I previously mentioned my analysis of the widening of the M1 motorway between junctions 10 and 13. My paper has now been published in a peer-reviewed journal: Transportation Research Part A, 174, 103749. The abstract is below. Access to the article may be available free of charge for a limited period here


Cost-benefit analysis of road investments involves models that generate travel time savings as the main economic benefit. Evaluation five years after opening of a scheme to widen a section of England’s M1 motorway between junctions 10 and 13 found that the traffic moved more slowly than before the scheme opened. Comparison was made with forecast flows generated by SATURN variable demand modelling and an associated economic model. Substantial net benefits to business users were forecast, whereas for non-business users time saving benefits were more than offset by increased vehicle operation costs, consistent with diversion of local trips to take advantage of the increase in capacity. There is reason to suppose that such diversion is facilitated by the wide adoption of Digital Navigation (known generally as satnav), which makes evident the fastest route choices, even at the expense of increased fuel costs. Diversion of local trips to utilise new strategic road capacity seems likely to be a general phenomenon, which detracts from the economic case for road investment. There is therefore a good case to treat the strategic road network as mature, focussing on improving operational efficiency and exploiting vehicle-to-infrastructure connectivity in the form of Digital Navigation.

The Department for Transport has issued a draft National Networks National Policy Statement (NNNPS) for consultation . It covers major investments on the road and rail networks in England. The draft is intended to replace the version issued in 2015, before the government’s commitment to Net Zero and publication of the Transport Decarbonisation Plan. The House of Commons Transport Committee has announced an inquiry into this draft.

The DfT states that the 2015 NNNPS shall apply to projects already selected for public examination, so the new NNNPS will apply only to applications accepted after it is implemented, following the consultation. It therefore looks as though the Lower Thames Crossing tunnel, which has been accepted by the Planning Inspectorate for consideration, will be subject to the old guidance, despite construction being deferred by two years as announced in the recent Budget, which seems odd.

The purpose of such National Policy Statements is to provide guidance for decision-makers on the application of government policy when determining development consent for major infrastructure. The intention is to remove the need for consideration of fundamental national policy questions at planning inquiries. Those subject to this guidance are the scheme promoters (National Highways for most road proposals), planning inspectors, and the Secretary of State when granting Development Consent Orders.

The important question is how investment in new road capacity could be reconciled with the government’s legal commitments to achieve Net Zero greenhouse gas emissions by 2050, meeting the requirements of both the Climate Change Committee’s Sixth Carbon Budget that has been agreed by the government and the intentions of the DfT’s Transport Decarbonisation Plan. (Rail, already substantially electrified, is less of a problem.)

The draft opens by rolling the pitch, stating that the government sees a compelling need for the development of national networks (para 3.22), such that there is a presumption in favour of granting Development Consent Orders (para 4.2), while at the same time recognising the need to move away from ‘predict and provide’ (para 3.44). This is very different from the new approach of the Welsh government, which does not see a compelling need to develop its national road network.

Scheme proposals are to be supported by assessments of whole life carbon emissions, to ensure minimisation as far as possible (para 5.29). The draft states that, in reaching a decision, the ‘Secretary of State should be content that the applicant has taken all reasonable steps to reduce the total greenhouse gas emissions from a whole life carbon perspective. However, given the important role national network infrastructure plays in supporting the process of economy wide decarbonisation, the Secretary of State accepts that there are likely to be some residual emissions from construction of national network infrastructure’ (para 5.36). Moreover, a net increase in operational greenhouse gas emissions [from more traffic] is not, of itself, reason to prohibit the consenting of national network projects or to impose more restrictions on them in the planning policy framework (para 5.37). So in policy terms, additional road capacity is more important than decarbonisation.

Importantly, the application for development consent orders applies to individual schemes. There appears to be no requirement to estimate the impact on carbon emissions from an investment programme, such as the planned five-year Road Investment Strategy 3 (RIS3) due to start in 2026. Accountability scheme by scheme is not so very different from the present practice whereby National Highways argues that each individual scheme makes only a de minimus contribution to national carbon emissions, which can therefore be disregarded.

The DfT’s Transport Decarbonisation Plan made broad-brush estimates of carbon reduction from policies and programmes, for instance 1-6 MtCO2e from increased active travel over the period 2020 to 2050, and 620-850 MtCO2e for electrification of cars and vans over the same period. It is inconsistent not to recognise offsetting carbon increases from investment in new road capacity, likely to fall somewhere between the above ranges, and certainly not de minimis for the programme as a whole.

There is also a problem of modelling future carbon emissions arising from road investment. Transport models are complex and opaque, with many parameters, the value of which requires expert judgement. In consequence, the are two types of protagonist: experts who have a good working understanding of transport models because they earn their living from building and running such models; and non-experts, who are interested in the output of models but are not able to understand the assumptions, simplifications and judgements that the experts must make. Non-experts include decision makers in national and local government who have prior expectations of the economic value of particular road schemes, and whose test of a good model is that it delivers outputs, comparing with- and without-investment cases, consistent with these expectations. Other non-experts are those opposing road schemes at public inquiries, who are faced with modelled outputs as part of the promoter’s proposal that are not open to detailed scrutiny. Inspectors at planning inquiries are also non-expert in this sense.

The NNNPS requires projects to be supported by a local transport model, but planning inspectors and the Secretary of State do not need to be concerned with the national methodology and national assumptions around the key drivers of transport demand (para 4.7). In practice, most schemes on the Strategic Road Network employ local versions of a set generic traffic and economic models, typically SATURN for network traffic modelling, the outputs of which are inputs to the TUBA economic model. So, as it appears, consideration of the predictive validity of these models for projecting carbon emissions need not be considered either at a public inquiry or by the Secretary of State. One can understand why a planning inspector should not be burdened with a task for which they are not professionally trained. Nevertheless, the question is where in the decision-making process the validity of the supporting modelling might be assessed.

The need to assess the predictive validity of transport models is pointed up by the failure of standard models to project fairly short-run traffic flows in two cases of motorway widening, on the M25 and the M1, as I have recorded previously. This does not increase confidence in the ability of such models to project economic benefits and carbon emissions out to sixty years.

One particular problem of transport models is that they are largely used to justify new investment, in which context the saving of travel time is supposed to be the main economic benefit. Yet average travel time, as estimated by the National Travel Survey, has changed very little over fifty years, excepting the period of the coronavirus pandemic. The implication is that people take the benefit of faster travel as enhanced access to desired destinations, people, places, activities and services, for the opportunities and choices on offer. Travelling further, rather than using travel time savings for more productive work or agreeable leisure, means more externalities related to vehicle-miles travelled, carbon emissions in particular.

Modellers who aimed to model such access benefits, and the resulting changes in land use and value, would not be appreciated by the economists who are wedded to travel time saving as the main economic benefit of investment, nor by decision-makers who are well used to conventional economic investment appraisal. So modellers must fix their assumptions, simplifications and parameters to get outcomes that satisfy a ‘realism test’ of prior expectations, subject to conformity with unspecified standards of professional respectability.

The upshot is that the modelling of the impact of new road investments will systematically underestimate carbon emissions from the additional (induced) traffic. This makes it easier to appear to comply with the pathway to Net Zero, but means that the outcome is likely to fall short of that pathway.

Some further light is shed on this matter by the cost-benefit analysis the DfT has published in support of options to implement the Zero Emissions Vehicle Mandate, the legislative framework to fulfil the government’s objective to phase out the sale of internal combustion engine cars and vans by 2030. The need for this cost-benefit analysis is not stated, since the timing of the phase out is largely for negotiation between the government and the motor manufacturers. Perhaps the Treasury wish to be assured that this route to decarbonisation represents good value compared with other possible decarbonisation measures. Or perhaps the DfT economists wish to parade their competences after cost-benefit analysis failed to be supportive of a number of major rail and road investments.

