Treatment of Induced Traffic

Part of Toolkit for the Economic Evaluation of World Bank Transport Projects

(Institute for Transport Studies, University of Leeds, 2003)


Induced traffic can be an important part of the economic appraisal particularly when the objective of the investment is to stimulate economic development.  It’s importance, however, is not restricted to such situations.  The omission of induced traffic from the economic appraisal, or its incorrect treatment, may lead to either over or underestimations in the user benefits (consumer surplus) of an investment.

In this note we address this issue by considering: the importance of induced traffic for the economic appraisal (Section 1); what constitutes induced traffic (Section 2); the situations in which induced traffic is likely to be relevant (Section 3) and the manner in which it can be modelled (Section 4) and user benefits calculated when it is present (Section 5)

1                   The Importance of Induced Traffic

Historically, projects have been justified on the basis of benefits to existing traffic only.  The impacts of induced traffic were not incorporated into the economic analysis unless the project could not be justified on the basis of existing traffic alone, the basis for such an approach is that there is uncertainty associated with the level of traffic that will be generated by a project.  However, apart from the potential of underestimating the benefits of the project such an approach may also have the following important limitations and consequences:

·                    User benefits may in fact be overestimated (not underestimated) if underlying traffic conditions are congested;

·                    A sub-optimal design standard for the project maybe promoted, i.e. the project could be under designed.

·                    A potentially good project or scheme maybe completely rejected;

·                    A potentially bad project could be promoted;

·                    The relationship between the infrastructure and the wider economy could be neglected.  In the absence of a detailed economic model the amount of induced traffic can be an interesting indicator and a proxy measure of the wider economic impacts (providing demand in the system is being correctly modelled);

·                    A significant change in fiscal benefits that may accrue to certain bodies maybe omitted, for example Government tax revenue in the case of “free” roads and additional financial income in the case of commercial facilities such as railways, toll roads and bridges; and

·                    An underestimation of environmental impacts could occur

The consequences of omitting induced traffic from the appraisal are therefore significant.  The remainder of this Note discusses the situations when induced traffic is relevant to the appraisal and the manner that user benefits should be calculated in the presence of such traffic.

2                   What is Induced Traffic?

When a new transport facility or service becomes available the users of the transport system can alter their behaviour in a number of manners:

·                    Change their route

·                    Change mode

·                    Change destination to one easily reachable using the new system

·                    Change their trip making frequency

·                    Change the time of travel

Additionally, the transport project may result in an altering of land use patterns.  For example, a new road and river crossing may facilitate economic development that would not have otherwise occurred, by say improving accessibility to markets.  The impact of changing land use patterns is discussed further in the Note Projects with Significant Restructuring Effects [Link]. 

Transport users can be categorised a number of ways (see also the Note Demand Forecasting Errors [Link].  The basis for the classification in Table_1 is the previous behaviour of the traveller or traffic and the manner in which they alter their behaviour as a consequence of the project.  As can be seen from this table Induced Traffic is therefore defined as the additional traffic (in person or vehicle kilometres) that has been induced by the project through mode changes, destination changes, trip re-timing, trip frequency changes or new trips associated with different land uses.

Table 1: Traffic Classification by Behavioural Response

Behavioural Response

Classification from the perspective of

Demand associated with the project

Demand within the entire multi-modal transport system

No change in behaviour

Base Load or Traffic

Normal Load or Traffic

Route change (same origin and destination after route change)

Re-assigned or Diverted Traffic

Mode change

Induced Traffic

Destination change

Time of travel change

Trip frequency increase

Generated Traffic

Generated or new (e.g. from different land use patterns)

Note: the term traffic is used to represent all forms of transport traffic including pedestrian traffic, road traffic, railway traffic and shipping traffic


3                   When is induced traffic likely to be Relevant.

There are two principal situations when induced traffic is likely to be relevant for an economic appraisal (see also Box 1):

      (i)            Firstly, when the benefits that will accrue to the Induced Traffic are significant compared to the benefits that will accrue to Base and Re-assigned Traffic; and

    (ii)            Secondly, when the Induced Traffic imposes significant costs on the Base and Re-assigned Traffic (e.g. a congestion or overcrowding cost).


