The Department for Transport’s National Transport Model (NTM) was first constructed two decades ago and has subsequently undergone a number of phases of development. The main function of the model has been to provide projections of travel demand as the basis for justifying investment in the road network. The model has also been used to project future carbon emissions, to inform the Department’s Transport Decarbonisation Plan, as well as to explore the impact of technological developments such as electric vehicles.

An account of the latest version, effectively a new model known as NTMv5, was released recently in the form of a 250-page ‘Quality Report’, oddly, two years after completion. NTMv5 is a spatially detailed conventional four-stage transport model structure, iterated so that congestion feeds back into demand. The model has been implemented using the standard commercial software, PTV Visum. The intention is that the model should be transparent to external stakeholders, a very welcome development given the opacity of previous versions of the NTM. The complexity of the model means that a single run takes around ten hours, with a number of iterations needed to achieve convergence of outcomes.

However, there are some notable limitations to the model. There is no detailed treatment of public transport capacity. Car ownership data derives from a separate model, which has not been updated. And the primary source of growth of travel demand is the DfT’s National Trip End Model data set that projects expected changes in demography and land use, which are problematic of account of uncertainty of economic growth, population growth and distribution, and planning policy.

A number of potential applications of the model have been identified, of which the most immediate is the preparation of new national road traffic forecasts. Also recognised is a need to project future transport carbon emissions, and for the analysis of packages of road schemes at national level, including value for money.

The purpose of the succession of NTM versions has been to support the traditional ‘predict and provide’ approach to road investment. This viewpoint persists in the latest version where the stated rationale for analysis of packages of road schemes is to identify ‘gaps in the network… where the road capacity in future may be insufficient, leading to unacceptable rises in congestion and journey times.’ (section 2.4.2). Yet we do not adopt that approach when considering urban roads, and the scope for enlarging peri-urban motorways at acceptable cost by converting the hard shoulder to a running lane is now problematic on account of public concerns about safety. Besides, the scale of induced traffic has been persistently under-estimated in traffic modelling, so the aim of avoiding unacceptable congestion seems naïve, even before addressing the Net Zero objective.

The model builders struggled to treat the complexities of urban traffic. It was accepted that a full link-based modelling of urban road capacity and related journey time responses could not be achieved, and therefore a simplified approach had to be applied. This involves assuming general fixed speeds on urban networks for the Base Year, which were reduced over time based on assumed growth of demand. (sections 4.7 and 11.4). This simplification has implications for projections of traffic in London, as recognised by the peer reviewers.

Peer Review

The DfT has published a Peer Review and an Audit of NTMv5. The 120-page peer review, led by the seasoned practitioners John Bates and Ian Williams, drew attention to a number of apparent shortcomings in the methodology (too technical for me to appreciate sufficiently to offer comment). These led to counterintuitive results when sensitivity tests were run, notably for London.

The reviewers advise caution in application of the model, primarily due to the focus of the NTMv5 being on the more strategic highway network, whereas many of the potential applications focus on urban travel policy and public transport interventions. In particular, the reviewers are critical of the treatment of urban traffic, observing that the assumed relation between traffic speed and demand growth lack validity, and that the range of policies aimed at reducing urban car use are not taken into account. Besides, it is noted that the DfT’s car ownership model has not recognised that ownership in dense urban areas has been declining for many years in response to increasing population density, notwithstanding rising incomes.

The reviewers find that for London, the model results are not convincing. The observed car (driver + passenger) trip mode share is 38% from the National Travel Survey in 2015/16, whereas that in the model in 2015 is 50%. Moreover, the model projects a future gain of car share, whereas over the period 2005-16 a major decline of 5.6% was observed (para 4.3.5). The reviewers concluded that the model could not be safely used to examine policies that relate specifically to London, and query whether this relates more generally to rapidly growing dense urban areas across England. They took the view that the model should be suitable for use in forecasting the growth of road traffic in most areas other than those adjacent to or within major urban areas (section 6.3.24), which is a pretty major qualification.

Audit

The 260-page audit of NTMv5, carried out by consultants Arup and AECOM, drew attention to a number of shortcomings in both documentation and substance, including that some of the model components and tools used to process the data are not owned by the Department, which limited access to some of the key processes and data used in model development – not consistent with the aim of transparency to external users. The auditors advised that users of model outputs should be cautious because of problems in reaching convergence to a stable outcome as the model is run through repeated iterations, a concern also of the peer reviewers.

What next?

The NTM documents recently published are two years old. No doubt, further development of the model has been taking place to respond to the issues raised in peer review and audit. In its Transport Decarbonisation Plan published last July, the DfT stated its intention to review the National Policy Statement on National Networks, the basis of strategic planning of road and rail investment, and to update the forecasts on which it is based. NTMv5 will presumably be used for this purpose. Yet the modellers will be stretched to meet the divergent needs of their client policy makers, between bullish forecasts of travel demand to justify continued infrastructure investment and bearish projections of transport carbon emissions. Given the uncertainties of the model illuminated by peer review and audit, it will be hard to be confident about the validity of carbon forecasts out to 2050 and 60-year investment appraisals.