The modelling assumes that that the switch to ZEVs could result in increased mileage per ZEV driver because electricity as fuel is cheaper than petrol or diesel (which begs the question of whether some new charge for EVs might be introduced, as I have suggested). This extra driving, a ‘rebound effect’, is supposed to lead to more congestion delays, with a very substantial cost impact: for a central sensitivity case of the preferred policy option, the abatement cost of the ZEV Mandate for cars and vans estimated as £12/tCO2e excluding the rebound effect, and £100/tCO2e including it (Tables 61 and 62).

So, the DfT thinks it would be much more costly to reduce CO2 emissions by means of the Mandate if the lower operating cost of EVs led to greater distances travelled. However, in my view, rebound of the magnitude modelled is unlikely, quite apart from the possibility of a road user charge for EVs. The per capita distance travelled by car depends on three main factors: speed of travel, time available for travel, and household car ownership. None of these are affected by the switch to electric propulsion. Vehicle operating costs have a second order impact at best, witness the growth of SUV ownership despite higher fuel use.

Paradoxically, the DfT modellers postulate additional traffic from reduced vehicle operating costs arising from electrification (mistakenly, in my view), while being in denial about the additional traffic arising from road users taking the benefit of investment in increased capacity as enhanced access involving more travel (again mistakenly).

The ZEV Mandate cost-benefit analysis states that the preferred policy option is expected to achieve emission savings of 415 MtCO2e in the period 2020-2050 (Table 29). This is substantially less than the savings from switch to electric propulsion of car and vans of 620-850 MtCO2e projected in the Transport Decarbonisation Plan, mentioned above. No clear explanation for this discrepancy is given; it may be because the present Mandate is for the period to 2030, with a further Mandate promised for 2031-35; or it may reflect the sensitivity of model outputs to input assumptions.

More generally, modelling for the ZEV Mandate exemplifies how modelling outputs can be very sensitive to input assumptions that are made in the absence of firm evidence of future travel behaviour. This is a caution that applies to most transport modelling, not least to the projections of transport sector carbon emissions to support decisions necessary to achieve reductions required by the legislative framework to achieve Net Zero.

We have been before in a situation in which there have been doubts about approaches to transport economic analysis endorsed by the DfT. Good work was done by SACTRA – the Standing Advisory Committee on Trunk Road Assessment – an independent body created by the DfT, that issued two influential reports in the 1990s. One confirmed the importance of induced traffic arising from new road construction, a view that had been resisted by the DfT since such traffic added to congested and reduced travel time savings. The other report recognised the wider economic impacts of investment, beyond the conventional time saving, vehicles operating costs and those externalities to which monetary values could be attached; estimation of such wider impacts, such as agglomeration effects, now forms part of the standard approach to investment appraisal.

Although SACTRA, by its very name, was intended to remain in existence, at least until formally stood down, it seems to have fallen into that state by not receiving new commissions. There is a need, in my view, to reconstitute it, or some similar body of independent experts, to look at the suitability of the current body of official guidance on transport economic analysis and modelling in an era when decarbonisation is a national policy priority. As it is, however, the people in DfT and their consultants, who naturally wish to please their clients, are talking to each other in an echo chamber, from which interested outsiders are excluded.

Other departments do better. The Treasury’s model of the UK economy has long been available to independent forecasters. The Energy Department collaborates with academic energy modellers and makes available the online Mackay Carbon Calculator that allows users to explore the options for reducing carbon emissions. Modelling of the coronavirus pandemic was largely carried out collaboratively by academic groups whose models and outputs were public for all to debate. And the modelling of climate change is carried out openly, collaboratively and internationally as input to the reports of the Intergovernmental Panel on Climate Change.

Th DfT instigated a move to update the National Transport Model to generate a new version, NTMV5, intended to be open to other users, but this seems not to have worked out in that the National Road Traffic Projections 2022 employed the previous version (as I have noted). The DfT should explain what went wrong, and should engage openly with those beyond the Department and its immediate advisers on how best to model the decarbonisation of the transport sector.

This blog post is the basis for an article in Local Transport Today 23 May 2023.

My written evidence to the House of Commons Transport Committee inquiry into the National Networks National Policy Statement is based on this blog.

The National Infrastructure Commission has published an Advice Note, directed to the government, on roads policy, to help inform plans for the Third Road Investment Strategy (a five year investment programme for strategic interurban roads). I found this rather disappointing in its analysis of the problem.

The need to decarbonise road transport is obligatory, yet investment in new road capacity is counterproductive, whatever is achievable through the switch to electric propulsion. The Department for Transport’s draft National Networks National Policy Statement, recently issued, persists in addressing carbon emissions at scheme level, where they can continue to be treated as de minimis. There should be a requirement to estimate carbon emissions for the whole future programme (RIS3), when announced.

Given the conflict between road building and achieving decarbonisation, a critical look is needed at the econometric analysis of the relationship between interurban road investment and GDP growth, which is less than convincing. Likewise, scepticism is justified as regards projections of the growth of future traffic growth based on demographic and economic factors; per capita car use did not increase for twenty years prior to the pandemic. The main factors determining car use per capita are speed of travel, time available for travel and household car ownership, none of which seem likely to increase in the future.

The benefits of road construction are subject to diminishing returns. Arguably, the UK has a largely mature road network. For instance, cities such as Stoke-on-Trent and Wakefield, which would see themselves as lagging economically, are well located in relation to the Strategic Road Network. For devolved regional governments able to decide priorities for infrastructure investment, new road capacity may not be high, except where it is required to permit major site-specific development.

The Advice Note argues that effective prioritisation of road projects requires a focus on the links that will be most significant for trade between major regional cities. However, interurban roads are used by commuters travelling into cities. It is a common situation for traffic on interurban routes in or near populated areas to show pronounced morning and evening peaks, the consequence of commuting. If capacity is increased to alleviate congestion at these times, this will attract commuters from local roads on account of the faster travel made possible – one type of induced traffic, and one reason why we cannot build our way out of congestion. This diversion of commuters on to new major road capacity is facilitated by the wide use of Digital Navigation (generally known as satnav), which makes fastest options clear. The increased local commuting pre-empts the additional capacity intended for longer distance business users.

The proposal for a systematic analysis of the road network to see which routes are slow or unreliable is reminiscent of the approach of US highway engineers to categorising levels of service as the basis for proposals to increase capacity, thus justifying multilane freeways that attract more traffic. Yet there is a conflict between accepting the need for further road construction and demand management measures to reduce carbon emissions from the sector.

We no longer add to urban road capacity to accommodate growth of demand for road traffic; indeed, the trend is to subtract carriageway available for general traffic in favour of more space for buses, cyclists and pedestrians, plus investment in urban rail, traffic management and demand management measures. Yet the focus of interurban roads policy continues to be on investment in new capacity (although the Welsh Government has taken a different view). Given the demands of decarbonisation, a reconsideration of this traditional focus is desirable.

The prospects for autonomous vehicles as a source of economic benefit are unclear. Yet Digital Navigation is widely use and is changing travel behaviour. Road freight operators take advantage of similar digital technologies to manage their fleets effectively. There are opportunities to exploit digital technologies to improve the operational efficiency of the mature road network, which would be far more cost effective than civil engineering technologies employed to increase capacity.

