) opportunities in 
key infrastructure investments, and some of the key current 
priorities that need more attention in this new ‘golden age’ of 
transport planning.

Not all transport 
dreams can be fulfilled: 

priorities are key. 
(npC, 2011, p.163) 



Mobility in the GautenG city-ReGion

12

Beyond ‘predict and provide’? insights from a comparison of 
historical surveys

in an earlier phase of its ‘mobility in the gCr’ project, gCro commissioned a group of academics from 
uJ to analyse historical transport surveys, and to compare results from these with data from the gCro’s 
2009 Qol survey. the academics, from uJ’s department of Civil engineering science and department of 
geography, environmental management and energy studies, worked with contracted experts and graduate 
students to assemble and interrogate the historical data, inter alia from the pwv transportation study of 
1975. ultimately, the analysis concluded that the historical surveys were too different in scope and sampling 
methods for meaningful comparisons to be made with the more recent 2009 survey. nevertheless, the 
report – Mobility in context: overview and analysis of transportation data for Gauteng (1975-2009) – offered 
some important insights. these include:

The old political regime (and, in some instances, the post-apartheid regime as well) adopted the 
‘predict and provide’ method by which important decisions regarding the design and upgrade 
of transportation networks were made.  However, the ‘predict and provide’ method relies heavily 
on the collection of reliable transportation data. One means of collecting such data is through 
the use of transport surveys. These surveys are then used to predict the challenges facing the 
transport sector so as to guide the development of solutions to these challenges. …

Overall, the ‘predict and provide’ method has resulted in government simply providing more 
road infrastructure, with a specific focus on private vehicles and, as of late, trucking. The Gauteng 
Freeway Improvement Project is a recent example of this. It is crucial to start to question if 
this is an effective solution to the challenges facing commuters (Rodrigue, Comtois and Slack, 
2006).  It is argued here that, in order to successfully manage a region’s transport system, 
greater focus should be placed on implementing strategies that will limit growth in the number 
of motor vehicles on the road.  … One strategy that can address this challenge is increasing the 
usage of public transport and another is re-thinking the urban planning models that have been 
in use. (mcKay and simpson et al., 2013, p.1)



13graeme gotz 



Mobility in the GautenG city-ReGion

original photo: hao-ting wong



Chapter 2 2011 gcro quality of life survey: analysis of transport data

15

2011 GCRO Quality of Life Survey: 
Analysis of transport data
Christo venter and willem Badenhorst

2.1  Introduction
The Gauteng City-Region Observatory (GCRO) has 
commissioned two Quality of Life (QoL) Surveys, in 2009 
and 2011, which measured the socio-economic circumstances, 
perceptions of service delivery, values, psycho-social 
attitudes, and other characteristics of residents in the Gauteng 
City-Region (GCR). The two surveys asked respondents 
a series of questions about their trip-making behaviour 
and their perceptions of transportation in the city-region. 
The 2011 survey covered 16 729 sample points, with Global 
Positioning System (GPS) points at respondents’ houses and 
trip destination points captured from a suburb-level list. This 
chapter provides an analysis of the 2011 QoL Survey, with the 
main aim of providing an up-to-date picture of travel patterns 
and opinions regarding transport and mobility in the province. 
Apart from standard tabulations of travel patterns and 
opinions across user groups and municipalities, we undertake 
a more in-depth exploration of the realities of access and 
mobility across different types of settlements in Gauteng. 

2.2 Key findings
This section provides an overview of key transport-related 
findings for Gauteng from the 2011 QoL Survey, comparing 
the findings across municipalities wherever appropriate. 
All analysis is based on the weighted dataset and is thus 
representative of the surveyed population (18 years and older) 
at provincial and municipal level. 

Sections 2.2.1 - 2.2.5 refer to a single trip described by each 
respondent in the survey. Respondents were asked about 
“the trip that you make MOST often, that involves using 
transport (taxis or cars or trains and so on).” No information 
was gathered about the relative frequency of the trip (i.e. how 
often it is made), so aggregate statistics calculated on this 
sample of trips do not reflect the population of all trips in the 
province. However, the data are useful for comparing across 
subgroups of trips in the sample, such as trips by mode or 
trip purpose.



Mobility in the GautenG city-ReGion

16

2.2.1 main trip purpose
Firstly, only about half of the trips people regard as their most 
frequent trips are to work, followed by shopping (21% of trips) 
and looking for work (12% of trips). The conventional focus of 
transport planning, which is very oriented towards the trip to 
work, misses major components of daily mobility. Secondly, 
about 12% of the sample identified the trip to look for work 
as their most frequent trip. Travel to look for work is of major 
importance to a sizable number of people, yet has received 
little attention in policy or planning. 

The figures above differ slightly from the main trip purposes 
identified by the National Household Travel Survey (NHTS) 
for Gauteng in 2003 (Table 2.1). In this survey respondents 
were asked to identify the purpose of all trips made by all 
household members on a particular day, thus more accurately 
reflecting the true distribution of trip purposes. In particular, 
the GCRO QoL data undercount school travel, as it only 
relates to the most frequent trip of the respondent, who by 
definition in this survey was a household member 18 years and 
older, and not necessarily those of children in the household 
(refer to section 2.2.6 for more on school travel).

2.2.2 mode used for main trip purpose
Respondents were asked which modes they used while 
making the most frequent trip. Figure 2.2 shows the mode 
used over the longest distance of that trip – referred to as the 
main mode from here onwards.7

9% other

48% work

12% look for work

6% education

21% shop

2% serve children

2% social/leisure

figure 2.1: trip pupose of most frequent trip

7 Note that the figures do not necessarily correlate to the overall percentage of 
people using a particular mode.



Chapter 2 2011 gcro quality of life survey: analysis of transport data

17

Cars and taxis8 dominate across all trip purposes. For getting 
to work, cars and taxis are equally important. Taxis are a very 
important mode for work-seekers, with almost three out of 
four work-seekers depending on a taxi. Taxis are also used for 
a variety of other purposes such as education and shopping/
leisure trips. Buses and trains play a minor role across all trip 
purposes.

A relatively small share of most frequent trips are made by only 
walking. However, it is likely that the importance of walking 
is underrepresented here as it does not reflect the walking 
component to and from public transport. Furthermore, many 
respondents might not have thought of walking as ‘transport’ 
and therefore not reported walking trips even if they were the 
most frequent.

Trip purpose % of household members 
naming purpose

work 39.3%

education 29.9%

shopping 44.1%

visiting 33.9%

table 2.1: trip purposes of all household members, nhts 2003 
(source: dot, 2005)

figure 2.2: main mode used for most frequent trip

all trips

other

shopping/leisure

education

look for work

work

8 33 50 3 5

9 33 50 2 3

9 28 57 2 3

13 32 44 5 6

6 9 73 2 9

6 42 42 3 5

0 10 20 30 40 50 60 70 80 90 100

percentage

walk Bicycle Car/motorbike taxi Bus/Brt train other

8 Taxis refer to minibus taxis.



Mobility in the GautenG city-ReGion

18

To identify the incidence of multimodal trips, i.e. trips 
that make use of more than one mode, we examined the 
combinations of modes reported. Only 3.4% of respondents 
make use of both public transport and cars on their most 
frequent trip, probably reflecting the role of public transport 
as a ‘mode of captivity’ that is abandoned altogether as 
soon as a car is bought. Among multimodal trips from one 
public transport mode to another, taxi-and-train is the most 
common combination (10.6% of trips). Transferring between 
other combinations of modes is rare. 