While the DfT’s intention to make NTMv5 available for use beyond the Department is praiseworthy, this seems problematic in practice. Doubtless the large transport consultancies could master the software and data, but given their complexity, clients would need deep pockets to fund the work. That would rule out non-government bodies that might want to challenge particular schemes. Regional transport undertakings have their own bespoke models. I am not aware of any academics who would be likely to buy into the NTM, a situation unlike national energy modelling where government and a substantial group of university researchers work with the same model. The DfT would be well advised to support academic researchers and others wishing to use NTMv5 to explore a range of policy scenarios.   

This blog was the basis for an article in Local Transport Today of 11 March 2022.

The Office of Rail and Road has extensive responsibilities for regulating the largely private sector rail industry but quite limited oversight of public sectors roads. The Department for Transport is planning its third Road Investment Strategy investment programme (RIS3). The ORR has been consulting on its role in relation to RIS3. Essentially, the ORR sees its role as ensuring that National Highways (formerly Highways England) achieve value for money in implementing the DfT’s investment priorities.

The ORR consultation document states that it is not the role of the ORR to set roads policy or determine investment priorities. However, it is a shortcoming of the ORR’s approach that it does not consider to what extent the investments agreed by government achieve the benefits to road users that are expected. This is a major gap in public oversight.

The National Audit Office from time to time evaluates benefits to users of road investment, for instance its 2019 report on improvements to the A303. But NAO oversight is occasional, not systematic.

Detailed analysis of the outcomes of road investment may show major discrepancy between forecast and outturn, for instance for widening the M25 between junctions 23 and 27. One general explanation is the underestimation of the scale of induced traffic . Induced traffic reduces travel time savings, supposed main economic benefits of investment, which is why transport models tend to underestimate its magnitude.

One source of induced traffic is the rerouting of local trips, such as commuting, to take advantage of faster travel on widened motorways, pre-empting capacity intended for business users and so undermining the economic case for widening. This is likely to be a general phenomenon in or near areas of high population density, where the strategic road network comes under greatest stress, and where the case for additional capacity seems strongest.

More generally, average travel time, as determined in the National Travel Survey, has remained essentially unchanged for half a century, during which time huge sums have been invested in road infrastructure justified by the saving of travel time. Travel time savings are short-run. In the longer run, over the greater part of the life of the assets, the main benefit of investment that allows faster travel takes the form of increased access to people and places, opportunities and choices.

All in all, there is reason to suppose that the outcomes of road investments may be substantially different from that forecast by the traffic and economic models in use, and that road users are not benefiting from investment in new capacity to the extent intended. The ORR should take on the task of ensuring that road investment appraisal methodologies are fit for purpose.

The Government published its Integrated Rail Plan for the North and Midlands (IRP) in November. Despite headline investment worth £96bn, public reception was mostly unfavourable. Expectations had been excessively raised. Cities that failed to gain hoped for improved services and new stations spoke up more loudly than the winners of this apparent lottery. Huw Merriman MP, chair of the Commons Transport Committee, put well ‘the danger in selling perpetual sunlight and then leaving it for others to explain the arrival of moonlight.’

What has not previously been remarked is the absence of any supporting economic analysis to justify the investment choices of the IRP. This is in marked contrast to the succession of documents justifying HS2, with benefit-cost ratios that declined over time as the capital costs steadily rose. One problem with applying the DfT’s standard approach to economic appraisal, for which the main benefit is travel time saving, is that it is silent on the distribution of economic benefits, a serious disadvantage for a project whose strategic purpose is to boost the economies of the cities of the North and Midlands.

The DfT has at long last recognised the problematic nature of theoretical time savings. The IRP states: ‘Over the last 50 years the time people spend travelling has remained relatively constant, though distances travelled have increased…. Overall, people have taken the benefits of better transport links as the ability to access a wider range of jobs, business and leisure opportunities, rather than to reduce total time spent travelling.’ (para 2.8)  

It is gratifying to find the DfT seemingly accepting an understanding of this reality, to which I have been drawing attention for many years. Nevetheless, there is a footnote appended that suggests the Department doesn’t yet quite get it: ‘Noting that the use of estimated time savings as the basis for quantifying economic impact remains robust.’

If time savings are a ‘robust’ measure of economic impact, why was the standard cost-benefit approach to investment appraisal not employed? The answer, as the IRP recognises, is that ‘rail schemes in the North are at increased risk of being considered poor value for money when applying conventional cost-benefit analysis. This is driven in part by smaller city populations in the North, different travel patterns, as well as the general high cost of building rail infrastructure.’ (para 3.59). So conventional cost-benefit analysis, as prescribed in the thousand-pages of the DfT’s Transport Analysis Guidance (TAG), is not fit for the purpose of appraising rail investments. The main problems are the absence of observed time savings in the long run, silence on the spatial distribution of benefits and on the value of consequential property development and economic regeneration.

In developing the IRP, the Government has been guided by the analysis of rail investment options carried out by the National Infrastructure Commission (NIC), which concluded that prioritising regional links appears to have the highest potential economic benefits overall for cities in the Midlands and the North and would improve many of the currently poorest services. Improving East-West links are higher priority than North-South routes. The Government agrees with the NIC’s analysis that there are opportunities to better serve existing city centres and wider city regions for greater economic benefit, and better integration with existing transport networks. Given constraints on public expenditure, the eastern leg of HS2 between the East Midlands and Leeds will not now go ahead.

