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THE TRAFFIC IMPACTS OF ROAD CAPACITY CHANGE: A REVIEW OF RECENT EVIDENCE AND POLICY DEBATES

THE TRAFFIC IMPACTS OF ROAD CAPACITY CHANGE: A REVIEW OF

RECENT EVIDENCE AND POLICY DEBATES
LISA KANE and ROGER BEHRENS
Urban Transport Research Group,
Faculty of Engineering and the Built Environment

University of Cape Town,
Private Bag, Rondebosch, 7701

Tel: 021 6502584
Fax: 021 6897471
E-mail: lisakane@iafrica.com

SYNOPSIS
The NDoT’s Action Agenda of 1999 argues that “building more roads in already well served
metropolitan areas is not the solution to traffic congestion”, and that “experience
internationally has shown that more roads attract more traffic – which in turn generates
demand for even more roads”.

This paper reviews the unsourced international experience referred to. This includes, in
particular, two seminal studies undertaken in the UK. The first study (SACTRA 1994)
compiled empirical evidence on ‘induced’ traffic as a result of increased road capacity, and it
concluded that this was indeed a real phenomenon. The second study (1998) investigated the
empirical evidence of the link between increased urban traffic and reductions in road capacity
in order to establish whether the converse of the SACTRA findings were also true, and it was
concluded that a decrease in road capacity could lead to ‘suppressed’ traffic overall.

Collectively it was found that the link between traffic and road capacity is far more complex
than previously understood, that the addition of new capacity can lead to limited short-term

relief in congestion, and that a reduction in capacity may in fact be part of the answer to
solving congestion problems.

The paper then discusses the implications that these findings have for urban transport planning
practice and policy formulation. The induced traffic phenomenon has the greatest
implications in appraising capacity improvement schemes – leading to significant
overestimation of economic benefits. The international experience endorses the policy
direction expressed in Moving South Africa, and this should receive greater attention in new
policy documentation.

SAMEVATTING
Die 1999 aksie-agenda van die NDoT voer aan dat die bou van meer paaie in welbedeelde
stedelike gebiede nie die oplossing van verkeersopeenhoping is nie, en dat internasionale
ondervinding wys dat meer paaie meer verkeer teweegbring – wat dan nog meer paaie vereis.

Hierdie verhandeling kyk na die bewerings en behels twee basiese studies in die VK. Die
eerste studie (SACTRA 1994) handel oor die skepping van “ekstra” verkeer a.g.v.
vermeerderde verkeerskapasiteit, en het bevind dat dit wel bestaan. Die tweede studie (1998)
ondersoek die verband tussen vermeerderde stedelike verkeer en verminderde
verkeerskapasiteit om te toets of die omgekeerde van die SACTRA-bevindings ook waar is,
en daar is bevestig dat verminderde kapasiteit wel verkeer in algeheel verminder.

Tesame skyn dit of die verband tussen verkeer en kapasiteit heel ingewikkeld is, dat
padverbeterings net tydelike verligting gee, en dat vermindering van die verkeerskapasiteit
moontlik deel van die oplossing is.

Die referaat bespreek daarna die gevolge hiervan op stedelike verkeersplanning en beleid. By
die beoordeling van padverbeteringskemas veroorsaak hierdie “ekstra” verkeer ‘n beduidende
oorskatting van ekonomiese voordele. Vir beleidsformulering word die voorstel in Moving
South Africa gesteun en dit word hopelik aangespreek in toekomstige dokumentasie

THE TRAFFIC IMPACTS OF ROAD CAPACITY CHANGE: A REVIEW OF

RECENT EVIDENCE AND POLICY DEBATES

LISA KANE and ROGER BEHRENS
Urban Transport Research Group,
Faculty of Engineering and the Built Environment

University of Cape Town,
Private Bag, Rondebosch, 7701

1. INTRODUCTION
The National Department of Transport’s Action Agenda of 1999 states that:

“With traffic congestion in certain areas set to increase dramatically over the [next] 20-year[s] … building more roads in already well served metropolitan areas is not the solution to
congestion. Experience internationally has shown that more roads attract more traffic which
in turn generates demand for even more roads. Instead, this strategy advocates managing car
use in these congested areas, pricing mechanisms and incentives whilst at the same time
investing behind the core public transport network as the emerging alternative”.
(DOT 1999:27)

This paper identifies and reviews the unsourced international experience referred to in this
statement. The literature documenting this experience deals, in essence, with two phenomena
associated with road capacity change — ‘induced’ and ‘suppressed’ traffic. The paper begins
by defining and explaining the behavioural responses that give rise to these phenomena
(sections 2 and 3). It then reviews the empirical evidence supporting their existence
(section 4). The paper concludes with a brief discussion on the implications this evidence has

for transport planning practice and policy formulation generally, and for the South African
urban transportation context more specifically (section 5).