Combination of modes % of respondents
Walk only 10.2%

Car only (driver or passenger) 29.7%

Public transport only 56.7%

taxi only 42.0%

Bus only 1.9%

train only 2.5%

taxi and bus 0.6%

taxi and train 10.6%

Bus and train  0.1%

 Car and public transport 3.4%

table 2.2: mode combinations (excluding ‘other’)

To examine the distribution of public transport use across 
income groups, Figure 2.3 plots the answer to the question 
“Do you ever use public transport?” by monthly household 
income. It is clear that public transport use is very skewed 
towards lower income respondents, with 70% or more of 
people with household incomes below R6 400 per month 
using public transport. Above this income threshold of R6 400, 
public transport use drops off significantly to 60%, and then 
further to below 40% in the next bracket. The threshold of 
R6 400 evidently corresponds to the income level at which 
car ownership starts to become feasible, causing a shift away 
from public transport use. 

Two other observations are significant. Firstly, about 30% 
of people reporting no income do not use public transport 
at all, suggesting a tendency to walk or to curtail travel if 
public transport is unaffordable. Secondly, even in the highest 
income brackets, between 10% and 20% of people still use 
public transport, although this may not be daily, and might 
refer to Gautrain use. The implication is, however, that a 
willingness to use public transport exists among a portion of 
even the very affluent. 

figure 2.3: public transport use by monthly household income

use public transport does not use public transport

100

80

60

40

20

0

n
o

 in
co

m
e

r
1 

- 
r

4
0

0

r
4

0
1 

- 
r

8
0

0

r
8

0
1 

- 
r

1 
6

0
0

r
1 

6
0

1 
- 

r
3

 2
0

0

r
3

 2
0

1 
- 

r
6

 4
0

0

r
6

 4
0

1 
- 

r
12

 8
0

0

r
12

 8
0

1 
- 

r
25

 6
0

0

r
25

 6
0

1 
- 

r
51

 2
0

0

r
51

 2
0

1 
- 

r
10

2 
4

0
0

r
10

2 
4

0
1 

- 
r

20
4

 8
0

0

r
20

4
 8

0
1 

o
r 

m
o

re

r
es

p
o

n
se

 n
o

t 
g

iv
en

p
er

ce
n

ta
g

e 71

29

83

17

86

14

81

19

82

18

76

24

58

42

34

66

21

79

13

87

22

78

16

84

65

35



Chapter 2 2011 gcro quality of life survey: analysis of transport data

19

2.2.3 trip purpose and mode use by sex
Figure 2.4 examines differences in trip purposes (of the most 
frequent trip) between men and women in the sample. It shows 
that men tend to make more work trips (56% vs. 41% of trips), 
while women make significantly more trips to do shopping 
(27% vs. 14%), taking children to school (3% vs. 1%), and other 
(10% vs. 8%). This suggests that women in South African 
cities still tend to undertake more household-related travel, 
while men do more work travel. Women and men have similar 
proportions of travel looking for work, perhaps pointing to the 
mounting pressures women face to find employment as either 
the primary breadwinner or secondary worker in the family.

figure 2.4: trip purpose of most frequent trip, by sex

8% other

56% work

13% look for work

6% education

14% shop

1% serve children

2% social/leisure

10% other

41% work

11% look for work6% education

27% shop

3% serve children

2% social/leisure

male female



Mobility in the GautenG city-ReGion

20

These differences in trip purposes between men and women 
also lead to differences in mode use. Figure 2.5 shows that 
women tend to use taxis more frequently for work, looking 
for work and shopping/leisure trips, as compared to men. 
Coupled with the higher incidence of shopping/leisure travel 
among women, this means that women make significantly 
more trips by taxi than men. Men tend to have a higher use 
of cars across all trip purposes. The implication is that any 
transport policies or interventions that affect the quality or 
cost of public transport services – especially taxis – have 
significant gender implications.

2.2.4 mode to work, by municipality
Looking at the main mode for work trips by municipality 
(Figure 2.6) it is clear that mode use varies across different 
parts of the province. Cars are more important in the higher-
income municipalities of Midvaal, Tshwane, Johannesburg 
and Mogale City, while taxis dominate elsewhere. Train use 
closely follows the availability of the Metrorail network in 

various parts of the province. 

figure 2.5: main mode used for most frequent trip, by sex

percentage

walk Bicycle Car/motorbike taxi Bus/Brt train other

all trips (f)

all trips (m)

shopping/leisure (f)

shopping/leisure (m) 

look for work (f)

look for work (m)

work (f)

work (m)

0 10 20 30 40 50 60 70 80 90 100

6 10 69 12

6 8 77 7

10 31 53 3

9 27 59

7 30

8 37 46 6

54 4

6 38 47 5

7 46 38 5



Chapter 2 2011 gcro quality of life survey: analysis of transport data

21

figure 2.6: main mode used for work trips, by municipality

2.2.5 average travel time
Respondents were asked to estimate how long it took them 
to reach their destination during the trip they undertook most 
frequently. Figure 2.7 and Figure 2.8 show the average travel 
time for the three main trip purposes by municipality.

Reported travel times vary slightly across the metropolitan 
municipalities. Travellers in Tshwane travel longest to get 
to work, but shortest to shopping places. Johannesburg 
residents take the longest to travel to shopping destinations. 
Overall, though, the similarities in travel times are striking.

Non-metro areas differ more significantly. West Rand residents 
(including Westonaria, Mogale, Merafong, and Randfontein) 
have shorter travel times to work/job search destinations, 
but longer shopping destination travel times, as compared to 
residents of Sedibeng District (Midvaal, Emfuleni and Lesedi). 
However, we would caution against drawing solid conclusions 
from this travel time data, as there is reason to doubt the 
accuracy of the travel times reported by respondents in this 
format (principally because the question wording did not 
follow standard practice in travel survey methodology, and the 
sample sizes for specific trip purposes in some municipalities 
are too small to support strong analysis).

gauteng (n=5 955)

westonaria (n=95)

tshwane (n=1 399)

randfontein (n=76)

mogale (n=216)

midvaal (n=49)

meratong (n=143)

lesedi (n=44)

Johannesburg (n=2 217)

emfuleni (n=450)

ekurhuleni (n=1 265)

0 10 20 30 40 50 60 70 80 90 100

percentage

walk Bicycle Car/motorbike taxi Bus/Brt train other

42 42

29 51

46 40

47 41

44 44

59 29

36 39

34 57

42 42

37 50

41 42



Mobility in the GautenG city-ReGion

22

figure 2.7: average travel time (minutes) for the three main trip purposes in metros figure 2.8: average travel time (minutes) for the three main trip purposes in district municipalities

work look for work shopping

ekhurhuleni Johannesburg tshwane

60

50

40

30

20

10

0

m
in

u
te

s

43 44
46

49 47 46 47

40
42

average travel time (minutes)average travel time (minutes)

work look for work shopping

west rand district sedibeng

60

50

40

30

20

10

0

42

47
45

52

34

44

m
in

u
te

s



Chapter 2 2011 gcro quality of life survey: analysis of transport data

23

2.2.6 school travel
The survey asked respondents specific questions about the 
travel conditions of school-attending children in the household 
(alternating between the eldest and the youngest child). In 
total, 37% of respondents reported that their households had 
one or more children in school, making school transport an 
important issue in the province.