To reach its conclusions, the NIC developed a novel multi-criteria analytical approach that attributed monetary values to improvements in productivity in city centres, benefits from connecting people to city centres, and environmental impacts. In addition, estimates were made of improvements to connectivity from faster journeys and of the benefits from unlocking investment in land around stations. In essence, this approach replaces traditional transport user benefits, which mainly take the form of a reduction in time costs, with estimates of the benefits of increased productivity and consumer amenity arising from higher city densities made possible by urban transport investment.

The NIC analytical approach was developed for consideration of a portfolio of rail investments. This is very welcome since there is an undoubted need to move beyond appraisal of individual schemes to view the benefits of whole programmes of infrastructure investments. In a subsequent blog, I will consider the applicability of this approach to road investments.

This blog was the basis for an article in Local Transport Today of 14 January 2022.

The Department for Transport’s Decarbonisation Plan projects the decline of domestic transport greenhouse gas emissions from the present 120 MtCO2e a year to approaching zero by 2050 (see figure above). There is considerable initial uncertainty about the pathway but the range of projected outcomes narrows over time as the proportion of zero emission vehicles increases. The modelling is largely based on the Department’s long-established National Transport Model. Although little detail is provided, there are headline numbers for cumulative emission reductions over the period 2020 to 2050.

For cycling and walking, the projected savings from investments and policy initiatives are put at 1-6 MtCO2e, a notably wide range. For cars and vans, the savings are estimated to be 620-850 MtCO2e, a proportionately narrower range, reflecting greater confidence in the impact of policy to phase out the internal combustion engine. What is striking is the relatively tiny decarbonisation contribution expected from increases in active travel, at best one percent of that from car decarbonisation. This is surprising, given the prominence in the Plan of the intention to promote active travel, including expenditure of £2 billion over five years. This looks like a case of virtue signalling by DfT, wanting to be on the side of the angels.

Counting on minimal decarbonisation benefit from more cycling is consistent with the evidence from Copenhagen and other European cities that you can get people off the buses onto bikes but that it is difficult to get them out of their cars. In any event, 80% of car carbon emissions arise from trips of more than five miles, implying limited scope for savings from mode switching from car to active travel.

More generally, the DfT’s Plan relies very largely on technological innovation to achieve net zero for domestic transport by 2050. Others see a need for significant reduction in travel demand, including the Climate Change Committee (CCC) in its Sixth Carbon Budget report of December 2020, which envisages 20% of transport emission reductions from reduced demand. The CCC recommended commitment to 78% reduction in overall emissions by 2035 compared with 1990 levels. This was accepted by the government and is to be implemented through sector plans, of which the Transport Decarbonisation Plan is the first. 

The question of the need for travel demand reduction is crucial, given this could be both unpopular and difficult to achieve. One can see why the DfT might shy away from measures to reduce demand, such as significant increases in the cost of travel. But aside from the political sensitivities, could such measures be justified on the basis of existing models that generate conflicting conclusions and whose validity is unproven?

The National Transport Model is an elaborate model of the surface transport sector. Other relevant models are essentially energy models of the whole economy, including the transport sector. All these models are complex and opaque, with many parameters whose magnitude requires professional judgement. Given the timescale to 2050, it is not possible to validate models by comparing forecast with outturn. Models are therefore prone to optimism bias, whether unconsciously because modellers want to please their clients, or consciously in aid of achieving some higher purpose.

Greater transparency of the National Transport Model would allow us to understand whether there has been undue optimism about the prospects for decarbonisation by technology. However, such transparency seems unlikely. The DfT has always resisted allowing others to use its model on the grounds that its components employ proprietary software developed by consultants. Not that this is unique. Most transport modelling utilises proprietary models owned by consultants. This contrasts with practice elsewhere.

The Treasury’s model of the UK economy has been available for external use for many years. The Department for Business, Energy and Industrial Strategy has developed its energy modelling in close collaboration with academia and plans to increase transparency. Climate modelling is an international, open, collaborative effort that feeds into the findings of the Intergovernmental Panel on Climate Change. The epidemiological modelling of the coronavirus pandemic, which has informed decisions on lockdowns and vaccine deployment, has been carried out not within government, but by university modellers, collaboratively and transparently.

Transport modelling needs to move on, to become transparent and collaborative rather than opaque and proprietary. More effort needs to be devoted to validating models by comparing forecast with outturn where that is possible, for instance over the initial years following the opening of a new element of infrastructure. For the period through to 2050, the best that can be done is for modellers to run their models on common assumptions, to understand why forecasts differ, and then to vary assumptions to test the sensitivity of forecasts to bias, both optimism and pessimism, whether concerning technological innovations or behavioural change.

We need an informed consensus from the modellers of transport decarbonisation to inform the development of policy.

The text above was published in Local Transport Today edition of 18 October 2021. Since this piece was drafted, two further relevant publications have become available.

