TAPAS.network | 21 March 2024 | Commentary | David Metz

When theory and reality don’t match, we need to change the way we think

David Metz

The detailed business case for the A428 road scheme recently published does not convince David Metz that this is a sufficiently justified project. Here he examines the questionable assumptions and doubtful calculations that typify such propositions. He suggests that more real world thinking based on heuristics – rules of thumb - would promote and support better informed and more open decision-making.

THE RECENT PUBLICATION of the Full Business Case (FBC) for the A428 Black Cat to Caxton Gibbet Improvements Scheme (reported in LTT 6 March 2024 and the subject of editorial comment) highlights the policy inconsistencies and misleading supporting analysis that typify road investments. We have the Introduction by the Roads Minister explaining that A428 has long been seen an important section of the strategic road network that required upgrade due to its problems of congestion, poor journey time reliability and resilience, and how accordingly the Scheme will enhance journey times, support local and regional economic growth, create jobs, and improve employment and the environment.

To justify these high level objectives, the 270 page FBC grinds through all possible aspects of the case for constructing ten miles of dual carriageway. This is impressive in its way, but is the effort ‘proportionate’, to use a favourite DfT term, I wonder? Perhaps the intent is to ensure the proposal is crash-proof in the event of any further legal challenge; or perhaps to deter potential challengers from initiating such challenge. Then again, the economics of the investment look pretty marginal, based on opaque reported analysis, so perhaps extensive quantity is seen as a counterbalance to thin quality in making the case for the Scheme.

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Journey time savings for all classes of vehicles, of £633m, are claimed as the main benefit, as is usual (although in 2010 prices discounted to 2010 – implying some antiquity to the modelling). But this is not split between business users (cars and road freight) and non-business (commuters and others), as must have been modelled, since each class has a different value of time. In other cases I have examined, the split between business and non-business has been shown, with time savings to non-business users almost entirely offset by increased vehicle operating costs, the result of local users diverting to take advantage of faster travel provided by the improved route. The economic case for a scheme depends on the scale of such diversion, since local users pre-empt capacity intended for longer distance business users. This failure to split the journey time savings looks like intentional obfuscation.

The time saving benefits are in any case offset by quite substantial carbon disbenefits worth -£182m. My impression is these are much more than in previous road schemes, reflecting updated carbon values promulgated by the former Department of Business, Energy and Industrial Strategy. So no longer are increased carbon emissions dismissed as de minimis, at least in economic terms. Nevertheless, if, as I expect, the long run benefits of the scheme mainly take the form of enhanced access, rather than time savings, the increased vehicle-miles-travelled (known as ‘induced traffic’ [reference 1]), would increase externalities. So carbon disbenefits are likely to have been underestimated.

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Whatever the magnitude, new road capacity must generate more carbon emissions. What needs to be spelled out is the total increase in carbon from the whole road investment programme, to see to what extent this impedes delivery of transport’s contribution to Net Zero. Regrettably, the new 114 page National Networks National Policy Statement, recently published and reviewed elsewhere in this issue, fails to prescribe programme level estimation of carbon emissions. If neither at programme level nor at scheme level, where is this significant and unwanted damaging impact to lie?

While the cost data in the FBC are redacted, presumably to protect National Highways position in other road scheme projects out to tender, the initial benefit-cost ratio (BCR) is estimated as 0.92. To make the investment at all viable, ‘wider impacts’ of £282m have been adduced to yield an adjusted BCR of 1.63. This scale of wider impacts seems very high for a non-urban scheme, based as it is on an elaborate, yet in reality, not much more than a back-of-the-envelope calculation. It may be that it is this tenuous boost to benefits, to put the Scheme in the DfT’s medium VfM category, that has necessitated the supporting assessment and sign off by the two accounting officers, the DfT permanent secretary and National Highway’s chief executive.

For my part, I suspect that optimism bias is at work to generate even an initial BCR of 0.92, requiring yet more optimism to get to 1.63. So I would not regard the figures in the FBC as robust, even though the analysis is presented as exceptionally extensive. Yet I have some sympathy for the highways engineers at National Highways, who see this scheme as necessary to create continuous dual carriageway between the M1 at Milton Keynes and the M11 at Cambridge, with onward travel to the ports of Felixstowe and Harwich. A stretch of single carriageway in what is otherwise a dual carriageway route is, to them, offensive. Naturally they seek to add capacity to reduce congestion and achieve a free-flowing network. This approach would also seem logical and persuasive to most local politicians and business leaders not versed in the principles of transport planning and the observed road user responses to additional capacity provision, let alone the minutiae of scheme appraisal and Benefit Cost Ratio calculation.

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However, congestion on roads in well-populated parts of the country typically displays morning and evening peaks, indicating use by commuters, who have choices of route. Travel patterns are not fixed and are certainly influenced by network changes (whatever modelling theory might prefer to think). So new free-flowing routes tend to attract additional traffic, whether by diversion in the short run to achieve the saving of journey time, or in the longer run through permitting longer trips within the travel time available. Both of these are beneficial but are not the benefits conventionally modelled, nor are they allocated to the categories of traffic that underpin the original justification for the scheme. Generally, where commuters and longer distance business users share road space, free flow is difficult to achieve, particularly at peak hours.