About half of trips to school are made on foot, and Figure 
2.9 shows that a smaller proportion of trips are made by car, 
taxi and school bus. However, public transport also plays an 
important role in providing children with access to education 
in Gauteng: about a quarter of school children in the sample 
use taxis, buses or trains. School buses transport about 8% of 
school children to school. Only 2% of children use bicycles. 

figure 2.9: main mode for trips to school

1% train

51% walk

2% Bicycle

19% Car/motorbike

15% taxi

8% school bus

3% other bus
1% other



Mobility in the GautenG city-ReGion

24

Figure 2.10 plots the distribution of the time between when 
children leave home, and the start of school (here called ‘time 
to school bell’), for users of different modes. The evidence 
indicates that transport conditions require many children to 
leave home very early to get to school, although we cannot 
be sure, on the basis of the way the question was asked, that 
children did not arrive at school in good time well ahead of 
the start of classes. Approximately 42% of children travelling 
by bus have to leave more than an hour before the school bell. 
This is slightly less for those travelling by taxi (39%), while 
29% of those travelling by car spent more than an hour on the 
road. Being driven to school by a parent evidently still requires 
many children to leave very early. Children who walk to school 
are, interestingly, best off: only 14% leave home more than an 
hour before the bell.

figure 2.10: time between leaving home and school bell, for all school trips

Bus time to school bell

50

40

30

20

10

0
<15 
min

15-30 
min

31-45 
min

46-60 
min

>60 
min

p
er

ce
n

ta
g

e

50

40

30

20

10

0

walk time to school bell

<15 
min

15-30 
min

31-45 
min

46-60 
min

>60 
min

p
er

ce
n

ta
g

e

taxi time to school bell

50

40

30

20

10

0
<15 
min

15-30 
min

31-45 
min

46-60 
min

>60 
min

p
er

ce
n

ta
g

e

50

40

30

20

10

0

Car time to school bell

<15 
min

15-30 
min

31-45 
min

46-60 
min

>60 
min

p
er

ce
n

ta
g

e



Chapter 2 2011 gcro quality of life survey: analysis of transport data

25

2.2.7 access to public transport
The QoL Survey measured access to public transport by 
asking respondents to estimate the walking time from their 
house to the nearest taxi stop, bus stop or train station. 
The results show that public transport access in Gauteng 
is reasonably good (see Figure 2.11). Overall, almost three-
quarters of households live within a ten minute walk of a 
public transport service, and 95% live within a 30 minute walk 
(about two kilometres). 

These figures correspond well with the NHTS findings from 
2003, which indicated that 91.8% of Gauteng households 
live within a 30 minute walk from public transport. Gauteng 
outperformed other provinces on this measure. However, 
public transport access is somewhat uneven across the 
province. Access is better in metropolitan municipalities 
than in district municipality areas, with Lesedi, Midvaal and 
Mogale City performing worst. In Midvaal, for example, 47% of 
households live further than 10 minutes from public transport.

The number of respondents who could not answer this 
question reflects people who either have no knowledge of 
public transport, or have no public transport within a walkable 
distance from their home. This percentage ranged between 
10% of respondents (in Lesedi) and 24% (in Midvaal), with an 
average of 13% for Gauteng. Figure 2.11 excludes these figures.

figure 2.11: walking time to nearest public transport, by municipality

100

80

60

40

20

0

e
ku

rh
u

le
n

i

e
m

fu
le

n
i

Jo
h

an
n

es
b

u
rg

l
es

ed
i

m
er

af
o

n
g

m
id

va
al

m
o

g
al

e

r
an

d
fo

n
te

in

ts
hw

an
e

w
es

to
n

ar
ia

g
au

te
n

g

p
er

ce
n

ta
g

e

75

21

4

66

30

4

75

20

5

63

26

12

68

26

5

53

37

11

62

30

8

74

21

5

70

25

5

64

30

6

72

23

5

within 10 minutes 11-30 minutes more than 30 minutes



Mobility in the GautenG city-ReGion

26

2.2.8 household expenditure on transport
Respondents were asked to estimate the total amount 
their households spend on transport each month. Recent 
research on expenditure questions in travel surveys suggests 
that responses to such questions frequently have large 
measurement errors (Behrens and Venter, 2006). Nevertheless, 
even if the absolute numbers are questionable, they might 
give useful insight when compared across subgroups of the 
sample.

Figure 2.12 shows the percentage of households spending 
more than specified amounts on transport monthly. Car 
users spend more on transport than public transport users, 
which is to be expected although car costs are usually greatly 
underestimated by respondents with cars. Interestingly, 
residents of metropolitan areas spend about R200 more 
on transport per month than residents of non-metro 
municipalities. This could reflect either more trips being made, 
or longer distances travelled in metro areas as compared to 
non-metro areas. 

However, the higher costs of car use are offset by income 
differences. Car users have much higher incomes than public 
transport users – about 40% of metro car users spend more 
than 10% of their (approximate) median incomes on transport. 
This rises to 55% for non-metro car users, and almost 80% for 
public transport users.

figure 2.12: percentage of households spending more than specified amounts on transport per month

public transport users (metro) 
public transport users (non-metro)
Car users (metro)
Car users (non-metro)

10% of median income

r200 r400 r600 r800 r1000 r1500

100

80

60

40

20

0

p
er

ce
n

ta
g

e



Chapter 2 2011 gcro quality of life survey: analysis of transport data

27

2.2.9 satisfaction with transport
To gauge people’s general satisfaction with transport, 
respondents were asked to rate their satisfaction on a five-
point Likert scale (from very satisfied to very dissatisfied) 
with the type of transport they most frequently use. Results 
are shown in the figures below (see Figure 2.13, Figure 2.14 
and Figure 2.15).

In general, satisfaction with transport is highest in Midvaal, 
Merafong, Lesedi and Randfontein municipalities, and lowest 
in Ekurhuleni, Johannesburg and Mogale City. These figures 
do not correlate well with other more objective measures of 
transport service quality mentioned before, such as public 
transport coverage and travel times, although it needs to 
be borne in mind that the graph (Figure 2.13) does not 
distinguish between public and private modes. Expectations 
might also be different in metropolitan and non-metro areas. 
Overall, however, people seem relatively satisfied with the 
transport they use. On average, 75% of respondents described 
themselves as either satisfied or very satisfied with their 
transport.

Satisfaction does not vary much by sex, as indicated in Figure 
2.14.

figure 2.13: satisfaction with transport, by municipality

figure 2.14: satisfaction with transport, by sex

female

male

0 10 20 30 40 50 60 70 80 90 100

percentage

very satisfied satisfied neither dissatisfied very dissatisfied

15 60 11 11 4

17 59 9 11 4

westonaria 

tshwane

randfontein

mogale

midvaal

meratong

lesedi

Johannesburg

emfuleni

ekurhuleni

0 10 20 30 40 50 60 70 80 90 100

percentage

very satisfied satisfied neither dissatisfied very dissatisfied

33 48 9 9

17 65 8 7

21 62 8 8

18 60 6 14

31 55 6 6

20 66 6 7

32 50 8 3

14 61 10 11

26 49 11 11

13 54 12 16



Mobility in the GautenG city-ReGion

28

figure 2.15: satisfaction with transport, by mode (note: *sample<30)

Satisfaction with transport varies markedly, however, 
depending on the mode people use (Figure 2.15). Car users 
are the most satisfied with their transport, and more so if 
the respondent is a driver (92% are satisfied) rather than a 
passenger (88%) or lift club member (82%). Motorbike users 
(86% satisfied) are also satisfied with transport conditions. 
Evidently the freedom and flexibility offered by a private car 
counts for much in people’s subjective perception – the very 
thing that is difficult to offer with public transport options. 

Ignoring the modes with very small sample sizes, most 
dissatisfied are train users (57% satisfied), walkers (66% 
satisfied), and taxi users (67% satisfied). Only 20% of taxi 
users said they were dissatisfied or very dissatisfied with their 
mode.

