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Road capacity change and its impact on traffic in congested networks: evidence and implications

Road capacity change and its impact on traffic in congested networks: evidence and implications

Roger B Behrens & Lisa A Kane’

This article reviews explanations of, and international empirical evidence for. ‘induced’ traffic
as a result of increased road capacity and ‘suppressed’ traffic as a result of decreased road
capacity. In essence, the former refers to new traffic appearing as a result of new road
construction, while the latter refers lo traffic disappearing as a result of road closure. Despite
problems with the available data and their measurement, it is concluded that – with the caveats
of either pre-existing congestion in the case of capacity increases or no spare capacity in the
case of capacity decreases – the weight of evidence indicates that induced and suppressed traffic
are indeed real phenomena. It is argued that the link between traffic and road capacity is
therefore far more complex ihan previously understood. The implications this has for hoth urban
passenger transport planning practice and policy formulation are discussed.
1. INTRODUCTION
Under-funding of” transport infrastructure investment in South African cities in recent
years and a concomitant increase in competition for limited transport project funding
have led to considerable debate on the priority and appropriateness of proposed
investments in transport infrastructure. Tn particular, debate has focused on whether
increasing road capacity through adding new network links or widening existing roads
constitutes the most effective and indeed the most appropriate means of addressing the
problem of traffic congestion that besets cities in periods of peak travel demand. While
different in scale and context, other parts of the world have had similar debates, and
a considerable body of literature has now developed on the often counter-intuitive,
empirically observed impacts that road capacity change has on the alleviation of traffic
congestion problems. The literature documenting these empirical studies deals, in
essence, with two phenomena associated with road capacity change – ‘induced’ and
‘suppressed’ traffic.
The purpose of Lhis article is to review the intemational literature, and extract from it
the implications for transport planning policies and practices that seek to address the
vexing problems of identifying the appropriate nature of transport infrastructure
investment and prioritising transport projects in the context of resource scarcity and
competition.
The article begins hy defining what is meant by the terms ‘induced’ and ‘suppressed’
traffic (Section 2). Section 3 reviews the explanations offered in the literature of the
behavioural responses that give rise to induced and suppressed traffic phenomena.
‘Respectively, Senior Lecturer, and Honorary Research Associale. Urban Transport Researeh
Group. Faculty of Engineering and the Buili Environment, tjniversity of Cape Town. Cape
Town, South Africa. An earlier version of this article was presented at the 19th annual South
African Transport Conference (Kane & Behrens, 2000).
ISSN 0376-835X print/ISSN t470-3637 ontine/04/040587-t6 © 2004 Development Bank of Southern Afriea
DOI: 10.tO8O/O3768350420OO2888O6

588 RB Behrens & LA Kane
Section 4 reviews the empirical evidenee supporting the existence of these phenomena.
Seclion 5 discusses ihc implications this evidence ha.s for transport planning practice
and policy formulation. The article concltides with a discussion on the relevance of
ihese implications for the South African context (Section 6).
2. DEFINITION OF INDUCED AND SUPPRESSED TRAFFIC
The watershed publication in the debate over induced traflic was, without doubt, a
report submitted to the United Kingdom’s Secretary of State for Transport in 1994, by
the Standing Advisory Committee for Trunk Road Assessment (SACTRA. 1994).
Although fcKTused priniiirily on trunk roads (i.e. roads in the national road system
managed by the national govemment), the location of many of these routes through, or
close to, conurbations meant that roads with a wide variety of iraftic 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
trat’iic redistribution, mode choice and generation (resulting from new road schemes)’
(SACTRA, 1994: I).
At the outset, the committee recognised that the notion of “roads generating traffic’ was
one thai had gained widespread popular acceptance, but ihai had not been subjected to

much rigorous investigation. There had been confusion and inconsistency over termi-
nology in the literature, one reason being that the definitions of ‘generated’ traffic are