2. DEFINITION
The watershed publication in the debate over induced traffic was, without doubt, a report
submitted to the United Kingdom’s Secretary of State for Transport in 1994, by his Standing
Advisory Committee for Trunk Road Assessment (SACTRA). The SACTRA committee was
chaired by Derek Wood, and its report was entitled Trunk roads and the generation of traffic.
Although primarily focused on trunk roads (that is, roads in the national road system,
managed by national government) the location of many of these routes through, or close to,
conurbations meant that roads with a wide variety of traffic conditions were considered, from
very congested, to virtually free-flowing. The SACTRA committee was asked to advise “on
the evidence of the circumstances, nature and magnitude of traffic redistribution, mode choice
and generation (resulting from new road schemes)” (SACTRA 1994:1). At the outset the
committee recognised that the notion of ‘roads generating traffic’ was one which had gained
widespread popular acceptance, but which had not been subjected to much rigorous
investigation. There had been confusion and inconsistency over terminology in the literature,
one reason being that the definitions of ‘generated’ traffic are not straightforward. Until the
publication of the SACTRA report, problems in defining induced traffic had blurred real
debate over the actuality of the phenomenon. There was a lack of professional consensus over
what induced traffic was, and if it existed to any significant extent. The committee thus chose
to address this issue of definition in detail (see Hill 1996), and this section of the paper
summarises the final definition they chose to use. Others have suggested slight variants on this

in the intervening years (e.g. Heanue 1998, Litman 1999) but for the purposes of this paper we
stay with SACTRA’s definition.

As a first step in their work, SACTRA decided that the word ‘generate’ was problematic to
use since ‘trip generation’ has a very specific meaning in a transport planner’s vocabulary.

Usually a household or individual is understood to generate trips, as the first stage in the four-
stage modelling process. With this very particular definition in mind, the notion that ‘roads

generate traffic’ (and implicitly, then, trips), seems nonsensical. To preclude any confusion
over this particular issue, the SACTRA committee chose to replace the term ‘generate’ with
‘induce’, and to investigate whether the provision of roads induce — that is, indirectly bring
about — traffic. In summary, the definition adopted by SACTRA was that induced traffic is the
additional daily private vehicle traffic which may occur on a network following some road
capacity increase. It does not therefore include additional traffic found on individual links if
the total network vehicle kilometres remains constant, nor does it include additional traffic
found in the peak period if the total daily vehicle kilometres remains constant.

The literature on the relationship between traffic levels and road capacity was broadened
considerably by the more recent publication of a report entitled Traffic impact of highway
capacity reductions: Assessment of the evidence (Cairns et al 1998). This report was
commissioned by London Transport and the Department of Environment Transport and the
Regions, and prepared by Sally Cairns, Carmen Hass-Klau and Phil Goodwin. The premise of
the study was that if we accept the notion of induced traffic, we must also consider the
possibility of traffic being suppressed when we impose road capacity reductions. The report
therefore reviewed evidence of the traffic impacts of capacity reductions (for example as in
the case of a bridge or lane closure), rather than increases. It is important to note that in this

report, as well as in the earlier SACTRA report, the capacity increases or reductions in
question referred specifically to road capacity change for private vehicles. The impacts of
increased or reduced capacity for public transport were therefore not investigated in any
significant way in this literature.

This paper reviews the literature on the explanations for, and empirical evidence of, ‘induced’
and ‘suppressed’ traffic conjointly. The earlier SACTRA definition is thus expanded to
include both phenomena as follows: Induced (or suppressed) traffic is the additional (or
reduced) daily private vehicle traffic which occurs on a network following some capacity
increase (or reduction), or, as discussed in the following section, some other reduction (or
increase) in the generalised cost of travel.