2.2.10 main problems with public transport
Public transport users were asked for the main problems they 
experience on a regular basis. Table 2.3 shows the results by 
municipality, and Table 2.4 by mode. Both tables, and those 
that follow below, show the ‘degree of severity’ with a colour 
scale, with low percentages in green and high percentages in 
red. Problems differ somewhat depending on where people 
live. Residents of the metros were more concerned with the 
high cost of transport, rude drivers/passengers and unreliable 
service. In non-metro areas, problems with unroadworthy 
vehicles, reckless driving and rudeness dominate. These 

satisfied neutral dissatisfied

other

other bus

school bus*

Brt/rea vaya bus*

gauteng*

train

taxi

Car passenger, lift club

Car as passenger

Car as driver

motorbike

Bicycle

walk

0 10 20 30 40 50 60 70 80 90 100

percentage

79 13 8

78 5 17

93 7

58 21 21

68 31

57 15 27

67 12 20

82 7 11

88 8 5

92 4 3

86 8 6

85 11 3

66 14 21



Chapter 2 2011 gcro quality of life survey: analysis of transport data

29

trends are consistent with higher use of taxis in non-metro 
areas. Interestingly, most people do not consider crime and 
security on public transport as a major problem.

Table 2.4 further explains some of the key public transport 
issues faced by commuters in Gauteng. Expensive fares are 
considered the most important problem by taxi users. Among 
bus and train users the problem is not cost, but reliability. 
These findings are consistent with the state of operations 
in these industries: bus and train fares are kept low by state 
subsidies, but taxi fares are not. Given that the taxi is the key 
provider of mobility for 42% of workers, 73% of work seekers, 
and 50% of all trips in Gauteng (Figure 2.2), affordability 
of taxis is clearly an issue to address. It is also important to 
ensure that future upgrading of the public transport system – 

Unreliability
Unroadworthy 

vehicles
Crime/

security
Reckless 

driving

Rude drivers 
and/or 

passengers
Lack of 

comfort Expensive

Insufficient 
service at 

night

Insufficient 
service on 
weekend

Long walk to 
nearest stop/

station
Long wait at 
stop/station

METRO

ekurhuleni 13% 14% 3% 12% 11% 6% 15% 1% 1% 3% 4%

Johannesburg 13% 11% 3% 12% 14% 9% 14% 2% 1% 2% 4%

tshwane 16% 9% 3% 14% 12% 9% 16% 2% 1% 3% 4%

                       

NON-
METRO

emfuleni 12% 14% 3% 15% 15% 9% 13% 2% 0% 1% 5%

lesedi 10% 5% 3% 18% 12% 14% 14% 3% 1% 2% 8%

merafong 13% 22% 3% 9% 6% 7% 12% 3% 0% 5% 7%

midvaal 9% 13% 0% 11% 4% 4% 12% 3% 3% 5% 21%

mogale 11% 11% 3% 11% 12% 8% 9% 4% 2% 4% 10%

randfontein 12% 14% 3% 12% 9% 9% 9% 3% 1% 3% 9%

westonaria 13% 11% 3% 13% 13% 7% 10% 6% 1% 3% 8%

for instance by replacing taxi routes with higher-capacity bus 
or Bus Rapid Transit (BRT) services – does not result in fare 
hikes for passengers (including those who remain taxi users), 
many of whom are vulnerable.

Affordability is also a key concern among people walking, 
suggesting that many non-motorised transport users do so 
not by choice, but because they cannot afford to travel by 
any other means.

In order to establish the problems that non-users might have, 
non-public transport users were asked to indicate their main 
reason for not using public transport. The data are summarised 
in Table 2.5, grouped by income level, and clustered into 
similar types of problems. The reasons for not using public 

transport are different for different groups. Among the lowest 
income group, cost is the most significant barrier for 27% of 
respondents. Not having access to public transport nearby 
is also a significant problem among low-income groups. 
From about R6 400 upwards, having access to a car (and 
its amenities, including flexibility and reliability) is the most 
common reason given for not using public transport. Concern 
with crime and security is a minor reason, except among the 
highest income category where 17% of non-public transport 
users identified crime as their primary concern. Thus, negative 
perceptions around the crime and security risk on public 
transport appear to be more of a problem among non-public 
transport users than among users.

table 2.3: Biggest problem with public transport reported by users, by municipality



Mobility in the GautenG city-ReGion

30

 
Unreliability

Unroadworthy 
vehicles

Crime/
security

Reckless 
driving

Rude drivers 
and/or 

passengers
Lack of 

comfort Expensive
Insufficient 

service at night

Insufficient 
service on 
weekend

Long walk to 
nearest stop/

station
Long wait at 
stop/station

walk 11% 15% 2% 11% 8% 8% 16% 1% 1% 3% 4%

Car 17% 12% 4% 14% 12% 9% 8% 2% 1% 2% 5%

taxi 10% 13% 3% 13% 13% 8% 17% 2% 1% 2% 5%

train 18% 9% 6% 8% 8% 11% 11% 4% 1% 3% 8%

Bus 20% 9% 3% 11% 10% 7% 12% 2% 2% 3% 4%

other 15% 16% 8% 10% 6% 10% 6% 2% 2% 3% 6%

table 2.4: Biggest problem with public transport reported by users, by mode of transport they used for the longest part of their most frequent trip 

 

Public transport access 
problems

Public 
transport 

cost
Public transport 
safety problems

Non-
motorised 
transport 

(NMT) user

Public 
transport 
non-user Car preference/utility Other

m
o

n
th

ly
 h

o
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se
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ld

 
in

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o 

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ea

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 t

ak
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 t
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 t
o 

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 s
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ti

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Th
e 

w
ai

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tr

an
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t 

is
 t

oo
 lo

ng

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an

’t 
aff

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 p
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or

ry
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cr

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ty

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or

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 a

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ou

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ro

ad
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ai
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ac
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en

ts

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al

k/
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on

’t 
w

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to
 u

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p
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 t

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ns

p
or

t

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an

 a
ff

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d

 a
 c

ar

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et

 t
o 

w
or

k/
sc

ho
ol

 o
n 

ti
m

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w

it
h 

m
y 

ca
r

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an

 t
ak

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un

p
la

nn
ed

 
tr

ip
s

I d
ro

p
 o

ff
 fr

ie
nd

s/
fa

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ily

 
on

 m
y 

w
ay

 –
 b

et
te

r 
th

an
 

ev
er

yo
ne

 u
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ng
 p

ub
lic

 
tr

an
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or
t

I a
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 a
 m

em
b

er
 o

f a
 li

ft
 

cl
ub

/p
as

se
ng

er

O
th

er

zero to 
r400 14% 4% 7% 27% 5% 2% 6% 14% 5% 1% 2% 0% 2% 11%

r401- 
r3 200 15% 12% 6% 10% 4% 3% 6% 13% 8% 2% 5% 1% 1% 16%

r3 200-
r12 800 14% 7% 3% 4% 5% 3% 2% 16% 18% 9% 10% 1% 0% 7%

r12 801-
r102 400 8% 4% 3% 1% 5% 2% 1% 20% 28% 14% 12% 1% 0% 2%

r102 400 
+ 4% 8% 2% 0% 17% 3% 0% 10% 18% 4% 19% 4% 0% 10%

response 
not given 8% 6% 5% 2% 6% 1% 3% 23% 12% 6% 11% 1% 0% 15%

all 10% 6% 5% 5% 6% 2% 3% 19% 15% 7% 10% 1% 1% 11%

table 2.5: reasons for not using public transport, grouped by type of problem and income



Chapter 2 2011 gcro quality of life survey: analysis of transport data

31

Figure 2.16 shows the desire line plots for Gauteng. On the 
basis of this we can observe the following:

• In terms of transport demand, Gauteng functions to 
some extent as a city-region, with connectivity between 
all parts of the province. In terms of the major linkages, 
two clusters stand out: Tshwane, and Johannesburg/
Ekurhuleni. Table 2.6 below shows the percentage of 
most frequent trips between municipalities. About 3% of 
Johannesburg residents make their most frequent trip to 
Tshwane, and 8% to Ekurhuleni. From Tshwane, about 6% 
go to Johannesburg. Almost 20% of trips from Ekurhuleni 

go to Johannesburg.