not straightforward. Until ihe 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 ehose to address this issue of definition in detail
(sec Hills, 19%). iuid this section of the article summarises the final definition they
chose to use. Others have suggested slight variants on this definition in the intervening
years (e.g. Heanue, 1998; Litman, 1999), but lor the purposes of this article SACTRA’s
definition is used.
As a first step in its work, SACTRA decided that the word ‘generate’ was problematic
to use, as ‘trip generation’ has a very specific meaning in a transport planner’s
vocabulary. Usually a household or individual is undersKKxl to generate trips, as the
tirst 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
non.sensical. Tu preclude any confusion over this particular i.ssue. the SACTRA
committee chose to replace the term ‘generate’ with ‘induce’, and to investigate
whether the provision of roads induces (i.e. indirectly brings about) traffic. In summary,
the definition adopted by SACTRA was that induced traffic is the additional daily
private vehiele traffic thai may occur on a network following some increa.se in road
capacity. It does not, therefore. Include additional traffic tbund on individual links it the
total of network vehicle kilometres remains constant, nor docs ii include additional
traffic found in the peak period if the total of daily vehicle kilometres remains eonstant.
The literature on the relationship between traftic levels and road capacity was
broadened considerably by the more recent publication of a report entitled. Traffic
impaci i)f hifihway capacity reductions: a\.’iessim’nt of the evidence (Cairns et al..
1998). This report was commissioned by London Transport and the Department of
Enviroimient Transport and the Regions. The premise of the study was tbat if we accept
the notion of induced traffic, we must also consider the possibility of traffic being

Road capaeity change and its impact on traffic in congested networks 589
suppressed when road capacity reductions are imposed. The report therefore reviewed
evidence of the traffic impacts of eapaeity reduetions (e.g. as in the ease of a bridge
or lane elosure). rather than inereases. (t is important to note that in this report, as wel!
as in the earlier SACTRA report, the capacity increases or reductions in question
referred speeifieally to road capacity change for private vehicles. The impacts of
increased or reduced capacity for public transport were therefore nol investigated in any
significant way.
This article 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: Indueed (or suppressed) traffie is the
additional (or reduced) daily private vehieie traffic that occurs on a network following
some eapaeity increase (or reduction) or, as discussed in the following section, some
other reduction (or increase) in the generalised cost of travel.

3. EXPLANATION OF INDUCED AND SUPPRESSED TRAFHC PHENOM-
ENA

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
on, their travel choices. The phenomena of indueed and suppressed traffic have thu.s
been observed lo occur in situations where a change in road capacity causes a
significant change in the generalised eost or attractiveness of motor ear 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 generalised cost (e.g. a river
crossing). In the case of capacity reduetions. such cost changes would oeeur typically
in situations where road space is taken away from networks that have little or no
existing spare eapaeity (Goodwin, 1996; Caims et al., 1998; DeCorla-Souza & Cohen,
1999).
What 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 nodceably different in the immediate,
short and long term (Kitamura. 1994; SACTRA, 1994: Goodwin. 1996; Cairns et al.,
1998; Dowling & Colman, 1998; DeCorla-Souza & Cohen, 1999; Litman, 1999;
Noland, 1999). ln many but not all respects, behavioural responses to increased
capacity mirror, in inverse form, responses to reduced capacity. These temptirally
differentiated responses are discussed below and are summarised in Tables la and Ib.
In the immediate term (i.e. tbe first few days), drivers often simply change their driving
styles in ways that adjust to the new traffic conditions. In the ease of capacity
reductions in particular, and often depending on the amount of forewarning reeeived by
media predictions of ‘traffic cbaos’, they bave been observed to drive slower and closer
together. However, the introduction of a £5,(X)/day congestion charge in London in
February 2(X)3 – whereby the generalised cost of private cars was significantly altered
– suggests tbat immediate-term responses can extend beyond simply changed driving
styles. On the first day of tbe seheme (albeit a school holiday), instead of the traffic
‘nightmare’ predicted by the media, automated counting machines showed ibat the