There is a gulf between the simplistic but erroneous headline justification for this and similar road investments, and the complex, opaque and misleading quantified supporting analysis. It would be good to find a common language to bridge this gap, based on a behaviourally realistic account of what is going on, what options there are to improve matters, and what is most likely to happen in practice if changes are made. Applying the concept of Heuristics is one possible solution.

Heuristics are simple rules – rules-of-thumb – for making decisions, coming to judgement, solving problems or shaping intuitions, that work well enough in most circumstances. I want to suggest that transport planners and practitioners would benefit from relatively simple heuristics in offering advice to decision makers about addressing perceived issues of system inadequacy and the justification for providing additional capacity in a range of circumstances.

This would mean distilling the evidence from research by academics and others to yield rules-of-thumb that are intuitively credible to both practitioners and decision-makers. One problem is that research findings are often based on case studies, specific to place and time, and are path-dependent, so generalisation may be difficult. Besides, the research literature in the area of transport studies has burgeoned in recent years, not necessarily to overall professional benefit, in part the consequence of the proliferation of open access journals that charge researchers for the cost of publication, rather than rely on library subscriptions; this creates an incentive for the journal to downplay rigorous peer review and editorial oversight in the interest of increasing income, and the consequence is a proliferation of case studies that may gain academic credit but are of limited general applicability.

Moreover, the research literature may overlook the authoritative information available in official publications, including statistical series, as well as in the unofficial ‘grey literature’ publications from think-tanks and others (a topic explored at length by Professor Phil Goodwin (ref 2)). Hence formal reviews of the ‘research literature’ may therefore be both unwieldy and incomplete, making it hard to see the wood for the trees and so difficult to draw useful conclusions. Government departments accordingly now seem often to commission ‘rapid evidence reviews’, which give consideration to a manageable number of selected papers to save time and effort, but selection may be biased, consciously or otherwise, to support the expectations of the commissioning department, and the most important recently revealed insight and understanding may not yet be included.

In these circumstances, I believe helpful Heuristics would need to be based on a deep and wide knowledge of both publications, practice and observed data, to establish a cogent and concise framework for analysis and decisions, in accessible language, not set in stone but subject to review in the light of new evidence and experience.

One area where rules-of-thumb may be particularly useful for transport planners and decision makers is in the tackling of road traffic congestion, central to the contemporary travel experience and to transport investment, such as the A428 Scheme, but for which repeated interventions have demonstrated little impact in practice. To the extent that relief may be achieved, this is more short term than long term. Yet huge amounts of public expenditure are justified by the objective of relieving congestion and boosting connectivity, with little evidence of success at outturn.

So, let me suggest some rules-of-thumb for thinking about road traffic congestion. I will not cite chapter and verse of the evidence in support, for which see my recent book (ref 3).

  • Congestion arises in or near areas of high population density where car ownership is also high. More car trips might seek to be made at times of peak demand than the road network can accommodate. Delays ensue, which motivate some road users to make other choices, including adopting alternative routes or times of departures, alternative modes of travel where available, different destinations where there are choices (such as for shopping trips), or not to travel at all (such as ordering good online). Congestion therefore is generally self-regulating in that if demand increases, delays increase and more potential trips are suppressed. Daily gridlock or long tailbacks are uncommon and arise where there are unanticipated obstructions to movement.

  • Increasing road capacity has the effect reducing delays in the short term, but thereafter attracting previously diverted and suppressed trips, as well as permitting new and longer trips, consistent with the maxim that we can’t build our way out of congestion, known from experience to be generally true. The result is additional traffic, known as ‘induced traffic’, which in the short term is the consequences of diversion of commuters and other local users on to the new capacity to save time; and, in the longer term, of road users taking advantage of faster travel to make longer trips to increase access to desired destinations, as well as changing trip origins by moving homes.

  • Interventions that reduce vehicle use initially reduce delays, but this attracts back onto the network previously suppressed trips, thus restoring congestion to what it had been. Interventions conceived as intended to reduce vehicle road use include the promotion of active travel and public transport, congestion charging and road pricing, and consolidation of freight deliveries into fewer goods vehicles.

  • Reduction in urban carriageway available to general traffic can make more space available for bus lanes, cyclists and pedestrians. This initially can increase congestion delays, which leads to drivers making alternative choices. In the longer term the intensity of congestion is difficult to reduce, but the absolute amount of congested traffic would be lessened and could be better managed to benefit the whole population.

  • Induced traffic results in more vehicle operating costs and in additional externalities, including carbon and air pollutant emissions, which public policy is seeking to reduce.