The Department for Transport has scrapped plans for new smart motorways, citing current lack of confidence felt by drivers and cost pressures. It also reflects a pledge by the Prime Minister when he was campaigning last year for election as leader of the Conservative Party. However, the possibility of resuming build seems not to be ruled out since cancellation is said to ‘allow more time to track public confidence in smart motorways over a longer period’.

This cancellation is no great surprise, given the existing pause on construction until five years of safety data is available, a response of the DfT to a critical report from the House of Commons Transport Committee. There has also been a succession of reports from coroner’s inquests into deaths from fatal crashes when a broken-down vehicle on the innermost lane, previously the hard shoulder, had been impacted by a moving vehicle. It always seemed unlikely that the safety case could be made sufficiently persuasive to road users for the programme of smart motorway constriction to resume.

The attraction of so-called smart motorways was that an additional lane could be added to a motorway without further land take and without the cost and disturbance of rebuilding the bridges crossing the carriageway. The greater reliability of modern cars provided some justification. Yet the public was not convinced. The reliability of variable message signs used to close the inner lane in the event of a breakdown has been criticised. And while in the past new road construction could credibly be presented as offering safety improvement compared with historic roads, this was not evidently the case for smart motorways.

Cancellation of the current batch of proposed smart motorways raised a major question about the value for money of future road construction. This economic benefits of the forthcoming plans for the third Road Investment Strategy (RIS3) will need thorough scrutiny.

I was invited to contribute to a special issue of the journal Urban Planning on the topic ‘Car Dependence and Urban Form’. The aim of the editors was to explore the scope for developments of urban form to reduce car use. I agreed to contribute a review of the evidence of drivers’ perspectives, because I sensed there is a mismatch between the general popularity of the car and the concerns about its adverse impacts held by many transport planners and academics, such that they would wish to see a reduction in ownership and use. The paper is here. The abstract is below.

Abstract:  The concept of car dependence includes both travel to destinations for which other modes than the car are not practical and preference for car travel even when other modes are available. While the concept has been a focus for transport analysts for some time, car ownership and use have continued to grow. This reflects the utility of the car for travel on roads where drivers do not experience excessive congestion and where there is parking at both ends of the journey. Local public transport and active travel only become generally attractive alternatives to the car in dense city centres where road space for car use is limited. Reduced car dependence is facilitated by city planning that encourages increased density, opportunities for which are constrained by the stability of the built environment. As well as utility for travel to achieve access to desired destinations, car ownership is also attractive on account of positive feelings, including pride, reflecting both self-esteem and social status. The positive feelings of the population at large towards car ownership are not consistent with the critical view of many analysts, a divergence in point of view that contrasts with the general acceptance of the need to respond to climate change, for which the purchase of electric vehicles is seen as an appropriate action. Rather than advocating measures explicitly aimed at reducing car dependence, a more effective policy approach would be to increase the availability of alternative modes while mitigating the detriments of car use.

The issue of the open access journal that includes my paper is published.

Road pricing has been a perennial issue for transport policy, seen by transport economists as a rational means for allocating scarce road capacity when congestion is prevalent. The loss of revenue from road fuel duty as we switch to electric propulsion is a further reason to introduce road pricing, as the House of Commons Transport Committee argued in a report published in February 2022. The Government’s belated response, in the form of a letter from the Chancellor of the Exchequer sent in January 2023, stated that the government does not currently have plans to consider road pricing. The Transport Committee chair was not satisfied with this brush-off and has invited the Treasury to respond in greater detail to the Committee’s conclusions and recommendations.

The recent webinar, in which I participated, on the role of road pricing in achieving Net Zero, organised by Landor in partnership with SYSTRA, was therefore very timely. (View here https://www.youtube.com/watch?v=keDmdMMvPO0 )

Road pricing (or road user charging) has been in use for centuries in the form of toll roads, the money levied used to reimburse the cost of construction. Road pricing (or congestion charging) has been adopted in London, Stockholm and Singapore as a demand management measure. A more recent aim has been to reduce air pollution in urban areas by imposing a charge on the more polluting vehicles if they enter a Clean Air Zone (CAZ). And the need to decarbonise the transport system now prompts the question of whether and how road pricing might help achieve this objective.

Webinar contributor, David Connolly, SYSTRA, argued that to achieve a Net Zero trajectory for transport, there would need to be a significant reduction in car use. To attain this, the cost of car use would have to rise significantly, to increase the relative attractiveness of all of the alternative modes, (including car-sharing) and encourage shorter &/or less-frequent car trips. Increased costs of car ownership, of fuel and of parking were possibilities, but distance-based road pricing would have a direct impact on car use and could plug the revenue gap created by the loss of road fuel duty.

Trevor Ellis, an expert in the technology of road pricing schemes, outlined how these have been applied throughout the world. GPS-based tolling has already been adopted by a number of European counties for trucks, while many US states are trialling or operating per mile fee programmes. In Asia, Singapore and Indonesia are to implement national all-vehicle distance-based schemes soon. Trevor concluded that distance-based charging by GPS gives the flexibility to vary the charge by time and place, as well as by distance and emissions, but the biggest challenges are likely to be gaining political and public acceptance.

Silviya Barrett, of the Campaign for Better Transport, reported the outcome of a survey of public attitudes to road pricing, finding substantial agreement that the present system of vehicle taxation is in need of reform as we switch to electric vehicles (EVs), with almost half respondents supporting pay-as-you-drive as they reached the end of the survey. There would be more support if public transport were cheaper with improved connectivity.

My own view is that it would be difficult politically to use road pricing to increase the costs of motoring or of road freight, as a means to reduce vehicle usage. Our society is too dependent on road transport, so that not many politicians would be brave enough to attempt to reduce carbon emissions by a direct hike of road fuel duty or imposing an additional charge for road use. The situation of low-income motorists needing their cars for travelling to work would be a point of particular sensitivity.

However, EVs do not pay fuel duty, so there is a case that they should pay a charge for use of the roads, both to contribute to the costs of operation and maintenance of the network, and to make a contribution to the Exchequer, as do internal combustion engine (ICE) vehicles. Yet this could not be implemented immediately since the lower operating costs of EVs are important to compensate for the present higher capital costs. Nevertheless, it is expected that capital costs will decline as battery technology advances and that equivalence in capital costs of EVs and ICEs will be reached prior to the 2030 date for completion of the phasing out of sales of new ICE cars and vans.

The phasing out by 2030 is a policy that commands wide support across the political spectrum, as well as from the car manufacturers and the public, who are purchasing EVs in impressive numbers. It would be desirable to link the introduction of a road user charge for EVs to this policy approach, on the grounds of fairness as between the two kinds of vehicle in respect the operating costs incurred. This would allow time to develop a suitable road pricing system for EVs. I suggest that the existing fuel duty should remain in place for ICEs, which would avoid the anxiety that would be created, particularly amongst low-income motorists, by a major change in the charging regime. EV owners are generally better off, given the newness of the technology and the very limited second-hand market, and would be more able to cope with the cost increase.

There are variety of technologies that might be used to implement road user charging, some of which are in use other countries. Yet rather than introduce an unfamiliar technology, there would be much to be said for building on London’s experience, as the basis for a national system.

The London congestion charge has been in operation for twenty years. It has been technically successful, publicly acceptable, with no concerns about privacy despite camera surveillance for enforcement purposes, and it generates useful net revenues that support public transport provision. London has employed the same enforcement and charging system to implement the ULEZ (its version of a CAZ), initially within the central congestion charging zone, expanded last year to encompass the area within the North and South Circular Roads with fairly minimal public opposition, and intended to cover all London boroughs later this year (albeit with some local political resistance emerging in the outer boroughs). This exemplifies the scope for incremental roll-out of an established technology.