3. EXPLANATION
It is widely held in the literature on travel behaviour that motorists are most likely to adapt
their behaviour when faced with significant changes to the cost of, or constraints upon, their
travel choices. The phenomena of induced and suppressed traffic have thus been observed to
occur in situations where a change in road capacity causes a significant change in the
generalised cost or attractiveness of motor car travel. In the case of capacity increases, such
cost changes would typically only occur in situations where road space is added to networks
already experiencing congestion, or in the case of major new links leading to a dramatic
change in generalsied cost, for example a river crossing. In the case of capacity reductions,
such cost changes would typically occur in situations where road space is taken away from
networks that have little or no existing spare capacity. (Cairns et al 1998, DeCorla-Souza and
Cohen 1999, Goodwin 1996)

What then happens when capacity is changed on a network with either congestion, or no spare
capacity, and thus how can the phenomena of induced and suppressed traffic be explained?
The literature offering such behavioural explanations identifies a variety of possible travel
adaptations, which tend to be noticeably different in the immediate, short and long term
(Cairns et al 1998, DeCorla-Souza and Cohen 1999, Dowling and Colman 1998,
Goodwin 1996, Kitamura 1994, Litman 1999, Noland 1999, SACTRA 1994). In many, but
not all, respects behavioural responses to increased capacity mirror, in inverse form, responses
to reduced capacity. These temporally differentiated responses are discussed below and
summarised in Tables 1a and 1b.

In the immediate term (i.e. the first few days) drivers often simply change their driving styles
in ways that adjust to the new traffic conditions. In the case of capacity reductions in
particular, and often depending on the amount of forewarning received by media predictions
of ‘traffic chaos’, they have been observed to drive slower and closer together.

In the shorter term (i.e. the first couple of months) behavioural responses tend to take the form
of re-routed trips or rescheduled departure times. In the case of capacity increases, trips are
attracted from other previously quicker, but now slower, routes within the network, or trips
are rescheduled to a preferred departure time (sometimes referred to as the ‘return-to-peak’
effect) in response to the initial relief in congestion. In the case of capacity reductions, trips
are re-routed to neighbouring streets, or trips are rescheduled (i.e. departing a little earlier or a
little later) to avoid the worsening congestion. It should be noted that changes in departure
time or route, while clearly increasing or reducing the amount of traffic on the particular
link(s) subject to capacity change at a particular time, do not necessarily lead to induced or
suppressed traffic as defined earlier. They may simply cause traffic to either divert from, or

reappear on, other equidistant links within the network or at other times on the same link(s).
The total amount of traffic on the network as a whole over the whole day would thus remain
relatively constant before and after the capacity change. It is only if the re-routed trips involve
significantly shorter or longer trip distances that induced or suppressed traffic occurs.
Rescheduled departure times on the other hand would not strictly induce or suppress traffic,
even though Robert Noland (1999) does observe that the ‘return-to-peak’ effect may induce
new trips by freeing up capacity at other times of the day, and theoretically at least, the inverse
would be true for shifts to the off-peak.

In the longer term (i.e. up to five to ten years after the capacity change) behavioural responses
tend to take the form of changed mode, trip frequency or trip end. In the case of capacity
increases, the reduced generalised cost of travelling by car may lead to people taking trips by
car that were previously undertaken by other modes, more frequent trips, or because of
improved travel speeds, trips to preferred destinations further away. In the case of capacity
reductions, the failure of shorter term behavioural adjustments to avoid unacceptable
congestion delays may lead to people using non-motorised or public transport modes instead
of their cars, suppressing non-essential trips or at least linking previously separate trips into
chains, or selecting nearer destinations. In some instances the change in travelling conditions
may ‘tip the balance’ in decisions that were being made for other household life-cycle reasons
anyway, like buying or selling a car, moving house or moving job. All these behavioural
responses potentially contribute to induced or suppressed traffic effects. In addition to these
behavioural responses, increased road capacity (and accessibility) can stimulate unforeseen
changes in land use patterns which can generate further unexpected traffic (Headicar 1996).