• Johannesburg clearly remains the heart of the province 
in terms of providing access to jobs and services to 
people across a large part of Gauteng. Johannesburg is 
a very strong attractor not only to residents from nearby 
Soweto and (the not so nearby) Orange Farm, but also 
areas across Ekurhuleni. In fact, in terms of movement 
linkages Ekurhuleni is virtually indistinguishable from 
Johannesburg. This is a strong indicator that integrated 
planning of mobility networks and land use development 
is needed between Gauteng municipalities in general, and 

especially between Johannesburg and Ekurhuleni.

• Within-municipality linkages are far stronger than those 
between cities. For instance, the desire lines between 
Tshwane and Johannesburg are weak compared to shorter 
distance desire lines. In Johannesburg 84% of most frequent 
trips stay within the city; in Ekurhuleni this percentage 
is 75%, and in Tshwane 90% (Table 2.6). Among district 
municipalities, travel to other areas is more common 
– Emfuleni, Midvaal, Randfontein, and Mogale City are 
closely integrated with Johannesburg, while there are also 
strong movements between Westonaria and Randfontein 
local municipalities. This finding is associated with the type 
of trips mapped here – not simply work trips (which would 
tend to show stronger long-distance linkages), but all trip 
purposes. Clearly local mobility is important and not just 
peak-period work travel that tends to happen over longer 
distances.

• Figure 2.16 further suggests that strong linkages also 
exist between ‘townships’ and their proximate urban 
centres (e.g. between Soshanguve/Mabopane and the 
Pretoria Central Business District (CBD); Soweto and 
the Johannesburg CBD; Ekangala and Bronkhorstspruit; 
Katlehong/Vosloorus and Germiston; and Orange Farm 
and Vereeniging). This suggests that the historic social and 
economic linkages between townships and their nearest 
urban centre are still strong.

2.3 Mapping of movement patterns
This section maps the key movements in Gauteng at a 
provincial level to provide a visual representation of functional 
linkages between different parts of the city-region. It is based 
on the most frequent trip identified by each respondent, 
weighted for socio-demographic variables to reflect the 
population at provincial and local municipality level. 

As in section 2.2, however, trip frequency is not reflected, 
so the number of trips in the graphs does not necessarily 
correspond to daily or hourly flows. The figures rather reflect 
the strength of connectivity between origins and destinations 
– both for economic and social purposes – taking all trip 
purposes into account, and from the point of view of the user 
rather than transport conditions on the transport network. It 
therefore has a different interpretation from the typical peak 
period volume plot on the network that is more reflective of 
economic-only linkages (being mainly composed of work 
trips). 

Origins and destinations were aggregated from the suburb-
level up to larger geographic units to improve clarity. As 
the 2011 QoL Survey did not survey households outside of 
Gauteng, the maps are restricted to origins and destinations 
within the provincial boundaries. The maps are plotted 
against a spatial layer (termed “urban classification”) that will 
be described in the next section.



Mobility in the GautenG city-ReGion

32

metropolitan higher order roads play, to a large extent, 
different roles in terms of the modes and users served. The 
national network seems to be more important for car travel, 
while provincial/metropolitan higher order roads play an 
important role in linking communities who use public-
transport to access opportunities. These roads include 
the R80 (connecting Soshanguve to Pretoria); several 
roads connecting the Mamelodi and Atteridgeville areas 
respectively to the Pretoria CBD; the R511 (connecting 
Diepsloot to Johannesburg); the various roads connecting 
Soweto with the Johannesburg CBD; and the R553 
stretching between Vereeniging and Johannesburg.  

Destination of most frequent trip

Johannesburg tshwane ekurhuleni emfuleni lesedi merafong midvaal mogale City randfontein westonaria outside 
gauteng

h
o

m
e

 m
u

n
iC

ip
a

l
it

y

Johannesburg 84.3% 2.9% 8.1% 1.8% 0.0% 0.1% 0.0% 1.7% 0.3% 0.1% 0.7%

tshwane 6.2% 90.0% 2.0% 0.5% 0.0% 0.1% 0.0% 0.1% 0.2% 0.1% 0.9%

ekurhuleni 19.9% 3.0% 75.2% 0.8% 0.2% 0.0% 0.3% 0.1% 0.1% 0.1% 0.4%

emfuleni 10.3% 1.2% 2.7% 82.8% 0.1% 0.0% 2.1% 0.1% 0.2% 0.1% 0.4%

lesedi 4.2% 1.2% 17.8% 1.8% 73.8% 0.3% 0.0% 0.3% 0.3% 0.0% 0.3%

merafong 5.6% 2.9% 0.3% 1.3% 0.0% 86.6% 0.0% 0.5% 1.9% 0.2% 0.8%

midvaal 8.1% 0.2% 10.2% 27.9% 1.9% 0.7% 49.8% 0.4% 0.5% 0.4% 0.0%

mogale City 27.9% 2.3% 2.3% 1.2% 0.0% 0.3% 0.0% 57.5% 7.5% 0.7% 0.3%

randfontein 18.8% 1.3% 1.9% 0.7% 0.0% 0.9% 0.5% 8.0% 61.9% 5.6% 0.2%

westonaria 6.5% 1.2% 1.4% 1.1% 0.2% 4.3% 0.0% 4.3% 15.1% 65.1% 0.7%

table 2.6: percentage of most frequent trips between origin and destination municipalities

Figure 2.17 - Figure 2.20 depict the most frequent trips 
allocated to the major road network (rather than as a desire 
line plot), to give a sense of the importance of various parts of 
the existing road network. Note, once again, that the thickness 
of lines on the network does not correspond exactly to the 
conventional hourly traffic volume plots that are obtained 
from transport models or traffic counts.

Based on these plots the following observations are made:

• The importance of the national (freeway) road network 
for intra-provincial mobility is clear. However, it appears 
that the national urban freeways and the provincial/

Figure 2.19 and Figure 2.20 (taxi and bus modes 
respectively) indicate that these roads primarily serve a 
public transport connectivity role.

• These patterns suggest that provincial and metropolitan 
roads are key assets to mobility in Gauteng and their 
maintenance and upgrading should be a key priority. 
Taking into account that they indicate desired rather than 
actual routes between origin and destinations, the plots 
might also help inform the alignment of priority routes for 
public transport, for instance BRT trunk or feeder services.



Chapter 2 2011 gcro quality of life survey: analysis of transport data

33

figure 2.16: desire lines of most frequent trips, gauteng figure 2.17: most frequent trips (car and road-based public transport) assigned to major 
road network



Mobility in the GautenG city-ReGion

34

figure 2.18: most frequent trips (car only) assigned to major road network figure 2.19: most frequent trips (minibus taxi only) assigned to major road network



Chapter 2 2011 gcro quality of life survey: analysis of transport data

35

figure 2.20: most frequent trips (bus only) assigned to major road network figure 2.21: distribution of urban settlement types across study area



Mobility in the GautenG city-ReGion

36

2.4 Analysis by settlement type
This section analyses some of the key mobility responses from the survey with reference to a newly created ‘urban settlement 
typology’. We differentiate settlements in Gauteng according to the general locational, housing, and neighbourhood 
characteristics of the area, and examine how the mobility and access realities differ according to the type of settlement a 
household lives in. The typology transcends administrative (e.g. municipal) boundaries, attempting to capture the underlying 
spatial characteristics of an area. The analysis helps to establish how the market dynamics and actions of government that 
produce specific settlement forms affect the day-to-day mobility and access outcomes faced by households in Gauteng.