CREDS, the Centre for Research into Energy Demand Solutions, a consortium of university groups, published a substantial report on the role of energy demand reduction in achieving net zero, including the energy associated with the transport system. The report concluded that the UK could halve its demand for energy by 2050, which would substantially ease the task of meeting that demand with zero carbon emissions. For transport, an ambitious set of assumptions were made, including that single occupancy car use becomes socially unacceptable and that the car fleet is reduced substantially. The model employed represents the whole energy system and is known as UK-TIMES. The model and assumptions are set out in some detail and the code has been published, which is very creditable, although it would take a professional modeller to fully appreciate the content.

The government has just published its Net Zero Strategy. This covers the whole economy including transport, although little is added to the previously published Transport Decarbonisation Plan, which placed minimal reliance on changes in travel behaviour. A technical annex sets out the modelling and assumptions used to justify the pathway to net zero by 2050, again employing the UK-TIMES model. For transport, the only behavioural change assumed is that the share of journeys in towns by active travel increases from 42% in 2019 to 55% in 2035. The trajectory of emission reduction for domestic transport on page 154 is similar to that shown in the Department for Transport decarbonisation plan, although the modelling framework used is different.

It is evident that the emission consequences of a wide range of travel behavioural change possibilities are being projected using different kinds of model. The recent publications reinforce the case for transparency and collaboration amongst the modellers.

A further addendum, November 2021

DfT has recently published papers about its new version of the National Transport Model, which is based on standard industry software and is intended to be available for use outside the Department. This is a welcome development that will make the model more transparent, although its complexity means that it is still quite opaque. However, the carbon modelling discussed above was derived form the older version of the NTM.

This blog post is the text of an article in Local Transport Today.

Cycling is widely advocated as a desirable means of travel – healthier, cheaper, more environmentally friendly and barely slower than the car for short-to-medium length trips. The Government seeks a step-change increase in cycling with £2 billion new funding, as a cost-effective way of reducing transport carbon emissions.

Certainly, there is substantial scope to increase cycling by investment in better infrastructure, witness Copenhagen with dedicated cycle lanes on all major roads, where 28% of all trips are by bike, compared with 2.5% in London. So when, at the outset of the pandemic, the Mayor of London announced his ambition to increase cycling by tenfold, you could see that this should be possible with the requisite investment. However, when you’re in Copenhagen, you are aware of the considerable amount of general traffic (and viewing Scandi noir crime dramas set in that city, you see very few of the characters using a bike). In fact, with 32% of all trips by car, Copenhagen is only slightly less car-dependent than London with 35%.

Aside from cycling, the other big difference between these two capital cities is that public transport use in Copenhagen is only half that of London, 19% versus 36% of trips. This indicates that you can get people off the buses onto bikes, but that it is much harder to get them out of their cars, even in a small, flat city with excellent cycling facilities where almost everyone has experience of safe cycling. Yet we don’t want to diminish the use of buses, which are an efficient means of moving people in urban areas, the diesel engines of which can be replaced by electric or hydrogen propulsion. Fewer bus passengers mean less fare revenue and less frequent services.

Data for other European cities indicate that Amsterdam is similar to Copenhagen, with 32% of trips by bike and 17% by public transport. In marked contrast, both Zurich and Vienna have excellent public transport responsible for 40% of trips, with cycling accounting for only 7-8%. More generally, while the pattern of urban travel reflects both local geography and history, we don’t find cities in developed economies with high mode shares of both cycling and public transport.

In seeking to reduce transport carbon emissions, we should be careful not to underestimate the attractions of the motorcar, which is useful for longer journeys and for shorter trips with less sweat, for carrying people and goods, including child seats and the stuff left permanently in the boot. The car is well-suited for meeting our needs for access to people and places, for door-to-door travel where there is road space to drive without unacceptable congestion delays and the ability to park at both ends of the trip.

But there is more to car ownership than the ability to go from A to B. The growth in popularity of SUVs suggest that there are feel-good factors that motivate purchase of these costly vehicles (it would be interesting to see the findings of the market research carried out by the car manufacturers, regrettably proprietary). The fact that cars are generally parked for 95% of the time is a good economic argument for car sharing. But conversely, this also indicates the value we place on individual ownership, to have vehicle available when we want it, a vehicle that reflects our personal consumer preferences. Cars are not unique in this respect. My washing machine sits unused more than 95% of the time. I could share with others at the laundrette, but it’s more convenient to have my own.

Car sharing in its various forms is advocated as a means to reduce car use, road traffic congestion and carbon emissions. Sharing has been facilitated by online digital platforms, which have been transformative of many aspects of the economy. For travel, we have the disruptive impact of ride-hailing as exemplified by Uber, and of online booking of trips by rail and air. By contrast, the growth of car sharing has been relatively slow, indicating the development of niche markets, with substantial replacement of private ownership looking unlikely.

Where road capacity limits car use in city centres, both public transport and active travel are attractive alternative modes. Agglomeration economics have led to increased population density in successful cities, which shifts travel away from the car. The growth of higher education in urban centres has contributed to reduced car use by young adults.  However, these trends may weaken post-Brexit and post-Covid. And while car use can be impeded in low traffic neighbourhoods in favour of cycling and walking, the aggregate impact may not be great.