London’s daily congestion charge is based on the presence of the vehicle within the charging zone, for however long. For London’s technology to the basis for a national road user charging scheme for EVs, it would be necessary to migrate the charging arrangements to a smartphone app, since a smartphone knows where it is in time and space, so knows if it is in a charging zone at a time when the charge is levied. Smartphones are generally linked to  payment mechanisms. They would also need to be linked to the vehicle, since it is the presence of the vehicle that is chargeable, not the phone, but this should be feasible.

Adoption of the smartphone as the mechanism for payment could be incentivised by capping the daily payment at no more than the standard daily charge as paid via the existing online payment mechanism, at present £15. Once there was sufficient uptake of the app, there would be opportunity to vary the charges according to such factors as duration in the charging zone, time of day, level of congestion, location or distance within the zone. This should be publicly acceptable with the daily charge cap in place, analogous to the capping of fares on London’s buses and trains when contactless payments are made. The standard daily charge payable online would remain for those not wishing to use the app, as would the existing camera-based enforcement system.

With the app payment mechanism tested and accepted, it would be possible to extend it beyond the existing congestion charging zone. In the past, there had been a western extension of the London scheme, introduced by Ken Livingstone when he was mayor, but revoked by Boris Johnson. It would also be possible for other cities to adopt the technology, whether before or after national adoption for EVs. In the past both Manchester and Edinburgh developed plans to implement congestion charging, which, however, were rejected in referenda. Cambridge is considering a similar initiative. Adoption by a single city may seem a major step by the voters, whereas taking advantage of a national charging system in prospect may lessen their reluctance.

A national scheme of charging for road use by EVs could be introduced incrementally, whether by road type (such as motorways) or region, and by starting the charge at a low level, increasing over time as the arrangements bed down.

While a national scheme for EV road user charging might employ a separate payment app from that used in London or other cities, it would make more sense to use a single payment mechanism, apportioning the revenues between the Exchequer and the highway authorities, allowing the latter scope to vary their component of the charge to meet local needs. Over time, this could reduce the need for local authorities to bid competitively to central government pots of money for funding local transport initiatives, consistent with a general policy trend to increasing devolution of responsibilities from national to local government.

One particular possibility for the exercise of local decisions on the local component of the road user charge would be to fund improvements to public transport by increasing the charge, subject to the willingness of the electorate. More and better bus and rail services would be important in providing an alternative to car use, so facilitating decarbonisation. However, fare box revenues are insufficient to support good services, both frequency and geographical spread, so external funding is required. Yet subsidy from government, whether national or local, will always be in short supply. So revenues from road user charging seem the most likely source of further support to improve local bus and rail services.

The phasing out of sales of new ICEs by 2030 is generally agreed to be about as rapid as is feasible, but faster decarbonisation thereafter could employ the revenues from EV road user charging to fund a scrappage scheme for ICEs. This would need to be targeted at the most carbon emitting vehicles, a function of engine size and distance travelled. Age would also be important since the amount payable per vehicle would become more attractive as vehicles became older and less valuable. However, such a scrappage scheme could not usefully be implemented until there were good numbers of EVs available in the used car market.

Overall, my view is that road user charging seems unlikely to be acceptable as a means to increase the costs of road vehicle use generally in order to reduce distance travelled and carbon emissions. But there is a case for charging EVs once capital costs reduce, on grounds of fairness between vehicle with different types of propulsion. The good experience of the London congestion charge offers an incremental route to nation application, the key step being migration to a smartphone app, a familiar payment mechanism. Revenues could be apportioned between central and local government consistent with further devolution, and employed to facilitate transport decarbonisation by supporting improved public transport and funding a scrappage scheme for internal combustion engine vehicles.

So no big-bang implementation of road charging technology, rather an incremental approach that aims to carry the public along, step by step.

This blog post was the basis for an article in Local Transport Today of 20 March 2003.

The House of Commons Transport Committee is holding a timely inquiry into investment in strategic roads, following a critical report from the National Audit Office about progress with the £27 billion Road Investment Strategy 2 (RIS2) programme, now at midpoint. I submitted evidence as follows.


This submission is concerned with whether the Government’s road investment programme is meeting the needs of users, whether the programme aligns with other policies, and the relevance of technological developments. These are matters in which I have taken an interest for many years, starting when I was Chief Scientist at the Department for Transport.

Here I argue that:

  • the economic benefits of road investment have been overstated;
  • there is conflict with other Government policies, particularly Net Zero;
  • technological opportunities to improve the operational efficiency of the road network are neglected.

Economic benefits of road investment

The main economic benefit of investment in new road capacity is supposed to be the saving of travel time. The benefit-cost ratio of a proposed scheme, a measure of value for money, largely depends on the estimated value of time savings to business users and others, in relation to the cost of construction. However, there are now available evaluations of outcomes of smart motorway schemes 3-5 years after opening that find no time savings, in part on account of traffic volumes greater than forecast.

I have compared the traffic and economic forecasts with the outturns for the two smart motorway schemes for which data is available: M25 Junctions 23-27 and M1 Junctions 10-13.[i] A salient feature of the forecasts is that the value of time savings to non-business users (commuters and others) is almost entirely offset by increased vehicle operating costs. This is the result of local users diverting to the new motorway capacity to save a few minutes travel time, for instance from home to work, not fully recognising the additional fuel costs arising from the longer trip. Such diversion is facilitated by the widespread use of Digital Navigation (generally known as satnav), which makes clear the fastest routes.[ii]  Increased use by local users pre-empts capacity for longer distance business users, for whom the additional capacity was intended, and based on which the economic case for investment depends.

It is likely that these examples are representative of the general situation in that the Strategic Road Network comes under greatest stress in or near areas of population density where local and long-distance traffic compete for carriageway. Remote from such locations, for most of the time traffic generally flows freely. Investment in additional capacity that is prompted by peak hour congestion serves to accommodate more local users, who have the flexibility to choose from a number of routes.

There is a maxim that we cannot build our way out of congestion, which we know from experience to be generally true, and to which the wide use of Digital Navigation contributes. It is common for the public justification of investment in new strategic road capacity to claim the relief of congestion and boosting the economy through improved connectivity. Yet such effects are very short term, negated by the local traffic induced by the new construction that restores congestion to what it had been. Accordingly, we have been deluding ourselves about the economic benefits of road investment.

Lack of alignment with other policies

The Department for Transport recently published new National Road Traffic Projections that include a Core Scenario plus seven variant scenarios. Traffic is projected to grow in all scenarios, by between 8% and 54% by 2060, which contrasts with the widely held view that car use needs to be reduced to meet the Government’s commitment to Net Zero by 2050. Projections of traffic growth would support a future road investment programme, yet would conflict with decarbonisation policies.

The Core Scenario, based on ‘existing firm and funded policies only’, projects 22% increase in traffic to 2060 and 42% decrease in carbon emissions. Yet Net Zero by 2050 is surely a firm government commitment. The Department for Transport published its Transport Decarbonisation Plan in 2021 which claimed that this commitment could be achieved, implying that future funding and policy development would need to constrain carbon emissions from road traffic to zero by 2050. So there is an apparent inconsistency between the 2022 National Road Traffic Projections and the 2021 Transport Decarbonisation Plan.