2.4.1 urban settlement typology
Drawing on recent work on settlement typologies and housing in South Africa9, we divided the GCR into eight settlement types 
at the suburb level. The underlying hypothesis was that the quality of access and mobility enjoyed by a household or individual 
varies systematically with the spatial, historical or socio-economic characteristics of the settlement they live in. As with all 
typologies, we attempted to limit the (large) amount of variation across different settlements (and indeed within them), by 
grouping suburbs together using a small number of key variables thought to reflect these underlying differences. 

The eight settlement types include:

• Urban core: Core areas of traditional CBDs of Gauteng’s cities, with high densities, mixed land uses, and high accessibility 
due to a convergence of public transport and road links in the CBDs. These include the Pretoria and Johannesburg CBDs, as 
well as the old town centres of the East and West Rand and Vereeniging.

• Old suburban: Traditional suburban developments, established before 1995, and characterised by relatively good road 
network coverage, low to medium densities, and typically located just outside the urban core areas. The age of settlement is 
used as a proxy for the well-established and well-serviced nature of the area.

9 The concept of the settlement typology used here, although adapted and customised for the current study, draws heavily on the work done by Catherine Cross and 
colleagues at the Human Sciences Research Council (HSRC) as part of the Department of Science and Technology-funded Integrated Planning, Development and 
Modelling (IPDM) Project jointly undertaken with the Council for Scientific and Industrial Research (CSIR) and the University of Pretoria (UP) between 2009 and 2012. 
For a recent review see Cross et al. (2013).



Chapter 2 2011 gcro quality of life survey: analysis of transport data

37

• New suburban: Suburbs founded after around 1995, 
typically located further away from the CBDs and closer to 
the outer fringe of the urban area. These areas typify more 
commute-oriented, sprawling types of development, and 
include many gated communities as well as low to medium 
density cluster housing areas. These areas might have less 
well-developed road networks and local amenities than 
older suburbs.

• Formal townships: Formal dwellings located within 
traditional black townships or homeland areas of the 
city-region, within proclaimed urban areas, but excluding 
Reconstruction and Development Planning (RDP) housing. 
These areas have varying infrastructure quality, density 
and amenities, but are generally planned settlements.

• Informal inner: Informal housing (including shacks 
and backyard dwellings) located within the traditional 
boundary of the built-up areas of Gauteng. These include 
shacks on unused or public land close to the urban core, or 
within traditional black townships.

• Informal outer: Informal housing located outside of the 
traditional boundary of the built-up areas of Gauteng. This 
includes shacks in new township developments, between 
RDP housing units (or in their backyards) and in newer 
peripheral informal settlements.

• Formal RDP: RDP houses or subsequent subsidised housing 
programmes delivered over the last 18 years. These tend to 
be located on the edges of traditional townships.

• Formal peripheral: Settlements on smallholdings, 
agricultural communities and other low-density parts of 
the city-region.

Readily available Geographic Information Systems (GIS) data 
were used to allocate suburbs to these eight classes, and 
to allocate individual households from the 2011 QoL Survey 
sample within the suburbs (for instance to differentiate 
between households living in formal RDP houses and 
households living in informal housing within those same RDP 
areas). A brief description of the data rules and layers used for 
this allocation is described below:

• Urban core: A selection of older CBDs from the Gauteng 
Spatial Development Framework’s (GSDF’s) major nodes 
data. 

• Old suburban: Extracted from the residential records of the 
1996 CSIR/Satellite Applications Centre (SAC) land cover. 

• New suburban: Extracted from the residential records of 
the 2011 CSIR/SAC land cover that did not appear in the 
1996 layer. These areas were thus developed between 1996 
and 2011.

• Formal townships: based on the 20 Townships Programme 
data layer from the Gauteng Department of Economic 
Development, and areas classified in the 1996 CSIR/SAC 
land cover as townships.

• Formal RDP: All households in the QoL dataset indicating 
their dwelling as a RDP house.

• Informal inner: All households in the QoL dataset indicating 
their dwelling as informal, within the urban core, old and 
new suburbs, and formal township suburbs as defined 
above.

• Informal outer: All households in the QoL dataset indicating 
their dwelling as informal and not included in ‘informal 
inner’.

• Smallholdings: Extracted from the 2009 South African 
National Biodiversity Institute (SANBI) land cover.

• Agricultural hinterland: Remaining extent of the province.

The spatial distribution of the settlement types across 
Gauteng is shown in Figure 2.21, with Table 2.7 indicating the 
number of survey responses allocated to each settlement 
type. Most numerous is ‘formal township’, containing almost 
40% of the sample, followed by ‘old suburban’ areas with 28%. 
Informal dwellings are distributed almost equally between 
inner and outer areas of the province, but also appear in urban 
core settlements. 



Mobility in the GautenG city-ReGion

solomon legodi 



Chapter 2 2011 gcro quality of life survey: analysis of transport data

39

Urban settlement 
type

Dwelling type Total % of  
sampleFormal Informal Other

formal peripheral 333 1 22 356 2%

formal rdp 1 985 17 55 2 057 12%

formal township 5 918 0 206 6 124 37%

informal outer 0 686 0 687 4%

informal inner 0 929 0 929 6%

new suburban 1 290 0 46 1 336 8%

old suburban 4 642 0 104 4 746 28%

urban core 462 26 7 495 3%

total 14 631 1 659 440 16 730 100%

table 2.7: allocation of households in dataset to eight urban settlement types

2.4.2 socio-economic description of urban structure types
To get a sense of the socio-economic differences between the settlement types, Figure 2.22 shows the employment status of 
residents in each, while Table 2.8 shows median incomes. Areas differ significantly in unemployment levels and income levels. 

Suburban areas (old and new) have by far the highest employment and income levels – these are generally the more affluent 
residential areas of the province. As is expected, households in informal dwellings have the lowest income and employment 
levels. Interestingly, informal workers are present in all settlement types, suggesting that seeking employment in the informal 
sector is a livelihood strategy that cuts across socio-economic boundaries. Urban core residents are relatively affluent and well-
employed, indicating that the central cities still manage to concentrate household capital. 



Mobility in the GautenG city-ReGion

40

Urban settlement type Median monthly 
income (Rands)

formal peripheral    r 2 094 

formal rdp    r 1 479 

formal township    r 2 163 

informal outer    r 1 109 

informal inner    r 1 178 

new suburban    r 7 536 

old suburban    r 8 214 

urban core    r 5 142 

table 2.8: median income of households in sample, per 
settlement type

figure 2.22: employment status of respondents by settlement type

formal peripheral

formal rdp

formal township

informal outer

informal inner

new suburban

old suburban

urban core

2931 7 33

0 10 20 30 40 50 60 70 80 90 100

percentage

employed formal employed informal unemployed other

16 5 49 30

24 5 40 31

18 8 58 16

17 9 56 18

41 7 23 29

43 7 16 34

35 8 27 30



Chapter 2 2011 gcro quality of life survey: analysis of transport data

41

Urban settlement type Race

African Asian/Indian Coloured White

formal peripheral 81% 3% 3% 14%

formal rdp 97% 1% 1% 0%

formal township 93% 2% 3% 2%

informal outer 98% 1% 0% 0%

informal inner 97% 1% 1% 1%

new suburban 56% 5% 7% 32%

old suburban 47% 6% 5% 41%

urban core 79% 3% 2% 16%

table 2.9: race distribution of sample, by settlement type

When disaggregated by race, the figures indicate an 
interesting diversity in many settlement types. Suburban 
areas consist almost equally of African and other race groups 
(Table 2.9). This might be due to a combination of factors, 
including increasing integration of older ‘white’ suburbs, 
demographic turnover in others and the development of new 
suburban areas (or outward growth of existing ones) that 
attract medium-income households from across the race 
spectrum. The latter point is supported by the fact that the 
percentage of Africans is higher in newer suburban than in old 
suburban areas. 