We need to be careful to avoid optimism bias when projecting the impact of measures to reduce transport carbon emissions. The models that are used for this purpose are complex and opaque, with many input assumptions and parameters to be specified. Optimism bias arises when modellers make choices, consciously or unconsciously, that tend towards achieving a strategic purpose. Yet optimism bias leads to outcomes that fall short of those that are forecast. 

It is now part of the culture of transport planning to place emphasis on the opportunities for promoting cycling. But caution is needed. When addressing the impact of changing mode share, attention should be paid to the modes from which the shift to cycling is expected. For instance, the well-established Propensity to Cycle Tool, which assesses the potential to increase the amount of cycling, assumes that commuters are equally likely to shift to cycling from any prior mode. However, the evidence from Copenhagen and elsewhere indicates that a shift to cycling from public transport is much more likely than from car use, which would substantially reduce the carbon reduction benefits assumed from boosting cycling.

If optimism bias informs assumptions about mode shift from cars to bikes, or about the scope for car sharing, then disappointment is likely to ensue.

Below are the main points and implications of my analysis of the outcome of widening of the M25 motorway between Junctions 23 and 27, published as ‘Economic benefits of road widening’, Transportation Research Part A, 147, 312-319, 2021. Abstract available at https://www.sciencedirect.com/science/article/abs/pii/S0965856421000872 Manuscript available from david.metz@ucl.ac.uk

  • The M25 motorway was widened between Junctions 23 and 27 as part of the Smart Motorway investment programme implemented by Highways England. Detailed traffic monitoring reports were published before the scheme was opened and for three years afterwards.
  • There was some increase in traffic speeds at Year One after opening, compared with Before opening, but this gain was lost subsequently account of increased volumes of traffic. At Year Three, average daily traffic was up by 16% compared with Before, and up 23% at weekends. This contrasts with an increase of 7% for regional motorway traffic growth.  
  • The conclusion of the Year Three monitoring report states: ‘These results show that increases in capacity have been achieved, moving more goods, people and services, while maintaining journey times at pre-scheme levels and slightly improving reliability.’ However, this could not have been the basis of the investment case, which in general suppose that travel time savings are the main benefit of transport infrastructure investment. Accordingly, reports of the traffic and economic modelling were obtained; these utilised the long-established SATURN and TUBA models.
  • The traffic model projected increased traffic volumes and speeds for the scheme opening year, comparing the ‘do something’ investment case with the ‘do minimum’ case without the investment. However, the increase in traffic volume was less than the observed outturn and the increase in speed forecast failed to materialise beyond the first year after opening.
  • The modelled economic benefits derived very largely from time savings for business users. There were also time savings for local users, commuters and others, but these were almost entirely offset by increased vehicle operating costs. This was the consequence of local users rerouting trips between unchanged origins and destinations to take advantage of short journey times made possible by diverting to the motorway, travelling somewhat greater distances.
  • The benefits forecast for business users were the main input to the economic appraisal that generated a benefit-cost ratio of 2.9, which was the basis for the investment decision. However, the time savings benefits did not materialise beyond the first year after opening, on account of the additional traffic above forecast.
  • The nature of this additional traffic cannot be deduced from the traffic monitoring. It is likely that much, possibly most, comprises local trips rerouting, of no net economic benefit; indeed, these trips would be of negative benefit on account of the additional externalities (carbon etc) arising from the increased distance travelled. The outturn BCR must be much less than the forecast 2.9, possibly even negative.
  • This M25 case is likely to be typical in that the Strategic Road Network comes under greatest stress in or near major urban centres where local traffic competes for carriageway with long distance users. Highways England has 10 smart motorway schemes in its current investment programme, with an average BCR estimated as 2.4. This likely reflects considerable optimism bias in the modelling.
  • The modelling to support decision making distinguishes between different classes of road user, yet the traffic monitoring does not allow such a distinction. The monitoring is therefore of limited use in refining the models and countering optimism bias. What is needed is monitoring of representative samples of road users over time to see how their travel behaviour changes as the result of the road investment. Such longitudinal studies, as they are known, are common in the areas of health and social sciences, but almost unknown for travel and transport.

The House of Commons Transport Committee is holding an inquiry into major transport infrastructure projects. Written evidence has been published. My evidence is set out below.

This submission is concerned with the effectiveness of the Government’s decision-making and appraisal processes for transport infrastructure projects, a subject on which I have researched and published in peer-reviewed journals.

Main points

  • The standard approach to the economic appraisal of transport investments, based largely on the value of time savings, does not reflect reality. An independent review of the methodology would be desirable. 
  • The value of transport investment lies in better access to people and places, making possible more opportunities and choices. Improved access changes the built environment, the consequences of which can be valued.
  • Digital navigation (satnav) is affecting traffic flows, and thus the outcomes of road investment, in ways that are little understood. A study is needed.

Time is not saved

The Department for Transport (DfT) has a well-developed methodology for the appraisal of transport infrastructure investments, set out in considerable detail in its Transport Analysis Guidance (TAG, formerly WebTAG, reflecting the pioneering effort to make the material available via the internet). The Guidance is consistent with the Treasury’s Green Book, and indeed appears to be regarded as an exemplar of good practice in economic appraisal in the public sector. However, the Green Book does not deal with the specifics of transport investment, so that the recent changes to it, while welcome, do not bear on what follows.