We are at present midway through the second five-year road investment programme, known as RIS2, worth £27bn over the period 2020-2025 when announced. RIS3 is now being planned. Yet there are headwinds:

  • The potential economic benefits are likely to be overstated, as discussed above.
  • Any increase in road capacity is counterproductive for the Net Zero climate change objective since both tailpipe and embedded carbon would be increased.
  • There are public anxieties about the safety of Smart Motorways in the absence of the hard shoulder, reflected in a critical report from the House of Commons Transport Committee, to which the Government responded by halting new schemes until five years of safety data is available.
  • The Government’s Levelling Up White Paper, published in early 2022, identified a dozen ‘missions’ across departments. The single mission for the Department for Transport is aimed at improving public transport in regional cities towards that achieved in London, a sensible political and social objective. There was no reference to road investment, which is appropriate, given that congestion delays on the Strategic Road Network are less in the Midlands and North than in the South East.
  • Current pressures on public expenditure.

Given these impediments, there is a good case for treating the Strategic Road Network as mature, with the future focus on improving operational efficiency. This is the situation for urban roads, which in the past were enlarged to accommodate more traffic, but nowadays the policy direction is to reduce capacity allocated to general traffic, to encourage active travel and facilitate public transport. Similarly, the aviation sector focuses on operational efficiency – airlines maximising flying time of aircraft, use of allocated routes and passenger load factors; airports (struggling recently) optimising throughput of passengers and baggage; and air traffic management making best use of crowded airspace. The underlying discipline is operations research, not civil engineering, together with modelling and economic analysis of operations, rather than of long-lived investment.

Technological developments

A focus on operational efficiency of the Strategic Road Network would naturally prompt consideration of how best to take advantage of the huge investment in Digital Navigation that has been made, both by providers of the service and by road users. Here a very odd phenomenon is the apparent disregard of Digital Navigation by road authorities, at least as judged by their publications – no reference to satnav in those of National Highways, the Department for Transport, or local authorities (with one exception known to me, Transport for London’s collaboration with Waze). Possible explanations include: preoccupation of highways engineers with civil engineering works; the need to spend the large budget allocated to road investment; the lack of staff with professional background to cope with digital technologies; and road authorities being monopolies, so not subject to competitive pressures to maximise efficiency.

The one constituent of road users that is highly competitive is road freight, particularly that forming part of integrated logistics businesses, which makes extensive use of digital technologies to manage HGV fleets on major roads and delivery vehicles on local roads. We are conscious of this when we order goods online, with a specified delivery date and often a time slot, the ability to track packages, delivery confirmed on the doorstep, and our feedback sought on the experience – all done by algorithm. This kind of operational efficiency needs to be brought to bear on the totality of traffic on the road network.

Road network operators with such experience would naturally want to take advantage of Digital Navigation, one aim being to better cope at times of stress – major incidents, bad weather, peak holiday flows. A second aim would be to optimise use of the network in normal times, including avoiding routing traffic through unsuitable minor roads.

When road users are asked why congestion is a problem, their main concern is the uncertainty of journey time. Digital Navigation provides estimates of journey time in advance, so those who need to be at their destination at a particular time can decide when best to set out; those who are more flexible can avoid the worst of congestion; and all can choose the fastest route. Digital Navigation is vastly more cost-effective as a means to mitigate the impact of road traffic congestion than costly and ineffective civil engineering investment.

While the Department for Transport and National Highways disregard the impact of Digital Navigation on traffic flows, they do pay attention to the possible impact of autonomous vehicles. The National Road Traffic Projections includes a Technology Scenario that envisages autonomous vehicles entering the market in the 2020s and making up 50% of it by 2047. And the government intends to introduce comprehensive legislation governing driverless vehicles when parliamentary time allows.

However, any significant impact of driverless vehicles on use of the road network seems a long way off at best. Eventual benefits would be experienced by vehicle occupants whose time might be available for non-driving tasks, with little scope to increase the operational efficiency of the network. The preoccupation with this future digital technology seems perverse when an existing digital technology, Digital Navigation, is widely used and is capable of changing travel behaviour in ways that are far more cost-effective than civil engineering.

[i] Metz, D. Economic benefits of road widening: Discrepancy between outturn and forecast. Transportation Research Part A, 147, 312-319, 2021.

[ii] Metz D. The impact of digital navigation on travel behaviour. UCL Open: Environment. 2022;(4):05. https://doi.org/10.14324/111.444/ucloe.000034

I posted a blog last year reporting a revision to the Department for Transport’s road traffic statistics that found traffic in minor roads to have increased by 26% between 2010 and 2019. This compared to an increase in traffic on major roads over the same period of 12%. There were two things going on: a statistical sampling problem and a likely real increase in traffic on minor roads.

DfT practice is to monitor a representative sample of minor roads, scaled up to estimate traffic on all minor roads on the network. Because any sample may become less representative over time, a benchmarking exercise is carried out every ten years using a larger sample. This allows data inferred from the original sample to be adjusted retrospectively and a new sample to be established. In the previous 2009 benchmarking exercise the adjustment was fairly small, but not so in the most recent investigation.

Transport for London queried the DfT estimates, which did not square with its own estimates of traffic on the capital that showed a declining trend. Prompted by this discrepancy, the DfT statisticians carried out a deep dive into the methodology, the finding of which were published last September. The outcome has been to revised downward the estimated increase in minor roads traffic from the previous 26% to 10% over the period 2010 to 2019 (see chart above). This amounts to an unusually large revision, and has been accompanied by relegation of the previous report to the archives.

The explanation offered by the statisticians mainly involved comparison of the samples employed in the 2009 and 2019 benchmarking exercises, using GPS data to compare traffic flows, dichotomising into ‘high’ and ‘low’ flow links, and finding that there were 5% more high flow links in the 2019 sample. This was then included as an additional stratification factor for recalculating both exercises. In addition, the benchmarking estimates for London were recalculated, distinguishing Inner London and Outer London, which had not been done previously.

Transport for London, in its Travel in London Report 15 (page 141), notes that the revised DfT data for minor roads traffic in London, although smaller than previously estimated, still represents a substantial upward revision of this component of road traffic in London, whereas the DfT has not revised its traffic estimates for major roads in the capital. The outcome is that whereas in the estimates published before 2019, minor road traffic was put at around 33 per cent of all road traffic in London, the latest estimates have increased this proportion (of a correspondingly larger total) to around 40 per cent.

I have been interested in these estimates of traffic on minor roads since there is much anecdotal evidence that the widespread adoption of Digital Navigation (generally known as ‘satnav’ in the roads context) allows these roads to be used by those without local knowledge, leading to more traffic than desirable in the neighbourhoods affected. The new estimated of the pre-pandemic growth of traffic on minor roads brings this into line with growth on major roads, which might seem to argue against the significant impact of Digital Navigation.

Yet the size of the correction prompted by the benchmarking exercise points the other way, since had the sample of minor roads used to track traffic growth remained representative over the ten-year period, the increase in traffic would have been seen year on year. The fact that this was only recognised from the benchmarking suggests some increased heterogeneity in the sample. My hypothesis is that use of Digital Navigation would lead to growth of traffic on minor roads located adjacent to congested major roads, where the former offer a time-saving opportunity, while minor road located elsewhere would be less affected. The London data showing a growth of traffic on minor roads compared with that on major roads, noted above, is consistent with my hypothesis, given the extent of congestion in this city.

I have been in correspondence with the DfT statisticians on this question. What remains unclear to me is whether they regard controlling for flow characteristics as simply a matter of controlling for mismatched samples, or whether they accept the possibility that use of minor roads changed over the decade in a way that increased the heterogeneity of traffic growth. I have been told that the heterogeneity of traffic growth is not something that their data is currently suitable to verify beyond road class, vehicle type, and regional differences. However, they are looking at other ways of stratifying the sample and at other options for minor road sampling and counting in the future, including use of GPS data.