  • The orthodox economic case for road investment relies mainly on the saving of travel time. Yet the evidence is that average travel time is a long term invariant, implying that people take the benefit of faster travel in the form of improved access - to people, places, employment, services and activities, with ensuing enhanced opportunities and choices.

  • Transport models that project travel times savings, comparing the with- and without investment cases, do not reflect the reality that improved access is actually the main beneficial outcome. Access is subject to diminishing returns, implying declining returns to road investment as the road network matures.

  • The car is very popular for its utility in door-to-door travel over short to medium distances, as well as over longer distances when alternatives are less attractive, provided congestion delays are acceptable and parking is available at both ends of the journey. These conditions may not apply in city centres, where public transport, particularly rail-based in all its forms, provides a speedy and reliable alternative to cars and buses on congested roads. But beyond city centres, in suburbs, towns and rural areas, the popularity of the car as a mode of travel against available alternatives is difficult to challenge.

  • Promotion of active travel has limited impact on car use. The evidence is that improved cycling facilities mainly attracts people from buses, which reduces farebox income and leads to reduced service levels or a requirement for more subsidy. It is difficult to be pro-active to successfully increase walking, which is the slowest mode of travel, permitting the least access to desired destinations for most people.

  • The built environment, within which are located nearly all the homes, facilities and services that are trip origins and destinations, is largely a given, with limited opportunity to increase density through brownfield or infill development. Creation of new communities on greenfield sites with choice of travel modes has proved difficult. Accordingly, there is limited scope for the creation ’15-minute cities’, an aspiration of many urban planners, aimed at reducing car use, congestion, pollution and carbon emissions.

  • As well as being popular for getting from A to B, for many people ownership of a car is attractive for a variety of lifestyle reasons. The fact that cars are generally parked for 95% of the time is a seemingly persuasive economic argument for car sharing in its various forms. But conversely, the desire to own a resource that is so little used is an indication of the value attached to ownership and convenience. This is in part why it proves difficult to shift car owners to other modes. Cars parked at the kerbside reduce carriageway available for vehicles on the move, contributing to congestion delays and deterring some road users.

  • The wide use of digital navigation (known in the roads context as satnav) has the effect of redistributing traffic. Commuters and other local users divert from existing routes to new capacity on major roads, to save time, pre-empting capacity intended for longer distance business users, including freight, so detracting from the projected economic benefits of the new capacity. In addition, traffic diverts from congested major roads to minor roads that offer a less congested alternative route, such minor roads previously used only by those with local knowledge, making them ‘rat runs’ less suited for active travel and detracting from quiet residential environments.

  • The most advanced forms of digital navigation predict journey times, so reducing uncertainty about time of arrival, which is what bothers road users most about the impact of congestion. Digital navigation is thus arguably the best means available for mitigating the perceived impact of road traffic congestion, as well as being vastly cheaper than providing new road capacity.

These rules-of-thumb about observed realities are proposed as ‘good enough’ ways of recognising and addressing the problem of congestion that we face on road networks and identifying effect means of mitigation. I suggest three questions to structure shared thinking about this and the other problems we face, amongst transport planners, politicians, other decision makes and influencers:

Q1 What’s going on here?
Q2 What options do we have to do better, that are both cost-effective and affordable?
Q3 What choices to make?

Responding to the first two questions is the task of analysts, including transport planners, economists and policy advisers, approaching problems with an open mind. Responding to the third question, with the benefits of the answers to the first two, is the task of decision makers in the public and private sectors, as well as advocates of all kinds. Better decisions would be made if those involved are clear about their roles, tasks and expectations. Heuristics, of the kind outlined above, could help them acquire good intuitions of the cost-effective options available, and give others greater insight into the basis on which decisions are made.

Nevertheless, some may argue that such heuristics serve to over-simplify what is bound to be a complex analysis of what’s going on. Albert Einstein said: ‘Make things as simple as possible, but no simpler’. Are these heuristics for understanding and reacting to congestion good enough or are they too simple? Do we still need the full panoply of the Department for Transport’s Transport Analysis Guidance to present to a small coterie of people a theoretical analysis based on problematic behavioural assumptions as to what should be done? Or, as some may believe, to justify, through virtually impossible to decipher analytical complexity (as represented by the likes of A428 business case), someone’s original hunch, then bought into tenaciously by the scheme’s promoting bodies. My own view is that narrative and dialogue based on heuristics would offer an alternative approach, well worth trying, to answer the three questions above in a generaly understandable way.

References and Links

  1. Phil Goodwin and Lisa Hopkinson, Induced Traffic: yet again a worryingly overlooked dimension in crucial road planning and appraisal policy.

  2. Phil Goodwin, From black to white and shades of grey: the flawed world of expert knowledge dissemination in transport.

  3. David Metz, Good To Go? Decarbonising Travel After the Pandemic. London Publishing Partnership, 2022.

  4. DfT/NH A428 Full Business Case

David Metz is an honorary professor at the UCL Centre for Transport Studies. www.drivingchange.org.uk

This article was first published in LTT magazine, LTT888, 21 March 2024.

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