The main economic benefit supposed to arise from investment in transport infrastructure is the saving of travel time. Accordingly, the DfT has commissioned considerable analysis designed to attribute values of time to different classes of user of the transport system, according to mode and purpose of travel. Travel time savings typically amount to 80% of overall economic benefits that are set against capital and other costs in the cost-benefit analysis employed to help reach investment decisions.

Average travel time has been measured regularly in the National Travel Survey (NTS) and has barely changed over almost fifty years, at close to an hour a day for travel by all modes except international aviation. So, there is a paradox in that huge past investments in transport infrastructure have been justified by the expected value of travel time saved, which yet is not apparent in any change in travel time averaged across the population.

The explanation is that travel time savings are quite short run. In the long run, people take the benefit of faster travel to travel further, to gain access to more people and places, to have more opportunities and choices. Thus, while average travel time remained constant, the average distance travelled increased from 4500 miles a year in the early 1970s to around 7000 miles in the late 1990s. The economic benefits to users of transport infrastructure investment therefore are not time saved for more work or leisure, but rather relate to enhanced access to, and choice of, jobs, homes, schools, shops and other services.[1]

Such access is subject to diminishing returns. For instance, 80% of urban residents in Britain have access to three or more large supermarkets within 15 min drive, and 60% have access to four or more, a level of choice likely for most to remove the need to travel further for yet more choice[2]. On the other hand, access increases with the square of the speed of travel, since what is accessible is defined by the area of a circle whose radius is proportional to the speed of travel. The combination of access increasing with the square of travel speed yet subject to diminishing returns means that travel demand to achieve access saturates, that is, it ceases to grow.

Such demand saturation, also known as market maturity, is of course a standard feature of consumer markets generally and it is to be expected for daily travel. The finding of the NTS that the average distance travelled has not increased over the past twenty years is consistent with this expectation. So rather than planning for ever more transport infrastructure investment based on time savings, we should limit investment to meeting specific access deficiencies in what is generally a mature transport system. This points, for instance, towards investment in urban rail that can increase economic density and hence agglomeration benefits, as the National Infrastructure Commission has argued[3], rather than on inter-urban roads where the benefits are overstated, as the following case study illustrates.

In 2015 the London orbital M25 was widened from three to four lanes in each direction between junctions 23 and 27, part of the so-called ‘Smart Motorway’ programme of Highways England, with detailed monitoring of traffic volumes and speeds before and for the first three years after opening. The growth of traffic was substantially greater than on major roads in the region and greater than forecast in the transport modelling used to justify the investment. The model predicted a significant increase in traffic speed, which generated travel time savings contributing to a benefit-cost ratio (BCR) of 2.9, which represented high value for money. However, beyond the first year, no increase in traffic speed was seen on account of the additional traffic. The evidence suggests that this is due mainly to local users rerouting between unchanged origins and destinations to take advantage of shorter journey times via the motorway, while incurring greater fuel costs. The outturn BCR must be quite small.[4]

This M25 case is likely to be representative of much planned investment in new capacity on the Strategic Road Network, which comes under greatest stress in or near urban centres where local traffic competes for carriageway with the long-distance users for whose benefit the investment is primarily intended. Rerouting to take advantage of new capacity is facilitated by the widespread use digital navigation (satnav) devices that offer routes with the shortest time.

At present, optimism bias in modelling means that traffic growth is underestimated and time savings overestimated. Monitoring of traffic flows before and after opening is too crude a measure to understand the consequences of the investment for the different classes of road user. Accordingly, we need to monitor the changes in travel behaviour of a representative sample of users, employing the travel diary technique as used for the National Travel Survey. This would allow transport models to be better calibrated, such that changes in access could be identified and valued, and externalities (carbon emissions, pollutants etc) that are related to vehicle-miles travelled better estimated. In particular modelling needs to take account of the impact of digital navigation on traffic on the road network.

Built environment is changed

The focus on travel time savings in the standard approach to appraisal means that the impact of transport investment on the built environment is not properly taken into account. Consider a proposal to construct a bypass around a village, motived by concerns about the local environmental impact of traffic. The economic case would be based largely on the value of travel time savings from a faster route. However, a bypass may make land more accessible for development, for instance for housing, subject to decisions of the planners and the prospective return to developers. A bypass scheme with housing is clearly different from one without, as regards both traffic and economic benefit. The standard approach to appraisal disregards the benefit of new housing when estimating the BCR on the grounds that this would double count the user benefits, which might be shifted to others such as land owners but which would not change in overall magnitude. In reality, the impact of the scheme with housing is very different from that without and they need to be appraised separately.

More generally, the real-world outcomes of transport investments depend on decisions by planners and developer. It has been attractive for the DfT to operate in a silo, disregarding changes in land use, initially on grounds of simplicity that were perhaps justified in the heyday of motorway construction. But now that we have a mature network of transport infrastructure in place, with only fairly marginal increases feasible on account of the high cost of civil engineering work, we need to focus on the benefits of new schemes beyond the traditional user benefits. Decision-making needs to be tripartite, involving planners, developers and transport authorities.