I have noted previously the likelihood that the use of Digital Navigation is facilitating the diversion of local traffic to new capacity on motorways. More generally, Digital Navigation is changing travel behaviour in ways that need to be better understood for decisions on road investment and other policies, in particular the promotion of walking and cycling for which minor roads are well suited. It is regrettable that the DfT is not able to shed light on these changes as part of its otherwise extensive and comprehensive compilation of road traffic statistics.

According to press reports, the European Commission is in discussion with providers of Digital Navigation services to protect people in neighbourhoods from noise and emissions by adjusting the routing algorithms, which is good news.

The Department for Transport has recently issued a new set of National Road Traffic Projections (known as ‘forecasts’ in the past, ‘projections’ perhaps indicating rather less commitment to the findings). These apply to England and Wales and look ahead as far as 2060. The new projections are derived from the DfT’s National Transport Model (NTM), which has been developed and updated since the 2018 forecasts –  so it is claimed, but see below.

The projections relate to a set of Common Analytical Scenarios, developed by DfT with the aims of better assessing uncertainty in scheme appraisal. There is a Core Scenario plus seven variants illustrating differences in economic growth, regional distribution of population, behavioural change, new technology and decarbonisation. Except for the Behavioural Change scenario, the other variants were created by changing some of the Core Scenario assumptions. For the Core Scenario, relationships between the key drivers of demand and road traffic are broadly assumed to continue in line with historical trends.

A noteworthy feature of the new projections is that traffic is expected to grow in all scenarios, by between 8% and 54% to 2060. This contrasts with the widely held view that car use needs to be reduced to meet the Government’s commitment to Net Zero by 2050, although this is not the DfT’s view. Projections of CO2 reductions to 2060 range from 38% to 98%, depending on scenario.

The Core Scenario is based on ‘existing firm and funded policies only’ and projects a 22% increase in traffic to 2060 and a 42% decrease in carbon emissions. Yet Net Zero by 2050 is surely a firm government commitment. The DfT published its Transport Decarbonisation Plan in 2021 which projected that this would be achievable, implying that future funding and policy development would need to constrain carbon emissions from road traffic to that indicated by the low carbon scenario projections. In which case, one might wonder why publish high carbon projections that go less than half way to achieving Net Zero.

This notion of ‘existing firm and funded policies only’ is stated as encompassing published plans or funded policies. So perhaps the civil servants are drawing attention to the shortcomings of the Transport Decarbonisation Plan, which was pretty vague about the details, particularly about the achievement of behavioural change. Carbon emissions under the Core Scenario are projected to fall initially quite rapidly, but then level off, apparently because ‘the details of future car and LGV regulations to reduce CO2e emissions beyond this point have yet to be finalised.’ (para 4.15 of the NRTP). Certainly, the details of the ‘ZEV Mandate’ remain to be settled – this is intended to oblige manufacturers to sell a specified increasing proportion of zero emission vehicles during the transition – a relevant factor may be the availability of battery production in the UK, which may require government financial support. Perhaps ministers are having a wobble about this Mandate, leading the civil servants to point up the implications for Net Zero of a weakening of policy intent. Nevertheless, it all seems very odd. If no new cars and vans propelled solely internal combustion engines are to be sold after 2030 (hybrids after 2035), then the normal turnover of vehicles would mean continuing decarbonisation until all internal combustion engine vehicles are scrapped (the average age of car at scrappage is around 14 years).

Congestion delays are projected to increase by between 4% and 59% by 2060, depending on scenario, which would provide a justification for creating more capacity. So another possible explanation of the ‘firm and funded’ qualifier is that no account has been taken of a future road investment programme, in particular RIS3 for the period 2025-2030, currently being planned.

In contrast to the Core Scenario, there are three scenarios that project carbon emissions reducing to near zero by 2050. The Vehicle-led and Mode-balanced Decarbonisation Scenarios assume high and fast uptake of EVs and other zero emission vehicles ‘in line with the government’s stated ambitions to end the sale of diesel and petrol cars, vans, HGVs,
and buses/coaches.’ (para 4.48). The Technology Scenario adds a high uptake of connected and autonomous vehicles.

A further scenario of interest is a Behavioural Change Scenario, involving new ways of working, shopping and travelling. This reflects past falling trends in driving licence holding by young people and in trip rates for most purposes, as well as coronavirus pandemic-induced changes in behaviour that are assumed to continue. Some of the latter assumptions are quite striking: 40% reduction in education trips by 2041, 39% in commuting, 41% in personal business, and 55% reduction in visiting friends and relatives (para 3.37). While it is welcome that the DfT is addressing the scope for changes in travel behaviour, these particular assumptions seem on the high side. Nevertheless, the impact of these behaviour changes is surprisingly small – only to level off the growth of car traffic, with van traffic increasing by 45% to 2060 (para 4.39), to compensate for car trips not taken. Car carbon emissions are similar to those of the Core Scenario, indicating that behavioural change in itself is expected to make minimal impact.

The new traffic projections adhere to the traditional practice of predicting demand for road travel driven predominantly by changes in travel costs, population and economic growth, 90% of demand growth being attributed to these factors. A large number of other factors are considered, which is appropriate since they are relevant. The outcome is an extremely detailed formulation of a set of scenarios, which therefore avoids criticism that potentially important factors have been disregarded, but it is then hard to see the wood for the trees.

Big picture

So, let’s stand back from the detail, to see the big picture, which in my view is this: the National Travel Survey has found a gradual decline in per capita travel since the turn of the century, including decline in the average number of trips taken and in distance travelled by car (prior to the pandemic) (see Chart above). This followed rapid growth in car use in the last century, mainly the result of increasing car ownership. But household car ownership has stabilised, with some three-quarters of households owning one or more cars or vans. There was a clear break in trend at the turn of the century, which implies a change in relationships between the determinants of demand and growth of car use. Accordingly, for modelling purposes, such relationships (known as elasticities) need to be forward-looking; assuming continuity of historic trends, as does the Core Scenario, is inappropriate.

The average distance travelled per capita by car depends mainly on three factors: speed of travel, time available for travel, and level of car ownership. The first two seem unlikely to change in the future, and while there has been growth of the number of cars owned within car-owning households, the second or third car tends to be used less than the first. The impact of economic growth and income growth on per capita car use is a second order effect, seen mainly as the purchase of larger, more expensive and fuel-consuming vehicles, notably SUVs. The unvarying travel time constraint, of about an hour a day on average, limits the distance that can be travelled, irrespective of income. The DfT Projections assume that three-quarters of the projected traffic growth is driven by increases in GDP and reduced costs of driving (para 4.7), which seems improbable.

That leaves population growth, which the new traffic projections take from the Office of Budget Responsibility as an overall 4% increase by 2060, and which therefore would have a very small impact on travel demand. The consequences for road traffic growth would depend on the extent to which the additional inhabitants were accommodated in new homes on greenfield sites where car use would be the norm; or at higher density within existing urban areas, where public transport would be relevant. Unfortunately if understandably, the Regional Scenario considers accommodating the population growth in regions beyond the Wider South East, which may be relevant to the Levelling Up agenda but has little impact on overall traffic or carbon emissions.

So, I would not expect much future change in either per capita car use or total road traffic, based on recent trends. This conclusion is at odds with the DfT modelling and so raises questions about the validity of the NTM, which has been in use for over twenty years in a series of versions. The version cited in the new projections is NTM version 2 Rebased (NTMv2R), which is unexpected since a new version, NTMv5, was announced in 2019.

Modelling regressed

NTMv5 was developed as a spatially detailed model to complement NTMv2R by providing additional capabilities for assessing the impact of major new road schemes, packages of transport improvements or spatially based charging arrangements. One particular purpose was to develop scenario-based traffic forecasts arising from changes in population, travel trends, GDP, car ownership, fuel price and road tax. Accordingly, it is surprising that NTMv5 does not appear to have been used to generate the new traffic projections.