Such situations are likely to occur within the following scenarios:

·                    Significant time savings for individual origin to destination movements occur (e.g. a new river or estuarial crossings where none previously existed)

·                    Significant cost (financial) savings for individual origin to destination movements occur (e.g. situations where transport costs form a large proportion of the total delivered price of the product shipped or the total cost of the trip purpose activity);

·                    High elasticity of demand is present (for example within a highly congested urban environment);

·                    Heavily congested conditions (steeply upward-sloping supply schedules);

·                    Changes in land use patterns will occur (i.e. structural economic shifts);

·                    There is little or no existing (Base) traffic (e.g. transport projects that break new ground).


The inclusion of Induced traffic within a project appraisal is also important when one of the objectives of the project is to stimulate economic development, particularly trade (trucks, freight trains and ships). 

Box 1: Measurement of induced traffic benefits

Induced traffic contributes to the consumer surplus of a transport investment in the manner illustrated in Figure 1.  In this figure the aggregate benefit to travellers between A and B arising as a result of a fall in the cost of a trip (from C0 to C1) is C0DEC1.  The contribution of induced traffic (the difference between T1 and T0) to the user benefit is the area DEF, whilst the contribution of the Base and Re-assigned traffic is the area C0DFC1.

Figure 1: User benefit Measure


If, however, induced traffic had been excluded from the appraisal, that is a Fixed Trip Matrix (FTM) assumption had been made, the benefit derived by that traffic, area DEF, would be excluded from the analysis.  The inclusion of induced traffic is therefore important in situations where its benefit is large.

An additional error can also occur under the FTM assumption in the presence of congestion or overcrowding, as the benefit to the Base and Re-Assigned traffic can be overestimated.  This is illustrated in Figure 2.  Under the FTM assumption the benefit to Base and Re-Assigned traffic would be estimated as C0DGC2, whilst the correct measure is C0DEC1. 

Figure 2:  Potential Error In User benefit MEASURE Associated with OMITTING INDUCED TRAFFIC.


In this example, the exclusion of induced traffic from the analysis would lead Total User Benefits being overestimated, as the error associated with the estimate of benefit to Base and Re-Assigned traffic (C1FGC2) is greater than the error associated with the Induced traffic (DEF).  The relative size of these errors is, however, dependent upon the characteristics of the transport market (depicted by the shapes of the demand and supply curves in Figure 1 and Figure 2, and the net effect can go either way.




4                   Modelling Induced Traffic

The complexity of the demand forecasting process and the scale of the data requirements vary when forecasting the different categories of traffic (see Table 1).  Base traffic is the least onerous form of traffic to model, as simple traffic count and origin-destination data in the existing situation provides all the information required.  Modelling re-assigned traffic is now also a standard process for which off the shelf software exists (e.g. HDM4 for road based traffic).  If only Base Traffic and Re-assigned Traffic is considered within the appraisal the implicit assumption is that all origins, destinations, time of travel choices and mode of travel choices remain fixed.  Such an approach is known as the Fixed Trip Matrix (FTM) approach, as the matrix of origin-destination demands is the same in the Do Minimum as in the Do Something.

The modelling of Induced Traffic is the most complex of all, as strictly speaking mode choices, destination choices, time of travel choices, changes in trip frequency and importantly land use changes all need to be forecast.  A consequence of Induced Traffic is that origin-destination demands will vary between the Do Minimum and Do Something.  Methods used to model Induced Traffic are therefore termed Variable Trip Matrix (VTM) approaches.  Without doubt VTM (or induced traffic) modelling can be complex, but as discussed in the previous sections can also be essential.  In practice, however, when modelling induced traffic a range of modelling approaches are available that include both simple methods and more complex methods.  These are set out below:

·                    The simple elasticity approach, where all responses are subsumed into a single elasticity.  Different elasticities can be used for different journey purposes (e.g. freight related travel, travel in the course of business and non-working time travel).  Such an approach only requires data from the mode affected by the project (e.g. rail travel data for a rail project or road travel data for a road project) and is most applicable to a situation where an existing network is being enhanced through improved quality of service (e.g. increased frequency of train services, or upgrading of a road from single to dual carriageway);