The broad objectives of investment in transport infrastructure are threefold: to stimulate economic growth; accommodate population growth; and mitigate environmental harm. Accordingly, we need an approach to appraisal that helps reach investment decisions relevant to these objectives, or whatever more specific versions may be decided by those holding devolved budgets. Changes to the built environment need to be recognised explicitly since they are important to achieving objectives, whether to make sites accessible for new housing or for business expansion. Moreover, changes to the built environment are spatially located, whereas time savings are not, yet location of benefits is very relevant to investment decisions. For instance, the economic case for HS2 was based largely on benefits to users of the new route and was silent on spatial distribution, whereas the strategic objectives were concerned to rebalance the economy in favour of regions beyond London[5].

An innovative approach to decision-making has been developed by the National Infrastructure Commission for its recent assessment of rail needs for the Midlands and the North[6]. This focuses on the way in which improved rail services can increase the effective density of city centres, which has long been recognised as boosting the productivity of businesses from agglomeration benefits through more efficient labour markets, better supply chains and enhanced knowledge sharing. The Commission has extended this analysis to capture the consumption impacts of agglomeration through access to increased amenities, which replaces conventional time saving benefits. Separately, the Commission has developed a property value uplift tool that allows the estimation of the impact of transport investment on property prices[7].

Digital technologies

The widespread use of digital navigation was mentioned above. The other important new technology is the digital platform, used by ride-hailing businesses to match demand to supply, as exemplified by Uber. Much is known about the impact of ride-hailing on traffic in US cities because the authorities are able to require provision of data as a condition of the companies’ operating licence. This has prompted the companies to volunteer data provision to help cities address urban transportation needs.

In contrast to ride-hailing, the providers of digital navigation are secretive. Little is known about the algorithms that calculate routes in the light of prevailing congestion, and how the guidance to users affects traffic flows generally. It is noteworthy that the DfT has recently revised its road traffic statistics to generate an increase of 26% of motor vehicle traffic on minor roads over the past ten years[8]. It is likely that this has been due in large part to use of digital navigation that makes minor roads usable to those without local knowledge.

The lack of appreciation of the impact of digital navigation is remarkable, given its likely influence on the functioning of the road network. The DfT’s Road Investment Strategy 2: 2020-2025 makes no mention of the use of satnav (although there is an illustration of a device on p38). Highways England created a ‘high-tech corridor’ on the A2/M2 in Kent to trial digital communications between roadside infrastructure and vehicles, to improve journey time reliability, yet this appears to pay no regard to the general use of digital navigation. The prospects for investment in such a publicly funded guidance system look poor, given the benefits provided without charge by the private sector providers of digital navigation.

A better approach to taking advantage of digital navigation to improve the operation of the road network would be through regulation. There is in fact legislation in place, but never used, to licence providers of dynamic route guidance. Licence conditions could include the provision of traffic information to road authorities and the avoidance of use of unsuitable roads.[9] Guidance to users is provided without direct charge, hence accommodating such licence conditions should not affect the business models of the providers, which depend either on selling direction-finding to retailers’ websites or mapping services to vehicle manufacturers.

Conclusion

The standard DfT approach to appraisal is no longer suited to decisions on investments in a mature transport system. The standard methodology has become vastly elaborate and misses the point that the benefit of investment is better access, which is seen as changes to the built environment. Decision-making needs to involve planners and developers as well as transport authorities. The National Infrastructure Commission has developed alternative approaches that better reflect the reality. An independent review of appraisal methodology would now be desirable.

Digital navigation seems to be having a significant impact on traffic flows. While the consequences are as yet little understood, it appears likely that the modelled benefits of road investment would be overstated if local traffic rerouting is disregarded. It would be desirable for the DfT to commission a study of the impact of digital navigation on the road network.

January 2021


[1] Metz, D. (2021) Time constraints and travel behaviour. Transportation Planning and Technology,44 (published online).

[2] Competition Commission, The supply of groceries in the UK market investigation, 2008. Fig 3.9

[3] National Infrastructure Commission, National Infrastructure Assessment, 2018.

[4] Metz, D. (2021) Economic benefits of road widening: discrepancy between outturn and forecast. Transportation Research Part A, (forthcoming).

[5] Department for Transport. Full Business Case: High Speed 2 Phase One. 2020.

[6] National Infrastructure Commission. Rail Needs Assessment for the Midlands and the North: Final Report. 2020.

[7] https://nic.org.uk/studies-reports/national-infrastructure-assessment/uplift-tool/

[8] Department for Transport. Benchmarking Minor Road Traffic Flows for Great Britain, 2018 and 2019: Methodology Report. 2020.

[9] Road Traffic (Driver Licensing and Information Systems) Act 1989.

The coronavirus pandemic stimulated initiatives by both the UK government and local authorities to promote active travel. The rationale was that public transport would be less attractive and would have less capacity while transmission of the virus remained a problem, so that the alternatives of walking and cycling should be promoted urgently.

The Secretary of State issued statutory guidance in May 2020 to local authorities expecting them to make significant changes to their road layouts to give more space to cyclists and pedestrians. As well as a response to the pandemic, active travel was seen as affordable, delivers significant health benefits, improves well-being, mitigates congestion, improves air quality and has no carbon emissions at the point of use. Substantial government funds were provided to local authorities for this purpose.