Table 1a. Behavioural responses leading to induced traffic
Changes in…. Induce person trips/day? Induce vehicle kms/day?
…route No Yes
…timing No No

…and in the longer term…

…mode (to private car) No Yes
…vehicle occupancy (decreasing) No Yes
…trip frequency (increasing) Yes Yes
…trip destination (becoming more
remote)

(Yes) (1) Yes
…trip origin (becoming more remote) (No) (2) Yes
Notes:
1. In the longer term, land-use changes as a result of capacity increases may result in new destinations on offer,
and hence new trips.
2. The source of trip origins is the household, and whilst the location of the household may change, there will
not be any new trips simply as a result of this re-location. There may, however, be induced traffic due to the
need to undertake the previously planned trips to new destinations, via new routes.
Table 1b. Behavioural responses leading to suppressed traffic
Changes in…. Suppress person trips/day? Suppress vehicle kms/day?
…route No Yes
…timing No No

…and in the longer term…

…mode (from private car) No Yes
…vehicle occupancy (increasing) No Yes
…trip frequency (decreasing) Yes Yes
…trip destination (becoming less remote) No Yes
…trip origin (becoming less remote) No Yes
In summary, it can thus be expected that — with the caveats of only occurring on networks
with either congestion or no spare capacity — a road capacity increase or reduction may result
in a change of route; timing; mode (or at least vehicle occupancy); trip frequency; trip
destination; or, over the longer term, trip origin. As illustrated in Table 1 these behavioural
responses have an impact on either the number of person trips, or the distance of existing
trips, or both. Both impacts potentially induce or suppress traffic.

The behavioural responses discussed above have been argued to be consistent with the basic
micro-economic theory of supply and demand (Goodwin 1997, Litman 1999, Noland 1999,
SACTRA 1994). In terms of the micro-economics of supply and demand, any increase in
supply (i.e. road capacity) results in a reduction in price (i.e. the generalised cost of travel).
The theory holds that when any good (i.e. travel) is reduced in price, demand for that good

increases. Hence increased road capacity leads to generalised costs going down, and so
demand for motor car travel increases and traffic is induced. Conversely, reduced road
capacity leads to generalised costs going up, and so demand for motor car travel decreases and
traffic is suppressed. Given that such micro-economic theory underpins so much modelling
and road scheme appraisal practice, as Phil Goodwin (1997) observes, ‘one wonders why the
phenomena are greeted with surprise’.

4. EMPIRICAL EVIDENCE
Documented empirical evidence on induced traffic has been available in the literature since
the early 1960s, but it was not until the 1990s that a body of authors began investigating the
topic in detail (Kitamura 1994). The seminal SACTRA report of 1994 has already been
mentioned, but perhaps equally influential in the US was the San Francisco Bay Area Lawsuit
(Garrett and Wachs 1996, Weiner 1997). In June 1989 two environmental organisations
claimed that the State of California, the Metropolitan Transportation Commission (MTC) of
San Francisco, and other regional agencies had violated the provisions of federal clean air
legislation by not doing enough to meet clean air standards. The case focused on the general
issue of the effects of increased road capacity on reducing public transport use, increasing
traffic speeds and enabling the spread of urban sprawl, all of which were argued to contribute
to greater air pollution emissions. The MTC had undertaken a conventional analysis to
determine the emissions impacts of its transportation plan. The environmental groups argued
that conventional travel forecasting models overstated the emission benefits of road building
in that, while they fully reflected the impact of speed improvements on reducing emissions,
they showed little or none of the air quality impacts of travel induced by speed improvements.
The phenomenon of induced traffic thus lay at the heart of the court case. At the time of the
trial the American Transportation Research Board was non-committal about the link between

roads, induced traffic and environmental pollution, but later evidence emerged from
California demonstrating that increased road supply did appear to increase vehicle kilometres
travelled (Hansen and Huang 1997). The verdict on whether or not this increase in vehicle
kilometres is detrimental to environmental pollution is still undecided. Most recently both
British and American authors have concerned themselves with how to model the induced
traffic which is now acknowledged to occur (DeCorla-Souza and Cohen 1999, Noland 1999,
Coombe et al 1998).

In this section empirical evidence which appears to have swayed the debate towards an
acceptance of induced and suppressed traffic phenomena are presented. Since there is a
considerable volume of empirical evidence available, only the pieces of evidence which are
particularly enlightening, or which appear particularly relevant to South Africa, are presented.

4.1 Evidence of induced traffic from traffic counts
Probably the most obvious means of examining this phenomenon is to inspect the results of
actual road improvements or closures and to compare these with what was expected. It is
enlightening to examine the case of the M25, London’s orbital freeway which was finally
completed in 1988. The press at that time branded the road as a ‘Transport Fiasco’ and
‘Obsolete before it was opened’, for reasons which will become evident through scrutiny of
Figure 1 and Table 2, giving the Annual Average Daily Two-way (AADT) traffic on selected
links of the M25 in 1992, and the equivalent design year forecast.