590 RB Behrens & LA Kane
Table la: Behavioural responses leading to induced traflic
Changes in: Induce person Irips/day? Induce vchicte km/day?
Route No Yes
Timing No No
Mode (to private car) No YeB
Vehicle (Kxupancy (decreasing) No Yes
Trip frequency (increasing) Yes Y «
Trip destination (becoming more remote) (Yes)’ Yw
Trip origin (becoming more remole) (No)^ Yes
Notes: In the longer lerm. land-use cttanges as a result of capacity increases may result in new destinaUons
on otTer, and hence new trips.
”The soiirte of trip origins is ihe household, and while the location of ttie household may change, iherc will
not be any new trips simply an a result of this relocation. There may, however, be induced traffic due to the
need to undertake ^ e previously planned trips to new destinations, via new routes.
Table Ib: Bebavioural responses leadin}> to suppressed traffic
Changes in: Suppress person trips/day? Suppres.s vehicle km/day?
Route No Yes
Timing No No
Mode (from private car) No Yes
Vehicle occupancy (increasing) No Yes
Trip frequency (decreasing) Yes Yes
Trip destination (t)ecoming tess remote) No Yes
Trip origin (txrconiing less remote) No Yes
amount of moming traffic moving into central London was 25 per cent lower than on
a nonnal working day (Clark, 2003).
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 titnes, 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
refened 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 are
re.scheduled (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 links 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 reappeai- on other
equidistant links within the network or at other times on the same links. 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. Only if the re-routed trips
involve significantly shorter or longer trip distances does induced or suppressed traffic
occur. Rescheduled departure times, on the other hand, would not strictly induce or

Road capacity change and its impact on traffic in congested netu^orb; 591
suppress traffic, even though Noland (1999) does observe that tbe ‘return-to-peak’
effeet may induee new trips by freeing up capacity at other times of the day and
theoretically, at least, tbe inverse would be true for shifts to the off-peak times.
In the longer term (i.e. up to five to ten years after the capacity cbange), 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 lo
people taking irips by car that were previously undertaken by olber modes, taking more

frequent trips, or because of improved travel speeds, taking Irips lo preferred destina-
tions furtber away. In the case of capacity reductions, the failure of shorter-term

behavioural adjustments to avoid unacceptable eongestion delays may lead to people
using non-motorised or public transport modes instead ol” their cars, suppressing
non-essendal trips or at least linking previously separate trips into ehains, or seleeting
nearer destinations. In some instances, the change in travelling conditions may ‘tip the
balance” in decisions that were being made for otber reasons, such as buying or selling
a car, moving house or moving job. All ibese behavioural responses potentially
contribute to indueed or suppressed traffic effects, ln addition to these bebavioural
responses, increased road capacity (and accessibility) can stimulate unforeseen changes
in land-use pattems, whicb can generate further unexpected traffic (Headicar, 1996).
In summary, it ean thus be expeeted tbat – with the caveats of occurring on networks
with either eongestion or no spare capacity – an increase or reduction in road capacity
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
I, these behavioural responses have an impaet on eitber the number of person trips or
the distance of existing trips, both of wbich potentially induce or suppress traffic.
Tbe behavioural responses discussed above have been argued to be consistent with the
basic microeconomic theory of supply and demand (SACTRA, 1994; Goodwin. 1997;
Litman, 1999; Noland, 1999), In terms of the mieroeeonomies of supply and demand,
any increase in supply (i.e. road capacity) results in a reduction in price (i.e. lhe
generalised eost 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 indueed. Figure 1 illustrates the indueed traffic effect in terms of this tbeory. Line
i7 represents road capacity supply before new road construction. Line s2 represents
road eapaeity supply after an increase in capaeity that results in a lower generalised
eosi of” travel – from gcJ lo {>c2. Following tbe dashed line that plots increased demand
in relation to decreased cost, at gel on the y-axis tbe quantity of travel (measured in
vehicle kilometres travelled) is ql on the .v-axis. At gc2 the quantity of travel is q2. The
quantity of travel therefore inereases from ql to q2 as ibe change in supply lowers tbe
eost of travel from gel to gc2. The increase in tbe quantity of travel from ql to q2
represents the induced travel effect.
Conversely, reduced road capacity leads to generalised eosts going up. and so demand
for motor car travel decreases and traffic is suppressed. Given that such microeconomic
theory underpins so mucb modelling and road scheme appraisal practice, as Goodwin
(1997) observes, ‘one wonders why tbe phenomena are greeted with surprise*.
4. EMPIRICAL EVIDENCE
Documented empirical evidence on induced traffic has been available in the literature