Mobility in the GautenG city-ReGion

42

Table 2.10 shows the migration status of the sample. The 
function of the urban core as a reception area for migrants 
from outside the province is clear: only 38% of residents were 
born in Gauteng, and about half moved to Gauteng within the 
last 15 years. Similarly, informal settlements regardless of their 
location on the inner-outer continuum are preferred locations 
for migrants, thus playing a key role in urbanisation within 
Gauteng. Figure 2.23 confirms this, with regards to the time a 
resident has been living in their present dwelling.

In summary, then, it appears that migrants who gain access 
to the city centres tend to have higher-income and lower 
levels of unemployment, while those who are less well-off are 
located in more distant informal settlements. Location close 
to economic opportunities offered by the traditional CBD and 
surrounds is associated with better economic well-being. This 
indicates that traditional role of the CBD as providing access 
to economic opportunity is still strong. However, the causality 
is not clear: more central locations might enable people to 
gain better employment and earn higher incomes; but more 
central locations might also command higher entry prices (in 
terms of housing cost or other social capital-related costs) 
and thus keep lower-income migrants out in the first place.

figure 2.23: time of tenure at present address, per settlement type

formal peripheral

formal rdp

formal township

informal outer

informal inner

new suburban

old suburban

urban core

0 10 20 30 40 50 60 70 80 90 100

percentage

less than 2 years 2-15 years more than 15 years always lived in this dwelling

305 26 39

6 43 16 35

5 20 27 48

8 41 12 39

10 38 18 34

8 46 16 30

8 41 17 34

24 36 11 29



Chapter 2 2011 gcro quality of life survey: analysis of transport data

43

Urban settlement type Born in Gauteng Moved to Gauteng
… more than 15 years ago … within last 15 years

formal peripheral 63% 14% 22%

formal rdp 63% 15% 21%

formal township 72% 13% 15%

informal outer 39% 18% 42%

informal inner 38% 19% 42%

new suburban 57% 16% 27%

old suburban 61% 14% 25%

urban core 38% 10% 52%

table 2.10: migration status of sample, by settlement type

Suburban settlements have a higher than expected amount of 
residents from outside Gauteng (about 40%); approximately 
half of residents moved into their houses within the last 15 years. 
This suggests that Gauteng’s suburbs have experienced their 
fair share of turnover. The formal township areas have been 
the most stable – a full three-quarters of township dwellers 
have lived there all their lives or for more than 15 years. This 
might be an indication of stable long-term communities, or of 
less than optimal housing markets that limit opportunities for 
housing ownership turnover.



Mobility in the GautenG city-ReGion

44

Finally, there appears to be a marked difference in the general life satisfaction experienced by residents depending on the type 
of settlement they live in (Table 2.11). Satisfaction is highest in old suburban areas (76% satisfied), followed by new suburban 
(72%) and urban core areas (70%). Lowest satisfaction occurs in informal areas, especially in more distant (outer) informal 
neighbourhoods. Once people get access to RDP housing their satisfaction jumps markedly (from around 40% satisfied to 
around 60%, with 26% dissatisfied), but not as high as people living in other formal townships (23% dissatisfied). Lastly, people 
living in peripheral or more rural parts of the province seem to consist of two groups: those with average to high satisfaction 
(60% are satisfied with life, on a par with the provincial average), and those with low satisfaction (29% are dissatisfied, more 
than the provincial average of 21%).

 Urban settlement type Life satisfaction

Satisfied Neutral Dissatisfied

formal peripheral 60% 12% 29%

formal rdp 59% 15% 26%

formal township 61% 16% 23%

informal outer 41% 13% 46%

informal inner 42% 18% 40%

new suburban 72% 14% 14%

old suburban 76% 13% 11%

urban core 70% 16% 14%

total 64% 15% 21%

table 2.11: satisfaction with life as a whole, by settlement type

Kyle Brand



Chapter 2 2011 gcro quality of life survey: analysis of transport data

45

2.4.3 transport patterns by urban settlement type
This section examines relationships between the settlement types and the mobility-related responses in the survey.

On average, about 23% of respondents reported not making any trips in response to the survey request to identify their most 
frequent trip. This is a proxy figure for immobility, i.e. an inability or lack of desire to travel. Even though experience indicates 
that this figure cannot necessarily be interpreted as the absolute number of people who are ‘stranded’ owing to an absence of 
affordable transport options, it gives an indication of the relative levels of travel activity participation across settlement types, 
which is broadly correlated to welfare.

Table 2.12 shows that immobility (as defined above) varies significantly across settlement types, and is clearly related to distance 
from the core areas of the province. Immobility in the CBD areas is only 14%, rising as settlements are further removed from the 
CBD, until it reaches 30% in peripheral areas. Clearly centrality of location correlates with higher transport options (including 
more public transport options converging on central cities), which in turn promotes more trip making.

 Urban settlement type “I never make any trips” (% of respondents per settlement type)

formal peripheral 30%

formal rdp 28%

formal township 26%

informal outer 25%

informal inner 26%

new suburban 17%

old suburban 19%

urban core 14%

table 2.12: extent of immobility in sample, by urban settlement type



Mobility in the GautenG city-ReGion

46

Figure 2.24 shows that mode use varies across these 
settlement types. As one would expect given the differences 
in incomes, car use is highest in old and new suburbs (between 
57% and 63% of trips), but also significant in urban core areas 
(25% of trips) and peripheral areas (30%). Walking as a main 
mode is important in urban core areas – again illustrating the 
benefit of central location in terms of being able to avoid 
more costly transport options – and also in inner informal 
areas. Here inner informal areas differ from outer areas. Outer 
informal areas are not within walking distance of destinations, 
and here only 5% of most frequent trips are on foot, which 
is remarkable given that this includes not only work but also 
daily shopping and other trips. Taxis play a larger role in 
outer than in inner areas. Clearly outer informal areas have a 
quadruple disadvantage: they are located further away from 
work opportunities; they have a shortage of other amenities 
nearby; an absence of bus and rail routes force higher reliance 
on taxis (which tend to be more expensive); and these fares 
consume a higher proportion of residents’ incomes, which are 
lower than elsewhere.

figure 2.24: main mode used for most frequent trip, by settlement type

formal peripheral

formal rdp

formal township

informal outer

informal inner

new suburban

old suburban

urban core

10 30 54

0 10 20 30 40 50 60 70 80 90 100

percentage

3

7 8 73 7

8 17 65 6

5 5 78 7

15 4 65 11

8 57 27 4

6 63 24 2

18 25 50 3

walk Car taxi Bus train other



Chapter 2 2011 gcro quality of life survey: analysis of transport data

47

It appears that some inner informal settlements are well 
located, such that users can walk to destinations (which could 
be in nearby formal settlements), or use inexpensive trains. 
Train use is highest in inner informal areas. 

Do people in different settlement types face longer travel 
distances and times? Table 2.13 tabulates the travel times 
reported by respondents for their most frequent trips. It 
shows, remarkably, that no great variation exists between the 
eight settlement types – average travel times vary between 
41.9 minutes in old suburban neighbourhoods and 47.5 
minutes in adjacent urban core areas. The percentage of trips 
taking longer than one hour is highest in township (15%), RDP 
(15%), and peripheral areas (16%).

Questions exist about the accuracy of the self-reported travel 
time data (see section 2.2.5 above). If the data is correct, it 
could indicate that residents of suburban locations are most 
‘time-advantaged’, and that travel times generally increase 
with distance from the CBD. Two exceptions to the pattern 
are urban core locations, which have longer travel times 
(likely due to the higher incidence of people walking), and 
outer informal areas (which have shorter than expected travel 
times, for unknown reasons). 