Table 2. A comparison of Design Year AADT and 1992 actual AADT on London’s M25
M25 Section Design Year Design Year
Two-way AADT

1992 Actual
Two-way
AADT

Difference between
1992 Actual AADT and
Design Year AADT
Junction 13-14 1997 97,100 162,000 64,900
Junction 21a-22 2001 41,500 106,000 64,500
Junction 11-12 1995 82,800 146,000 63,200
Junction 22-23 2001 56,500 114,000 57,500
Junction 20-21 2001 59,000 113,000 54,000
Junction 10-11 1998 75,900 129,000 53,100
Junction 8-9 2000 55,200 107,000 51,800
Junction 19-20 2001 59,500 110,000 50,500
Junction 14-15 2000 103,000 152,000 49,000
Junction 15-16 2000 100,000 143,000 43,000
Notes:
1. The ten sites showing the greatest difference between Design Year Two-way AADT and Actual 1992 AADT
were selected for inclusion in this table.
2. Total number of junctions for which data were available was nineteen.
3. Source of information: SACTRA 1994 and Denvil Coombe pers com 2000
A review of the experience of the M25 concluded that in the years immediately following the
opening of the freeway, reassignment, redistribution and mode shift had been important and
the SACTRA report speculated that induced development traffic (that is, induced traffic as a
result of new or changed destinations) may become important in future. SACTRA concluded
that the M25 appears to confirm the notion that roads induce traffic although the exact size of
this effect could not be established at that time.

Although the M25 is a widely quoted example, and one which instigated public interest in the
issue of induced traffic, there are of course many smaller road improvements where
comparisons similar to the one above can be made. Goodwin (1996) summarised evidence
from the SACTRA report and elsewhere, and compared the growth of traffic on improved
corridors with the growth of traffic in a control corridor. If a control corridor was not
available then average growth rates were used for comparison.. The results from this work
have been adapted and reproduced below.

Table 3. Summary of traffic impact of capacity increases at individual locations

Scheme Interval1 Result (after corrections, where necessary)2
Barnstaple Bypass 3 years +20% overall
M62 5 years +19%
York Northern Bypass Not clear Redistribution, modal diversion and new trips 2% of

interviewed drivers

Severn Bridge 1 year Authors suggest induced traffic is 44%
Westway (London) 4 months
10 years

Corridor +14% (Control3
+2%)

Authors suggest induced traffic of 40-50%
M11 (London) 9 years Corridor +38%. (Control +29%)
A316 (London) 12 years Corridor +84% (Control +66%)
Blackwall (London) 1 year Screenline +15%
M25/Lea (London) 4 months Corridor +9%
Rochester Way 2 years Corridors: West +26%, East +24%, Transverse +30%
Leigh Bypass 1 year Screenline +20%
Manchester Ring 1 year Corridors: East-west +23%, North-south +15%
Notes:
1. ‘Interval’ indicates time between capacity increase and analytical study.
2. ‘Result’ indicates changes in traffic flow after capacity increases, as a percentage of previous flow on the
link, corridor or screenline.
3. ‘Control’ indicates similar unimproved site, used for comparison purposes.
The conclusions from this work were that the growth rates in traffic on the improved
corridors, which appeared to be associated in some way with the road capacity change, were
on average 25%. The traffic growth element associated with the capcity change was found to
increase over time, with unweighted averages of 9.5% for less than a year, and 33% for
intervals of more than 5 years. Finally, whilst a reduction in traffic was observed on
alternative routes to the improved route, this was on average only half as great as the increase
on the improved route itself. In other words, the relief on alternative routes was not as great as
had been forecast.