592 RB Behrens & LA Kane

gel
cost •
* • •
4 /

Supply before road
capacity increase

j Increased road
/ capacity

Supply afler road
capacity decrease
* • DemantKin VKT)
V’
^^.^-‘- n Induced travel
–“”‘ ^ (in VKT)
q\ q2
Quantity of travel (vehicle kilometres travelled)

Figure 1: Induced traffic explained in terms of the microeconomic theory of
supply and demand
Note: VKT = vehicle kilometres travelled.
since the early t%Os. but it was not until the 1990s thai a body of authors began
investigatinj; the topic in detail (Kilamura. 1994). The .seminal SACTRA repon of 1994
has already been mentioned, but perhaps equally influential in the United States was the
San Francisco Bay Area Lawsuit (Ganretl & Wachs. 1996; Weiner. 19971. In June
1989. two environmental organisations claimed ihat the Stale ol” California, the
Metropolitan Transportation Commission (MTC) of San Francisco, and other regional
agencies had violated the provisions of federal clean air legislation by nol 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 hud undertaken a conventional analysis lo 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 ihus 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 pol-
lution, but later evidence emerged from Califomia demonstrating that increased road

supply did appear to increase vehicle kilometres travelled (Hansen & 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 that is now
acknowledged to occur (Coombe et al., 1998; DeCorla-Souza & Cohen, 1999; Noland.
1999).
In this section, empirical evidence which the authors believe has at least swayed the
academic debate towards an acceptance of induced and suppressed traffic phenomena..

Rcmd capacity change and it.s impact on traffic in congested networks 593
is presented. As there is a considerable volume of empirical evidence available, only
the pieces of evidence that are particularly enlightening, or that appear particularly
relevant to South Africa, are presented.
4.1 Evidence of induced traffic from before-and-after 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
that was finally completed in 1988. The press at that time branded tlie road as a
“transport fiasco’ and ‘obsolete before it was opened’, for reasons that will become
evident through scrutiny of 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.
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. The SACTRA report speculated that induced development traffic (i.e.
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) summarises
evidence from the SACTRA report and elsewhere, and compares 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 are reproduced in Table 3.
The conclusions from this work were that the growth in traffic on the improved
corridors, which appeared to be associated in some way with the road capacity change,
was on average 25 per cent. The traffic growth element associated with the capacity
change was found to increase over time, with unweighted averages of 9,5 per cent for
less than a year, and 33 per cent for intervals of more than five years. Finally, while
a reduction in traffic was observed on altemative 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 altemative 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 that 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 (SACTRA,
1994; Li):
Considering all these sources of evidence, we conclude that induced traffic

594 R8 Behrens & L4 Kane
Table 2: A comparison of design year AADT^ and 1992 actual AADT on London’s
M25 orbital freeway
M25 sectioD Design year

1997
2001
1995
2001
2001
1998
2000
2001
2000
2000

Design year
two-way AADT

97 KH)
‘ 41 5H0
82 800
56 500
59 000
75 900
55 200
59 500
103 000
100 000

1992 actual
two-way AADT

162 000
106 000
146 000
114 000
113 000
129(K)O
107 (K)0
110 000
152 000
143 000

Difference between
1992 actual AADT
and cle<iit>n year
AADT
64 900
64 500
63 200
57 500
54 000
53 100
51 800
50 500
49000
43 000