One possible explanation is that a peer review of NTMv5 by experienced practitioners made a considerable number of criticisms. The reviewers advised 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 relate to urban travel policy and public transport interventions. In particular, the reviewers were critical of the treatment of urban traffic, observing that the assumed relation between traffic speed and demand growth lacked validity, and that the range of policies aimed at reducing urban car use were not taken into account. Besides, it was 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 concluded that the model could not be safely used to examine policies that relate specifically to London, and queried whether this might apply 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, which is a pretty major qualification.

So perhaps the DfT was unable to rectify NTMv5 to respond to these criticisms, and hence reverted to NTMv2R, which had previously been used to prepare the 2018 National Road Traffic Forecasts. This version was also the subject of peer review, the reviewers noting problems with modelling traffic in London and other conurbations where non-car modes are most competitive. The 2018 Forecasts predicted substantial traffic growth in London, but admitted that this was likely to be over-forecasting because travel behaviour in London and relationships between key variables and road traffic demand can be different to the rest of the country, due to a high use of public transport and significantly higher congestion on roads. This was recognised as known issue with the NTM, which it was intended would be addressed in the future (para 4.33 of 2018 forecasts). However, it is not clear whether this has been done, prior to preparation of the new projections.

There is bound to be feedback from congested road capacity to travel demand. In the ‘vision and validate’ approach, nowadays effectively adopted by cities, the vision of the balance between the twin functions of roads – movement and place – means that travel demand must be managed. This contrasts with the earlier ‘predict and provide’ perspective, where forecasts of traffic growth led to proposals to increase road capacity. If our vision now includes Net Zero, the presumption of increased road capacity is problematic, and the modelling should take account of capacity constraints on demand for road travel. Given that over 80% of the UK population live in urban areas, models need to be responsive to urban traffic conditions.

The validity of the NTM is therefore questionable. The modelling suite used to prepare the present projections is complex and opaque, hence it is not possible for those other than DfT modellers and their consultants to understand what has been achieved and what has not. The peer reviews provide an exceptional opportunity to look under the bonnet, and what was found make one doubt whether the NTM in its various versions is reliably roadworthy. And that’s before the problems associated with specifying scenarios to reflect policy uncertainties.

One intention in creating NTMv5 was to make this important model transparent to external stakeholders, which NTMv2R is not. Lack of transparency and accessibility contrasts unfavourably with the online Carbon Calculator of the Department for Business, Energy and Industrial Strategy, open to all.

Projecting future road traffic volumes is not an end in itself, rather it serves policy purposes. Projections of growth of both traffic and congestion delays would help justify a further major road investment programme. Projecting carbon reductions of 98% meets the Net Zero objective. Arguably, the modellers have struggled to reconcile both policy requirements, but have fallen short.

This blog was the basis for an article in Local Transport Today 24 January 2023.

The British government has long been keen on encouraging the prospect of what were initially known as ‘connected and autonomous vehicles’ (CAV). In 2015 it set up the Centre for Connected and Autonomous Vehicles to stimulate the development of the technology and steered funds into the sector via the Transport Systems Catapult. Typical of recent bullish statements by DfT ministers is this from Grant Shapps, when Transport Secretary, earlier this year:

‘The benefits of self-driving vehicles have the potential to be huge. Not only can they improve people’s access to education and other vital services, but the industry itself can create tens of thousands of job opportunities throughout the country. Most importantly, they’re expected to make our roads safer by reducing the dangers of driver error in road collisions. We want the UK to be at the forefront of developing and using this fantastic technology, and that is why we are investing millions in vital research into safety and setting the legislation to ensure we gain the full benefits that this technology promises.’

There’s no doubting the enthusiasm, but is this just hype, or is there a reality underpinning the vision? And what exactly is the vision anyway? It seems to be principally focussed on re-imagining the existing private car as a vehicle that no longer needs a driver behind the wheel, and which can whizz its occupants around in robotic mode, avoiding collisions and improving safety, whilst allowing the passengers to get on with other tasks, or simply enjoying the ride and the view – or maybe having a nap.

Trials of such driverless cars on public roads are taking place in a number of countries, mostly with a human ‘safety driver’ still on board, but this requirement has been dropped in some US and Chinese locations where traffic conditions are deemed favourable. Yet the prospects remain uncertain, so it is timely that the House of Commons Transport Committee has initiated an inquiry into self-driving vehicles.

I am specifically exploring here the prospects for such driverless cars ever becoming widespread, acceptable and effective in the foreseeable future. I’m not considering the possibilities of driverless multi-user pods or rapid transit buses on at least semi-segregated roads, where some deployment has already taken place. Nor do I discuss the scope for freight vehicles to operate in platoons on inter-urban motorways, where a recent UK trial found the hoped-for improvements in fuel use to be disappointing.

The government published a substantial policy document in August of this year entitled Connected and Automated Mobility 2025, jointly presented to Parliament by the Secretary of State for Transport and the Secretary of State for Business, Energy and Industrial Strategy.

Note that Automated has replaced Autonomous, perhaps reflecting a scaling down of expectation. Note also that Mobility has replaced Vehicles, hence CAM rather than CAV, a sensible but small generalisation. But note also the absence of reference to Connected within the new document: the whole emphasis is on automation of individual vehicles, with little mention of the possibilities of connectedness between vehicles. In this, the government is following the prevailing mindset of the automotive industry, tech start-ups as well as established vehicle manufacturers, who see autonomy easier to achieve than connectedness between vehicles of different manufacture and type.

The self-driving vehicle concept is seen as the application of CAM technologies with greatest commercial potential. But for deployment to happen, safety must be assured. So in 2018 the government asked the Law Commission to develop the legislative framework for a safety regime. The Commission’s final report, also published earlier this year, will be the basis of legislation that the DfT will bring forward.

Legal consequences

Because, to be useful, a self-driving vehicle will need to be able to drive itself for at least part of a journey, there are profound legal consequences. The human driver can no longer be the principal focus of accountability for road safety. Instead, new systems of safety assurance are needed, both before and after vehicles are allowed to drive themselves on roads. The legal framework has to cover both self-driving functions, where a user must be able to take over control when the vehicle cannot cope – for instance in poor visibility-  as well as more advanced automation when the vehicle is able to cope under all conditions.

The Law Commission proposes three new legal actors:

  • Authorised Self-Driving Entity (ASDE) – the vehicle manufacturer or software developer who puts a self-driving vehicle forward for authorisation to the regulator.
  • User-in-charge (UiC) – the human in the driving seat while the vehicle is driving itself, who can take charge if the self-driving function cannot cope.
  • NUiC operator, a supervisory system responsible when there is no user in charge, to navigate obstructions and deal with incidents.

There will need to be regulators for new functions:

  • Vehicle type approval.
  • Authorisation to self-drive.
  • In-use safety regulation.
  • NUiC operator licencing.

The proposals of the Law Commission will need to be enacted in legislation, to make possible the government’s intention to make the UK an attractive place for the deployment of self-driving vehicles, even though the main development of the technology is taking place in the US, where there is considerable diversity of regulatory regimes across the states. However, the comprehensive legal framework may deter some prospective developers.

Ride-hailing operators such as Uber, who have aspirations for a driverless future, might hope to save the costs of the driver. But under the proposed regime they would need to own the vehicles and accept responsibility as the NUiC operator for oversight of operations, and possibly also to be the ASDE. This would be a large and costly change from the company’s current capital-light business model, where ownership of the vehicles lies elsewhere.