Despite the weight of evidence in support of the induced traffic phenomena, the lack of
controlled experimentation means that it can never be categorically proven, in the scientific
sense. Although the definition of induced traffic requires a consideration of network-wide
effects, in practice this is rarely possible and a consideration of corridor effects is often the
best available evidence. Furthermore, it will never be possible to control the day-to day
variations which are symptomatic of urban traffic, nor to provide entirely satisfactory control
sites and so eradicate the effect of changes in traffic due to exogenous variables such as

economic growth or local migration (Bonsall 1996, Hansen 1998). This is the reality facing all
transport planners. Our transport ‘laboratories’ are not our own. Nevertheless, in conclusion to
its own report to the UK Department of Transport in 1994, the SACTRA committee stated
that:

“Considering all these sources of evidence, we conclude that induced traffic can and does
occur, probably quite extensively, though its size and significance is likely to vary widely in
different circumstances”. (SACTRA 1994:ii)
It may be argued that road capacity increases have indirect benefits, that is they lead to
commercial activity which may not have otherwise taken place. The SACTRA report is clear
on this point, and suggests that whilst indirect benefits may occur which are not accounted for
in an economic evaluation, these occur only in unusual specific circumstances. In order to
understand this point it is important to ask whether additional road capacity leads to any
completely new commercial activity, which would not have taken place anywhere else in the
country. It is rarely the case that genuinely new jobs are created as a result of a road scheme.

4.2 Evidence of suppressed traffic from traffic counts
A useful summary of the impact of capacity reductions on network flows is provided by
Cairns et al (1998). The researchers collected evidence from over forty locations on the
impact of capacity re-allocation as a result of bus lane implementation or pedestrianisation;
maintenance or structural repairs; or natural disasters such as earthquakes. The results were
wide ranging, but the unweighted average overall reduction in traffic on the network was 25%
of the traffic previously using the road or area subject to capacity reduction. An extract from
their analysis is provided in Table 5.

Since the publication of the SACTRA and the Cairns et al reports, the general consensus in
the UK has been that the induced and suppressed traffic phenomena occur. The debate now is

over their magnitude and importance. In the US the debate so far has focused more on
induced traffic, but the consensus also appears present there (Hansen 1998).
Table 5. Summary of traffic impact of capacity reductions at individual locations
Scheme Interval Result (after corrections, where necessary)
Tower Bridge closure 1 month -80%
Bologna City Centre 8 years -51%
Edmonton-Kinnaird Bridge Closure 3 weeks -42%
Partingdale Lane local area 3 months -30%
A13 closure 1 day -23%
Luneburg 3 years -15%
Cambridge city centre 5 months -11%
Freiburg ring road 10 months -7%
Edinburgh-New Town cordon 3 months -3%
Ring of Steel London ‘Square Mile’ 1 year -0.2%
Frankfurt am Main bridge closure Not clear +2%
Aarau 1 day +14%
Notes:
1. The table indicates changes in traffic flow after road capacity reductions, as a percentage of the previous
traffic flow in the area.
2. This table shows only a random selection of the cases listed in Cairns et al 1998.

5. IMPLICATIONS
What then are the implications of this general consensus for transport planning practice, and
for transport policy formulation? Since practice in South Africa tends to concern itself with
the provision of additional capacity, the implications of suppressed traffic are not discussed.
Both induced and suppressed traffic are, however, relevant to policy and are discussed in the
final sub-section.

5.1 Practical implications
To consider the practical implications of these findings — and of induced traffic more
particularly — it is necessary to reflect on how transport modelling and economic appraisal is
generally undertaken; to examine whether current practice adequately reflects induced traffic;
and to ask whether, in practical terms, this is important.

Induced traffic, as defined in Table 1 of this paper, is not completely ignored in the planning
process. Indeed, some components are well entrenched in modelling practice (such as
changes in route), others can be included theoretically, but are often not used in practice (such
as changes in destination). This inclusion of induced traffic phenomena in the modelling
process is described in Table 6.
Table 6. Inclusion of induced traffic in the modelling process
Changes in…. Induced traffic included? (Vehicle

kms/day)