·                    The inclusion of a single behavioural response (such as mode choice).  Typically, such an approach is adopted when forecasting the demand for improved public transport services, such as guided bus or Light Rapid Transit (LRT), where some of the demand will be extracted from competing modes (road and other public transport services).  Such an approach requires travel data on all modes of travel being considered; and

·                    A staged model (also known as a four stage model) that incorporates all behavioural responses.  This is the most complex form of transport model and can be expensive in terms of both data and resources in development (calibration and validation) and operation (long model run times).  However, models such as these may be needed for large projects in congested urban areas (e.g. new metro systems or new urban motorways).

Recent computing advances have also allowed the operationalisation of Land Use and Transport Interaction (LUTI) models and Computable General Equilibrium (CGE) models which not only model the impact on travel but also the impacts on land use, the labour market and property rents.  Such models, however, represent the state of the art and their use is currently relatively limited.  They are discussed further in the Note Projects with Significant Restructuring Effects [Link].  Further information regarding the calculation of induced traffic demand forecasts and errors associated with such calculations is also contained in the Note Demand Forecasting Errors [Link].

A final key issue associated with modelling induced traffic and capturing the benefits of it is that the model area, for both the modelling exercise and the cost benefit analysis, need to be sufficiently large to ensure that all benefits or costs are included within the appraisal.  This may seem an obvious statement to make, but in situations where projects have international consequences, such as transit traffic in a land locked country, such issues may be overlooked.  The Note Demand Forecasting Errors [Link] also contains a small discussion on the definition of the model area.

In constructing defensible models, it is always advisable to validate the model against the existing situation (see Note Demand Forecasting Errors [Link]).  Sometimes it is also useful to seek out evidence from comparable situations elsewhere, though caution should be exercised when considering the transferability of travel behaviour particularly between countries.  Peer review of the demand forecasts by appropriately experienced individuals will add further to their credibility.


5                   How to calculate user benefit in the presence of induced traffic

In the majority of situations the calculation of the user benefit associated with induced traffic is relatively straight forward and utilises the Rule of the Half (RoH) methodology.  This method is presented in the Framework [Link] but for convenience the formula is also reproduced in Box_2.  It should be noted that this method (and all other methods) require reliable demand forecasts of the volume of induced traffic.  Such demand forecasts can be quite complex to obtain. 


Box 2: Rule of a Half

User Benefitij = ½(Cij0-Cij1)(Tij0+Tij1)

Where:    Cij0 is Cost between origin (i) and destination (j) before investment

               Cij1 is Cost between origin (i) and destination (j) after investment

               Tij0 is Demand between origin (i) and destination (j) before investment

               Tij1 is Demand between origin (i) and destination (j) after investment


Operationalising the Rule of Half (RoH) is a relatively straight forward procedure, though the following properties of the RoH should be borne in mind:

·                    User benefits should be calculated on a matrix basis and not a link basis.  That is user benefits must be calculated on an origin-destination (i-j) pair basis, implying the cost used in the calculation is the travel time, vehicle operating costs and money costs required to travel between origin (i) and destination (j) by mode (m).  This contrasts to the Fixed Trip Matrix (FTM) situation, i.e. no induced traffic, where user benefits can be calculated for each link in the network and summed, instead of on an i-j pair basis;

·                    User benefits can be calculated separately for each mode and time period, even in situations where demand switches between modes and time periods.  This is a particularly useful property of the RoH as often the demand forecasting process will use different models to represent different time periods and modes;

·                    User benefits associated with the individual components of generalised cost (e.g. time, vehicle operating costs and money costs) can be calculated and summed to give total user benefits:

where:     H is the travel time per trip in hours,

               VoT is the value of travel time in currency units per hour.

               VOC is the vehicle operating costs for motorised transport in currency units per trip

               U is the user charge in currency units per trip

Subscripts for origin (i), destination (j), mode (m) and for different trip purposes (which would carry different values of time and operating cost) have been omitted for simplicity.