Junction 13-14
Junction 2Ia-22
Junction II-I2
Junction 22-23
Junction 20-21
Junction 10-11
Junction 8-9
Junction 19-20
Junction 14-15
Junction 15-16
,^ 180000
2 160000
S” 140 000
i 120000
Z. lOOOOO
•i 80000
S 60000
u
” 40000
20000
m

m m

— — — — — — (NC I
ol =!> i 4 ./. ^i
20-
1 ^
o
•a
i

D Design year (between 1995 and 2001) AADT 0 Unexpected traffic

Notes: ‘AADT = annual average daily two-way (traffic).
“The ten sites showing the greatest difference between design year two-way AADT and actual 1992 AADT
were selected for inclusion in this table.
Total number of junclions for which data were available was 19.
Sourccx: SACTRA (1994: 46); Coombe (2000).
can and does occur, probably quite extensively, though its size and
significatice is likeiy to vary widely in different circumstances.
It may be argued that road capacity increases bave indirect benefits; that is, they lead
to commercial activity that may not have otherwise taken place. The SACTRA report
is clear on tbis point, and suggests that while indirect benefits may occur that are not

Road capacity change and its impact on traffic in congested networks 595
Table 3: Summary of traffic impact of capacity increase.s at individual locations
Scheme
Bamstapie Bypass
M62
York Northem Bypass
Severn Bridge
Westway (London)
Mil (London)
A.316 (London)
Blackwaii (Ixmdon)
M25/l^a (London)
Rochester Way
L^eigh Bypass
Manchester Ring

Interval’
3 years
5 years
Not clear
! year
4 months
10 years
9 years
12 years
1 year
4 months
2 years
1 year
1 year

Result (after corrections, where necessary)
+ 20% overall
+ 19%
Redistribution, modal diversion and new tfips 2% of
interviewed drivers
Authors suggest induced traffic is 44%
Corridor + 14% (control + 2%)
Authors suggest induced traffic of 40-50%
Corridor + 38% (control + 29%)
Corridor +84% (control +66%) ‘
Screenline + 15%
Corridor +9%
Corridore: West + 26%. East + 24%. Transverse + 30%
Screenline +20%
Corridors: East-west + 23%, North-south +15%
Notes: ‘”Interval” indicates the time between capacity increase and analytical siiudy.
“Result’ indicates changes in traffiu ilow after capacity increases, as a percentage of previous flow on the
link, corridor or screenline.
^’Control* indicates similar unimproved site, used for comparison purposes.
. Goodwin (1996: 46).

, , I –
accounted for in an economic evaluation, these take place only in unusual specific
circumstances. It is important to ask whether additional road capacity leads to any
completely new commercial activity that 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 before-and-after 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 40 locations on

the impact of capacity reallocation as a result of bus lane implementation or pedestri-
anisation: 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 per cent of the traffic previously using the road or area suhject
to capacity reduction. A randotnly selected extract from their analysis is provided in
Table 4. Figure 2 sutiimiirises the data on induced and suppressed traffic presented in
Tables 3 and 4. to illustrate the fairly consistent impact the road capacity increases and
reductions have on daily network traffic flows.
Since the publication of the reports hy SACTRA and Cairns et al., the general
consensus in the United Kingdom has been that induced and suppressed traffic
phenomena occur. The current debate is over their magnitude and importance. In the
United States, the debate so far has focused more on induced traffic, but the consensus
also appears present there (Hansen, 1998).

596 RB Behrens & LA Kane
Table 4: Summary of traffic impact of capacity reductions at individual locations
Scheme Interval Result (aOer corrections, where necessary)
Tower Bridge closure ! monih — 80%
Bologna city centre 8 years – 51%
Edmonion-Kinnaird Bridge closure 3 weeks ^42%
Paningdale Lane local area 3 months – 30%
A13 closure 1 day -23 %
Luneburg 3 years -15 %
Camhridge city centre 5 months – 11%
Freiburg ring road 10 months – 7%
Edinburgh-New Town cordon 3 months – 3%
Ring of Sieel London ‘Square Mile’ ! year — 0.2%
Frankfurt ara Main bridge closure Not clear + 2%
Aarau I day + 14%
Notes: The table indicates changes in traffic flow after road capacity reductiotis, as a percentage of the
previous traftic flow in the area.
Snurce: Caims et al. (1998: 34-50).
5. IMPLICATIONS
What, ihen, are the implications of this general consensus tor transport planning
practice, and for transport policy formulation? These are discussed in tum.
5.1 Practical Implications
When considering lhe practical implications of these findings – and more particularly
of induced traffic – it is necessary to rellect on how transport modelling and economic
appraisal are generally undertaken; to examine whether current practice adequately
reflects induced traffic: and to ask whether, in practical terms, this is important.
induced traffic, as explained earlier in Table 1, is not ignored completely in the
planning process. Indeed, some components are well entrenched in modelling practice
(such as changes in route); others can be included theoretically, bul are often not used