Electric vehicle maker Tesla’s approach to automation has meanwhile been to incorporate the hardware into existing privately-owned vehicles and to progressively improve the software over time to get to the point of implementing what is being marketed as ‘Full Self-Driving’ capability. Taken literally, this would also require Tesla to be licenced as a NUiC operator, with oversight of its whole fleet of vehicles on the road, which is hardly conceivable. So if they use the automated mode, Tesla drivers would need always to stay alert and be prepared to take charge in the event of the unexpected.


A key question in this discussion is the appropriate level of safety required for a self-driving vehicle. The Law Commission took the view that this is best decided by ministers, in the light of judgement of the public’s acceptance of risk. The view of the government, set out in the recent policy document, is that self-driving vehicles should be held to the same standard of behaviour as that expected in road traffic legislation for human drivers: ‘competent and careful’. This standard is higher than that generally enforceable now on the average human driver – who include, for example, drivers who are fatigued, distracted or under the influence of drink or drugs- despite this not being the behaviour that is expected of them.

The ‘competent and careful’ standard appears to be the minimum required politically. Anything less would hardly be publicly acceptable. But does it do the trick? On occasion, self-driving vehicles will inevitably be involved in crashes with fatalities. ‘Competent and careful’ implies that the self-driving vehicle could not be blamed. The fault would be attributed to the other drivers (‘human error’) or to vehicle- or road-related defects. Yet would it be possible to demonstrate such blamelessness in practice, when the other parties to the crash would be seeking to shift responsibility?

In Britain there is one fatality per 140 million miles driven, so deaths involving self-driving vehicles could be expected to be exceedingly rare events. But when they do occur, they will surely  attract much public attention. As a result, there may well be pressure to tighten safety standards further, which, done in response to public anxiety, may undermine the general acceptability of self-driving vehicles. There is therefore a good case for a higher initial safety standard than ‘competent and careful’ to be set.


The practical development of vehicle automation for general deployment is proving more difficult than the pioneering technology optimists had hoped. Apart from getting the technology to the point of being publicly acceptable, there is an evident need to develop viable business models consistent with the expected regulatory regime. And that means asking who will buy the vehicles? This in turn will depend on how purchasers perceive the benefits. In this regard, the practical benefits of vehicle automation remain unclear.

Proponents point up the safety benefits, especially in the United States where almost 39,000 people were killed in motor vehicle crashes in 2020, a fatality rate of 12 per 100,00 population, compared with 2.3 for the UK. Given that human error and risky behaviour is said to be responsible for 90% or more of fatalities, it would seem a reasonable expectation that the ‘robot driver’ of a self-driving vehicle could do better than fallible humans. On the other hand, robots suffer from their own shortcomings, tending to be less effective at perceptions involving high variability or alternative interpretations. In particular, robots would find it difficult to engage in the kind of visual negotiation that occurs between human drivers to settle which gives way when space is tight. Besides, the driving performance of a robot would need to be very similar- or better- than that of a human driver to ensure public acceptability. A self-driving vehicle that proceeded particularly cautiously to meet safety requirements could be unattractive to the purchasers, and an irritation to other road users . So the robot driver would effectively need to learn how to drive like a human.

Another claimed benefit is that automation might increase the capacity of existing roads by allowing these safety-conscious vehicles to move with shorter headways, that is, with a smaller distance between them than the recommended two-second gap on fast roads. The more precise control exercised by a robot might also smooth traffic flows and allow the use of narrower lanes. However, such increases in capacity would seem likely to be possible only on roads dedicated to self-driving vehicles, since the presence of conventional vehicles, not to mention cyclists, motorcycles and pedestrians, would require standard spacing to be maintained. In any event, in line with current experience, any increase in capacity would be expected to attract additional traffic, so that long term congestion relief would not be expected.

Automation that allowed an increase in road capacity might anyway be of interest to a road authority, as a public benefit, but not to individual vehicle owners if they had to bear the cost of the necessary technology. Because self-driving vehicles would be capable of operating empty, for example when returning to base after dropping off the occupant, and thus not needing to pay to park, they could add to the traffic miles generated and hence to congestion. Conventional taxis operate without a passenger while seeking a fare, of course, but privately owned vehicles without occupants would be a new source of traffic. All this is before any consideration of how they would be licenced and the fee, and/or any road user charges they must pay- whether the same as, or different to, conventionally driven vehicles.


One obvious problem of driverless vehicles is how they can happily enter the vehicle population alongside conventionally-driven vehicles The prospects for widespread vehicle automation on existing roads with mixed traffic seem very uncertain. The driving task on motorways might be lessened in good visibility and in the absence of road works, but the driver would need to be immediately available to take control in adverse situations – and when going into general traffic. There are some low-speed environments that might accommodate driverless vehicles, including campuses, business parks and other new developments with extensive road space, and some such deployment has taken place; in these circumstances driverless shared-use pods could be a cost-effective transport technology. Yet it is hard to see driverless vehicles successfully negotiating historic towns and cities with complex road layouts, often narrow streets, extensive kerbside parked cars, cyclists and randomly moving pedestrians.

This impediment to automation in general traffic in urban areas is particularly relevant to the idea of driverless taxis that could be attractive to ride-hailing operators such as Uber, to avoid the cost of the human driver and spread the extra capital cost of the vehicle through intensive use. On the other hand, there would be the potential cost of ownership of fleets of automated taxis, rather than the current model of ride-hailing operators where drivers own their own vehicles. Besides, a driverless taxi system operator would need to exercise oversight of the activity of each vehicle in their fleet, to deal remotely with incidents and navigate obstructions, which would add to costs. It is certainly possible that the relatively unskilled human taxi driver in their own car may remain a lower cost option than the robot driver in a specially provided one.

The way forward thus remains unclear. Indeed, after more than a decade of development of autonomous vehicles, the early excitement and optimism have been followed by some disillusion as the problems of achieving and implementing an acceptably safe product have been recognised. The recent decline in the value of technology stocks and venture capital investments suggests that finance to support further development of vehicle automation may be harder to come by. Indeed, Argo, an autonomous vehicle tech start up funded by Ford and VW, is shutting down, evidence of uncertain prospects for the technology. Accordingly, it would be premature to predict the eventual outcome, both in timing and extent of deployment. Who can judge whether, as enthusiasts for the technology assert, children born today will not need to learn to drive a car?

The major transport innovations of the past have been those that made possible step-change increases in the speed of travel – the railway and the modern bicycle in the nineteenth century, the internal combustion engine for road vehicles and the jet engine for aircraft in the twentieth century. These step-change increases in speed, and thus reductions in journey times, permitted increased access to people and places, opportunities and choices, which were the benefits of harnessing the energy of fossil fuels for the motive power of mobility. In contrast, it is unlikely that automation would increase the average speed of travel on the existing road network, which is constrained by safety and congestion. Accordingly, the benefits of vehicle automation are much more likely to take the form of improved journey quality, and hopefully safety, and the possibility of doing other things whilst on the move – particularly those that have come with the digital information and communications era . It remains to be seen to what extent purchasers of driverless vehicles will be willing to pay for these benefits – or if they can achieve them by adapting to wider new mobility thinking in other ways, particularly at a time of changing inter-generational attitudes to the ownership of vehicles personally, and their use.

The UK government has been very supportive of vehicle automation, in particular aiming to put in place a comprehensive legislative regime based on the thorough analysis by the Law Commission. Yet there is only limited commercial development of the technology underway in Britain, so the benefits for both industrial and transport policy do not seem to be that great. A more important technology priority for road transport policy has surely to be the switch to electric propulsion and the quest for transport decarbonisation.

This blog is the basis for an article in Local Transport Today dated 14 November 2022.