Urban settlement type Mean travel time of most 
frequent trip (mins)

% of trips <20mins % of trips >60mins

formal peripheral 46.9 22% 16%

formal rdp 46.5 28% 15%

formal township 46.3 27% 15%

informal outer 42.4 25% 11%

informal inner 46.2 26% 14%

new suburban 42.7 30% 12%

old suburban 41.9 32% 12%

urban core 47.5 31% 13%

table 2.13: travel time of frequent trip, by settlement type

The next two tables help to shed further light. Table 2.14 tabulates average estimated trip distances for the most frequent trip10. 
It shows that, across all trip purposes, trip distances increase as settlements are located further away from the CBD. This is 
consistent with classical land use-transport theory which assumes that all trips are centred on the CBD. While all destinations 
are clearly not in the CBD any longer, it does suggest that the CBD and its surrounds still play a very important role as the 
location of many urban activities. 

10 As trip distances were not reported in the survey, we estimated trip distances from the shortest-distance route by road between the origin and destination of each trip, according to the suburb reported for each. This measure is more likely to be accurate 
than travel times, as origins and destinations were generally accurately reported. Estimated distances and reported travel times were then used to estimate travel speeds.



Mobility in the GautenG city-ReGion

48

In terms of travel distances required to access daily activities 
and work, being located in or near the traditional core of our 
cities confers a large benefit. Average trip distances (for all 
trip purposes) are more than three times longer for people 
living in the peripheral areas of the province than those in the 
centre. Of particular concern is distances travelled by people 
to look for work. Residents of peripheral/semi-rural and of 
RDP settlements are worst off in this regard, travelling more 
than 25km on average to look for work – a significant cost and 
time investment.

If average travel times are very similar but travel distances 
differ markedly, it means that average speeds must also differ 
across the urban space. This is indeed confirmed by Table 
2.15 showing the average travel speed estimated for all most 
frequent trips made by residents in each settlement type. 
Estimated speeds are lowest in the urban core, increasing with 
distance from the CBD. These speeds are calculated across 
all modes, including walking, public transport and car modes. 
Trips from the CBD are on average only 17km/h, due to the 
high incidence of walking. In old and new suburbs average 
speeds range between a slow 28.7km/h and 33.5km/h, 
reflecting the many short-distance trips made on low-order 
streets and also probably high levels of congestion on higher-
order roads. 

Urban settlement type Mean travel distance (estimated), km

Work Look for work Shopping All trips

formal peripheral 25.50 28.19 32.25 28.46

formal rdp 21.68 25.55 17.48 21.38

formal township 23.62 24.70 16.80 21.54

informal outer 20.25 22.72 17.38 19.95

informal inner 19.58 19.97 11.85 17.94

new suburban 19.36 16.22 13.00 17.39

old suburban 15.66 15.93 10.74 14.91

urban core 10.53 8.47 9.55 9.15

table 2.14: mean travel distance for most frequent trip, by settlement type

nKululeKo nKosi



Chapter 2 2011 gcro quality of life survey: analysis of transport data

49

Urban settlement 
type

Mean travel speed, all 
modes (estimated), km/h

formal peripheral 49.9

formal rdp 36.9

formal township 37.6

informal outer 37.5

informal inner 31.1

new suburban 33.5

old suburban 28.7

urban core 17.3

table 2.15: mean travel speed of most frequent trips across all 
modes, by settlement type

Main mode used Mean travel speed 
(estimated), km/h

walk 10.4

Bicycle 28.5

motorbike 29.2

Car as driver 34.6

Car as passenger 33.3

Car as passenger through a 
lift club 27.2

taxi 36.2

train 40.8

gautrain 53.3

Brt/rea vaya bus 41.9

school bus 30.3

other bus 34.5

other type 34.4

table 2.16: average door-to-door travel speed (estimated), by 
main mode used

Urban settlement type Mean monthly 
household transport 

cost
formal peripheral   r313

formal rdp   r192 

formal township r294

informal outer  r150

informal inner  r153 

new suburban  r549 

old suburban  r564 

urban core  r429 

table 2.17: mean monthly household expenditure on transport, 
by settlement type

Average speeds vary largely predictably between individual 
modes (Table 2.16). Frequent trips, of which the greatest part 
of the journey is done on foot, have an average speed of 
10.4km/h (greater than walking speed as faster modes may 
be used on other segments of the trip). At the other end of 
the scale, public transport modes specifically designed for 
speed improvements seem to deliver: note the relatively high 
door-to-door speeds of the Gautrain (53.3km/h) and BRT 
(41.9km/h).

The average estimated speed for car trips varies between 
27.2km/h and 34.6km/h, lower than for taxi trips (36.2km/h) 
and rapid bus trips (41.9km/h). This result seems 
counterintuitive, but might give an indication of the extent to 
which congestion has eroded the speed advantage of the car 
over other modes in Gauteng. However, given the accuracy 
problems with reported travel times in the data, further work 
would be needed to confirm this finding. 

Table 2.17 summarises the average monthly expenditure on 
transport, by settlement type. Transport costs are heavily 
influenced by the types of modes used. Suburban households 
spend by far the most on transport (more than R500 per 
month), closely followed by urban core households (about 
R430). Evidently the shorter distances travelled by residents 
of these areas do not translate into low transport costs, as 
most trips are made by the relatively expensive car mode. 
Households in informal settlements spend about R150 per 
month on transport, in both inner and outer locations. The 
amounts are slightly higher in RDP settlements (R192) and 
almost double in formal townships (R294). 



Mobility in the GautenG city-ReGion

50

 Urban settlement type Satisfaction with transport
Satisfied Neutral Dissatisfied

formal peripheral 75% 5% 21%

formal rdp 67% 13% 20%

formal township 70% 12% 18%

informal outer 70% 9% 20%

informal inner 58% 14% 28%

new suburban 81% 9% 9%

old suburban 85% 7% 9%

urban core 81% 11% 8%

table 2.18: satisfaction with transport, by settlement type

Are residents of these different types of settlements satisfied 
with transport? Table 2.18 shows the result to this question 
in the survey. Following the same patterns as with general 
‘life satisfaction’ (see Table 2.11), residents are most satisfied 
in suburban and central core locations, with as much as 85% 
of people responding positively. Dissatisfaction is highest 
in informal settlements, and more so in inner than in outer 
areas. In peripheral areas there is once again evidence of two 
groups, those who are very satisfied and those who are very 
dissatisfied with transport conditions.

Looking at differences in the types of problems experienced 
by public transport users in the different areas (Table 2.19), 
it is clear that affordability is the most common problem 
in all areas with heavy public transport use. This includes 
township, informal and especially peripheral areas, where 
long travel distances help to raise travel costs. Reckless and 
rude drivers are considered more of a problem in urban core 
areas, perhaps corresponding to more aggressive driving 
styles under crowded CBD traffic conditions. Residents in 
suburban locations complain more about the unreliability and 
discomfort of public transport services, suggesting that the 
market for public transport in these areas has different service 
quality concerns than elsewhere.



Chapter 2 2011 gcro quality of life survey: analysis of transport data

51

  Single biggest problem with public transport

Urban structure 
type Unreliability

Unroadworthy 
vehicles Crime/security

Reckless 
driving

Rude drivers 
and/or 

passengers
Lack of 

comfort Expense

Insufficient 
service at 

night

Insufficient 
service on 

weekend

Long walk to 
nearest stop/ 

station
Long wait at 
stop/station Other

formal peripheral 16% 9% 2% 13% 6% 6% 22% 2% 2% 4% 13% 7%

formal rdp 12% 14% 2% 11% 13% 7% 16% 1% 1% 3% 4% 16%

formal township 13% 12% 3% 13% 14% 9% 14% 2% 1% 2% 4% 15%

informal