In London, the Mayor announced a bold new plan for street space, hoping to accommodate a ten-fold increase in cycling and a four-fold increase in walking, the rationale being that with London’s public transport capacity potentially running at a fifth of pre-crisis levels, millions of journeys a day would need to be made by other means. If people were to switch only a fraction of these journeys to cars, London risked grinding to a halt, air quality would worsen, and road danger would increase. To prevent this happening, Transport for London (TfL) would rapidly repurpose London’s streets to serve this expected unprecedented demand for walking and cycling in a major new strategic shift.

I have previously commented skeptically about the feasibility of such a large shift in travel mode. But the rationale for the urgency of the government’s and the Mayor’s initiatives was to achieve a reduction in use of buses and trains. However, that reduction came about through the measures to reduce virus transmission that included encouraging all those who could work from home to do so, as well as closure of non-essential shops during the periods of lockdown. The result was that city centres were denuded of workers and shoppers, and the extra space for walking and cycling was not needed.

The was quite often local opposition to local measure to introduce Low Traffic Neighbourhoods in which car use was restricted, not least because they were introduced without consultation as matters of urgency to respond to the pandemic. In a number of cases, decisions were reversed. An important reversal arose from a recent judicial review in the High Court initiated by bodies representing London taxi drivers who complained about TfL’s decision to exclude of taxis from an important street in central London (part of the A10 route).

The judge found against the Mayor and TfL, concluding that the measures proposed in their Plan and Guidance (Streetspace for London), and implemented in the A10 order, far exceeded what was reasonably required to meet the temporary challenges created by the pandemic. However, the judge also concluded that had the Mayor and TfL proceeded more cautiously, monitoring the situation and acting upon evidence rather than conjecture, their proposals would have been proportionate to the difficulties which needed to be addressed.

So the judgement was critical of the rushed process, but does not rule out measures that change use of streets provided proper process is followed, including gathering relevant evidence, consulting with those that might be affected, and drawing rational conclusions.

Update 22 June 2021: the Court of Appeal has reversed the High Court judgement, details of the judgement to follow.

The Climate Change Committee has published a comprehensive and impressive analysis of how to achieve net zero carbon emissions by 2050. This includes a detailed treatment of surface transport, currently responsible for 22% of UK Greenhouse gas emissions, the absolute amount having changed little since 1990, stable in the range 110-120 MtCO2e annually. Cars account for 61% of surface transport emissions. Three options are proposed to secure emissions reduction:

Reducing demand for car travel by a variety of social and technological changes, including increased home working, online shopping, increased car occupancy though shared mobility, a shift to active travel and public transport, and more fuel-efficient driving.

Improving conventional vehicle fuel efficiency through regulation of road vehicle performance, use of biofuels, and more rail electrification.

Widespread deployment of electric vehicles (EVs) with the uptake of new battery EVs to reach 90-100% by 2030, in line with the government’s intention to phase out sales of new conventional cars and vans by that date. Driving range is expected to improve as battery technology advances. Sufficient charging infrastructure would be needed for the 30% of car users without access to off-street parking, as well as rapid charging for longer trips. The electricity supply system will need reinforcement.

The CCC has modelled the quantitative requirements associated with these options to show that it is possible to reduce surface transport emissions to 32 MtCO2e in 2035 and to 0.9 MtCO2e in 2050. The largest contribution comes from EVs. There are of course multiple uncertainties, many of which have been modelled.

The question is to what extent it will be possible to follow this emissions reduction pathway without measures beyond those already planned. Will it be necessary to create stronger incentives, for instance through more subsidy for EV charging facilities, or by making conventional vehicles more costly to operate through increased taxation? Changing relative prices can be a powerful incentive to change behaviour. It has not been helpful that public transport fares have risen much faster in recent years than the cost of motoring, in part due to a freeze on the rate of road fuel duty since 2010, reflecting perceived political sensitivities.

I am not optimistic about the practical possibilities that would increase the cost of car use, even for the virtuous cause of tackling climate change. We will have to make the most of regulation, the costs of which are more opaque, to effect the necessary changes.

The National Infrastructure Commission (NIC) has issued an interim report on its assessment of rail needs for the Midlands and the North. It sets out a methodology for appraising investment options. The aim is to assess the potential benefits of possible investment packages, focussing on what rail is good at compared to other modes: transporting people into dense city centres and providing high speed links between cities.

The NIC believes that existing approaches to assessing the impact of rail investments on economic growth, such as conventional cost benefit analysis, fail to fully capture the interactions between rail investments and other factors, such as skilled employment and urban development.

Specifically, the NIC notes that conventional cost-benefit analysis in transport starts from ‘user benefits’ such as journey time savings. Wider economic benefits from agglomeration can then be added provided care is taken to avoid double-counting. However, this approach has been criticised for commuter journeys, because assumptions made around time savings do not appear consistent with the empirical evidence on travel times (this is a reference to my longstanding observation of the invariance of average travel time). Instead, the intention is to assess the economic benefits of increased transport capacity that allows more people to travel into city centres, thus increasing the agglomeration benefits that arise from density.

This is a rather radical approach, which runs counter to half a century of conventional transport economic analysis, and which I welcome, as a long time critic of orthodoxy. I look forward to seeing how its works out in practice.