…route Generally yes
…mode Generally no1
…vehicle occupancy (decreasing) Generally no
…trip frequency (increasing) Generally no
…trip destination (becoming more remote) Generally no2
…trip origin (becoming more remote) Generally no3
Notes:
1. Assumptions about mode choice changes may be made in forecasts, but a feedback loop between changes in
generalised cost on the vehicle network, and the mode choice model, are not common.
2. Although in theory the trip destination model can be used for forecasting, with new inputs of future costs, in
practice this is not often the case (Coombe, 1996).
3. Generally development is forecast exogenously and does not take into account the impact of the scheme under
consideration on the access patterns.
4. This table was based on Table 1 from DeCorla-Souza and Cohen (1998).
Data giving an estimate of the scale of the traffic not generally included in the four stage
modelling process is scarce. Goodwin (1996) suggests, from a comparison of modelled and
actual flows on nine urban schemes, that unpredicted traffic in the first year of a scheme is
almost 6%. Heanue (1998) examined traffic growth in Milwaukee over almost thirty years
and suggested that the growth which could be attributed to road capacity improvements was
between 6% and 22%. Coombe (1996) tackled the problem rather differently, attempting to
model all induced traffic effects, and then to compare the results with conventional model
outputs. In the congested urban case studies used he found that, in the cases where traffic was
induced, the overall short-term increase in trips was between 1% and about 3%. One could
argue over whether these findings are significant, given the large errors inherent in
conventional transport models (Atkins 1986), but this train of debate is to an extent futile,

since the largest impact of induced traffic appears to be in economic assessment, rather than in
modelling output.

The economic appraisal of urban road schemes usually involves the processing of aggregate
data from a transport model. In the first instance, a matrix of trip movements is derived from

base year data, and then this matrix is factored to some future year, using estimates of socio-
demograhic data, and any information relating to land-use development expected in the study

area. Alternatively, traffic flows are measured on critical links, and the forecast new link flows
are estimated using simple factoring techniques. The future-year matrix, or link flow data, is
then used with varying road network supply scenarios, in order to derive data for the future
year under consideration. The total time spent on the network by travellers (measured in
vehicle hours), vehicle operating costs, and accidents are then calculated for the do-minimum
and do-something future year scenarios. The difference in time, operating and accident costs is
an estimate of the economic benefit of the scheme. This information is the key input to the
economic evaluation process. The important point to note is that in the evaluation process the
trip matrix used is fixed, that is, it does not vary according to road supply (and hence
generalised cost conditions) on the network. Given the explanation of induced traffic outlined
above, this assumption of a fixed (or inelastic) demand matrix is erroneous, especially in cases
of new road supply in congested urban conditions (Brand 1991).

Some may argue that induced drivers receive a benefit from using the scheme, and so induced
traffic must be advantageous. It is true that, under the fixed matrix assumption, benefits to
induced drivers are ignored. In most circumstances, however, the benefits to induced drivers
are far outweighed by the delay costs, imposed by induced drivers, on the existing drivers on
the network. These delay costs (measured in vehicle hours) are significant since, in the

congested area of the speed-flow curve, even a small number of additional drivers on the
network can impose substantial delay penalties on the network as a whole (Mackie 1996).
Thus, when considering drivers on the network as a whole, induced traffic is not
advantageous.

The question which remains is: what practical difference does an assumption of a fixed
demand matrix make to economic evaluation? Coombe (1996) looked at the economic impact
of relatively small increases in induced traffic. He found that in West London induced traffic
of just 1% led to an erosion of benefits of 30% and in Norwich, induced traffic of 2.3-2.9%
led to reductions in benefits of 22-20%. One reason for this is that the small increase in
absolute vehicle hours, as a result of induced traffic, has a relatively large impact on the
difference in vehicle hours between a do-minimum and do-something case. To understand this
it is important to note that a large proportion of the benefits in economic evaluations come

from savings in vehicle hours. Typically the difference in vehicle-hours between a do-
minimum scenario and a do-something scenario may be of the order of only a few percent

(depending on the scope of the network considered). An additional 1-3% of induced traffic, in
the do-something scenario, thus has a significant impact. Hence, SACTRA were clear in their
statements regarding the importance induced traffic for economic evaluation. They stated that:
“the economic value of a scheme can be overestimated by the omission of even a small
amount of induced traffic” (SACTRA 1994:iii).

This conclusion needs however to be viewed with some circumspection in South Africa, as it
is based upon evidence from analyses of the UK economic evaluation programmes ‘COBA’,
which is not used here (Mackie 1996). To our knowledge researchers elsewhere have not
examined this topic in detail. However, given that much of the approach to transport

economics is universal, and given the strong evidence and conclusions from the British
literature, it seems to be timely to re-examine economic evaluation in South Africa, and to
investigate the impact of induced traffic on economic evaluations. To ignore this phenomena
could lead to seriously misleading economic evaluation results, and the subsequent allocation
of funds to inappropriate road schemes. In particular, the SACTRA findings indicate that
ignoring the induced traffic phenomena would tend to overinflate the economic benefits of
schemes where the network is operating at, or near to, capacity; or where trips are suppressed
by congestion (that is, roads in and around urban areas, and at freeway widening schemes).