in practice (such as changes in destination). This inclusion of induced traffic phenom-
ena in the modelling process is described in Table 5.

Data providing an estimate of the scale of the traffic not generally included in the
four-stage modelling process are scarce. Goodwin (1996) suggests, from a comparison
of modelled and actual flows on nine urban road schemes, that unprcdicted traffic in
the Iirst year of a scheme is almost 6 per cent. Heanue (1998). wlu) examined traffic
growth in Milwaukee during almost 30 years, suggests lhat the growth which could be
attributed to road capacity improvements is between 6 and 22 per ccnl. Coombe (1996)
tackles the problem rather diflerenlly. 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 finds that in the eases where traftic was induced, the overall
short-term increase in trips was between I and about 3 per cent. One eould argue
whether these findings are significant, given the large errors inherent in conventional
transport models (Atkins. 1986). bul this train of debate is to an extent fufile. as lhe

Road capacity change and it.s impact on traffic in congested networks 397
100
80
60 –
4 0 –
20 £

g -20-I
-40
-60
-80-
-100-
Capacity decreases Capacity increases
Figure 2: Changes in daily network traffic flows after road capacity changes
Note: Known time intervals of before-and-after studies are indicated in parentheses.
Source: Cairns et al. (1998: 349-50); Goodwin (1996: 46).
Table 5: Inclusion of induced traffic in the modelling process
Changes in: induced traffic included? (vehicle km/dayl
Route
Mode
Vehicle occupancy (decreasing)
Trip frequency (increasing)
Trip deslinalion (becoming more remote)
Trip origin {becoming more remote)

Generally yes
Generally no’
Generally no
Generally no
Generally no’
Generally no’

e.^: ‘Assumptions about mode-choiee 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.
•Although in theory the trip destination mode! can be used for forecasting, with new inputs of future costs,
in practice Lhis is not oficn the case (Coombe. 1996).
•’Generally, development is forecast exogenously and does not take inlo account the impact of the scheme
under consideration on the access patterns.
Source: t)eCorIa-Souza &. Cohen (t998).
largest impaet of induced traffic appears to be in economic assessment, ratber tban in
modelling output.
The economic appraisal of urban road schemes usually involves tbe processing of
aggregate data from a transport model. In the first instance, a matrix of trip movements

598 RB Behrens & lA Kane
is derived from base year data, and then this matrix is factored to some future year,
using estimates of sociodemographic 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 consider-
ation. 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 appropriately weighted 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. Note thai in the
evaluation process the trip matrix used is usually 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 ahove. this assumption of a fixed or inelastic
demand matrix is erroneous, especially in cases of new road supply in congested urban
conditions (Brand, 1992).
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 as. in the congested area of the speed-fiow curve, even a small numher 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 I per cent led to an erosion of benefits of 30 per cent,
and in Norwich induced traffic of 2.3-2,9 per cent led to reductions in benefits of
22-20 per cent. 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 targe 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
per cent, depending on the scope of the network considered. An additional 1-3 per
cent of induced traffic, in the do-something scenario, thus has a significant impact.
Hence, SACTRA was clear in its statements regarding the importance of induced traffic
for economic evaluation, stating that ‘the economic value of a scheme can be
overestimated by the omission of even a small amount of induced traffic’ (SACTRA,
1994: iii).
In summary, to ignore the impact of induced traffic on economic evaluations can lead
to seriously misleading economic evaluation results, and the subsequent allocation of
funds to inappropriate road .schemes. In particular, SACTRA’s 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.