·                    User benefits/disbenefits associated with money costs (e.g. road tolls and fares), when calculated under the RoH and variable demand, do not net out with changes in the fare revenue element of the producer surplus calculation (i.e. they are not transfer payments); and 

·                    Technically, there is no unique attribution of user benefits between modes or indeed between origin-destination pairs, because it is not possible to identify an individual on the do-something network and trace back to find out what mode he/she used in the do-minimum.  


Off the shelf software exists to calculate network wide user benefits using a matrix based Rule of a Half approach (for example the United Kingdom program, Transport User Benefit Appraisal (TUBA) [1]). 


Exceptions to the Rule of a Half

The Rule of a Half breaks down when the assumptions upon which the methodology is based are undermined.  The two principal assumptions are:

-                     The demand curve is linear; and

-                     Demand for travel exists in the before and after situation (by mode and time period).

The circumstances in which these assumptions may break down are set out below.  In each situation advice is given regarding the method that should be adopted for the calculation of user benefits.

Large changes in the generalised cost: The bigger the proportionate reduction in generalised cost brought about by a transport infrastructure project, the less reliable the linear approximation to the demand curve becomes.  The recommendation here is that, as a rule of thumb, if the project results in a >25% reduction in average generalised cost from origin to destination for trips using the project, this feature should be reported as part of the cost benefit analysis.  In such situations user benefits should be estimated using the method of numerical integration detailed in Nellthorp and Hyman (2001) [2] and attached as Annex 1 to this Note.  This approach requires repeated model runs to sketch in the unknown part of the demand curve and is a pragmatic way of estimating the shape of the demand curve.

New modes or existing modes become redundant: Introduction of completely new modes in the do-something scenario - for example, high speed rail, urban light rapid transit, or even a new conventional railway - where none exists in the do-minimum.  Alternatively, the removal of a mode (e.g. closure of a railway branch line) in the do-something where it exists in the do-minimum.  In such situations either the “before” or the “after” cost does not exist, so the Rule of the Half breaks down.  Instead of using the Rule of a Half, user benefits should be calculated through the method of numerical integration as set out in Nellthorp and Hyman (2001) [2] and attached as Annex 1 to this Note.  Again numerical integration is a simple pragmatic solution rather than the theoretically best approach – which requires the ability to integrate the demand function – which is often more complicated to do.

There is no existing demand: such projects would include projects that break new ground or open up areas for development such as a new freight railway or low volume rural roads and feeder roads.  As with a new mode, in such situations the “before” cost does not exist, so the Rule of the Half breaks down.  If the Rule of a Half is applied in such circumstances it will invariably result in an overestimation error.  However, in some situations (notably producers who are attracted to enter and serve a “world” market for their product which involves a given fixed price) the rule can lead to underestimation (see Gannon (1998) [3]).  Numerical integration once again offers an option for the calculation of user benefits (see Annex 1), however, in such situations it maybe more appropriate to estimate some of the wider economic impacts associated with the economic (re-)generation associated with transport projects.  This issue is also discussed in the Note Low Volume Rural Roads [Link].

Significant land use changes and/or structural economic shifts: this special circumstance and its treatment are discussed in detail in the Notes Low Volume Rural Roads [Link] and Projects with Significant Expected Restructuring Effects [Link].


6                   Further Reading


[1] Department for Transport, Transport Users Benefit Appraisal (TUBA), Integrated Transport Economics and Appraisal, Department for Transport, UK, [Available online at]


[2] Nellthorp J and Hyman G (2001), ‘Alternatives to the RoH in Matrix based Appraisal’, Proceedings of European Transport Conference 10-12 September 2001. London: Association of European Transport.


[3] Gannon, C. (March 1998), Evaluation of Generated Traffic Benefits: A Note on Qualifications for the “Rule of One-Half”.  TWU Department, World Bank, Washington DC.


[4] Mackie, P.J.(1996), Induced Traffic and Economic Appraisal.  Transportation 23: 103-119


[5] SACTRA (The Standing Advisory Committee on Trunk Road Assessment) (1994) Trunk Roads and the Generation of Traffic. London: The Stationery Office.


[6] Department for Transport, UK (2000), Guidance on the Methodology for Multi-Modal Studies (GOMMMS), Volume 2, Appendix F (Transport Cost Benefit Analysis Background Material).  [Available online at]