5.2 Policy implications
With regard to implications for transport policy formulation, the evidence on induced traffic
shows that an urban transport strategy with road capacity improvements at its core cannot in
the long term bring relief to congestion and car dependency problems. If increased road
capacity induces traffic it follows then that whatever road capacity improvement policy is
implemented, with the caveat of pre-existing congestion, the amount of traffic per unit of road
will increase, not decrease. The same has been argued to be true of ‘advanced transport
telematics’ or ‘intelligent transport systems’ aimed at the more efficient use of road capacity
through driver guidance systems and improved traffic control (Bell 1995). Martin Mogridge
(1997) goes one step further and suggests that improving urban road capacity can in fact make
congestion worse, due to the impact that shifts in mode have on the viability of public
transport, which leads in turn to further mode shifts. This implies, as Phil Goodwin (1998)
puts it somewhat bitingly, that policies based on road capacity improvements differ only with
respect to ‘the speed at which congestion would get worse’.

If the evidence on induced traffic illustrates the futility of supply-side policies as a means of
solving urban congestion problems, the evidence on suppressed traffic perhaps provides a

pointer to an appropriate policy alternative. There would however appear to be a consensus in
debates around the policy implications of induced and suppressed traffic that to argue simply
for no future road capacity increases for private vehicles in urban areas would be absurd. This
seems particularly true in a developing country with comparatively poor infrastructure. Rather
what is called for in the literature, is a balance between supply-side and demand-side
strategies within an integrated transport policy framework (Bell 1995, Goodwin 1998). Within
such a balanced framework, it is argued that new road construction would need to be justified
in terms of its contribution to the implementation of a larger multi-modal transport plan,
rather than simply in terms of its estimated congestion benefits for motorists. Some parts of
the transport network may require road capacity increases, while other parts — particularly in
city centres and residential neighbourhoods — may require selective road capacity reductions
and reallocation to non-motorised and public transport modes. In the context of growing travel
needs, it is argued that selective reductions in road capacity for private vehicles would need to
be accompanied by increases in the capacity and quality of the public transport network. Other
aspects of such an integrated policy are seen to include a variety of travel demand
management measures that involve neither the increase nor decrease of capacity, but changes
in the generalised cost of travel (e.g. congestion pricing, parking tariffs and public transport
fares).

What then can be said about the Moving South Africa statement quoted in the introduction of
this paper? The international experience reviewed would appear to support the policy
direction expressed here unreservedly. Our only criticism is that such a fundamentally
important, and often contentious, set of debates and research findings has received such
cursory attention within the new policy documentation. The international experience would
suggest that those who undertake the design of road schemes, and painstakingly nurse these

schemes through the minefields of public and political approval, are extremely reluctant to see
them struck from improvements lists (Goodwin 1998, 1999). As a consequence abandoned

road schemes tend to resurface over and over again. For Moving South Africa’s above-
mentioned policy direction to be acted upon at a sub-national level in South Africa,

considerable convincing and debate will probably be required. This paper hopefully serves
towards that end.

6. ACKNOWLEDGEMENTS
The authors would like to thank Wilfred Crous, Romano Del Mistro, Paul Mann, Chris
Roebuck, Christo Venter, Peter Wilkinson and Keith Wolhuter for criticisms and comments
on earlier versions of this paper. The comments of the two anonymous South African
Transport Conference (2000) referees are also acknowledged. Responsibility for any errors
remains our own.

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Curriculum Vitae of Authors
Lisa Kane is a graduate civil engineer who specialised in transportation planning whilst
working for The MVA Consultancy and Oscar Faber TPA in the UK. She has worked at the
University of Cape Town since 1996, attained her Masters degree there and is currently an
Honorary Research Associate in the Urban Transport Research Group. Her main field of
interest is transportation planning method.

Roger Behrens is a registered town and regional planner, and a PhD candidate in the field of
transportation planning at the University of Cape Town. He has worked at the university’s
Urban Problems Research Unit as a researcher and consultant since 1992, and is now a
member of the Urban Transport Research Group. His current fields of research interest lie in
transport policy analysis, activity-based methods of travel analysis, local area movement
network design, and non-motorised modes of transportation.

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