Road capacity change and its impact on traffic in congested networks 599

5.2 Policy implications
With regard to implications for transport policy fonnuliition, the evidence on induced
traffic shows that an urban transport strategy with road capacity improvements at its
core cannot bring relief to congestion and car dependency problems in the long term.
If increa.sed road capacity induces traffic, it follows that whatever policy for road
capacity improvement 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). 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 in tum leads to
further mode shifts. This implies, as Goodwin (1998) puts it somewhat bitingly, that
policies based on road capacity improvements differ only witb respect to ‘tbe speed at
which congestion would get worse’.
If tbe evidence on induced traffic illustrates the futility of supply-side polieies as a
means of solving problems of urban congestion, the evidence on suppressed traffic
perhaps provides a pointer to an appropriate policy altemative. There would, however,
appear to be 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 and a need for rapid economic growth.
Rather, what is called for in the literature is a balance between supply-side and
demand-side strategies witbin 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 implcmeti-
tation 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 reductions in road capacity and the
reallocation of road space 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 measures for travel demand management that involve neither the
increase nor decrease of capacity, but changes in the generalised cost of travel, such
as congestion pricing and parking tariffs.
6. CONCLUSION
What, then, is the relevance of the empirical findings reviewed in tbis article, and what
is the relevance of their practical and policy implications to the South African context?
It is probable that choice passengers in South Africa perceive public transport to be less
safe and less reliable than do their counterparts in countries like the United Kingdom.
It is therefore assumed that, in the absence of significant safety and reliability
improvements. South African choice passengers are less likely to switch from private
car to public transport modes. Consequently, it is Hkely that induced traffic resulting
from shifts from public transport modes to private car use will be considerably less in
South Africa than in tbe United Kingdom, as a relatively larger proportion of choice

600 RB Behrens & LA Kane
passengers already utilise private cars. Similarly, suppressed traffic resulting from shifts
from private car to public transport, due lo reduced generali.sed costs for the former,
would also be considerably less. The other behavioural responses to capacity change
discussed In Section 3 (i.e. changes in route, vehicle occupancy, trip frequency and
destination) should, however, retnain reasonably constant across the different contexts,
and the direction of impacts should therefore remain true in South African cities even
if the scale of impact is different. Meta-analysis of South African before-and-after
studies will, however, be necessary to test the assumptions embedded in this argument.
From the particular interpretation of the relevance of the evidence reviewed in this
article, it is therefore concluded that strategie.s for addressing traffic congestion
problems in South African cities, based primarily on supply-side road capacity
improvements (in the form of either new infrastructure provision or measures for

transport systems management aimed at achieving better utilisation of existing ca-
pacity), will be unable to bring relief in the longer term. Balanced supply- and

demand-side strategies that incorporate new infrastructure provision, transport system
management and travel demand management, integrated with land-use strategies that
reduce the need for travel, offer the only realistic longer-term prospects for relieving
congestion and improving accessibility for the populations of South African cities.
In the authors’ view, however, it is necessary to reframe the urban passenger transport
probletn from one focused primarily on inefficiency or traffic congestion, to one
focused equally on inefficiency, inequity and non-sustainability. The former problem
framing leads to the allocation of road space resources to alleviate congestion for
general traffic. The latter leads to a more disaggregated and dedicated allocation of road

space resources to benefit all passengers equally and to encourage the use of high-oc-
cupancy and low-polluting travel modes. From this perspective, given the historical

injustices imposed on passengers captive to public transport and non-motorised modes
in South African cities, the authors believe it to be entirely justifiable and appropriate
to reallocate proportionate shares of road space, in the form of footways, cycleways and
dedicated bus lanes, for exclusive use by pedestrians, cyclists and public transport
users, even if tbis imposes greater congestion costs on private motorists. The evidence
reviewed here suggests that, provided policy commitments to improving the quality and
safety of public iransport services are followed through, this would not lead to the
general traffic chaos many would expect. ‘
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