The National Infrastructure Commission (NIC) has published its final report on Rail Needs Assessment for the Midlands and the North. This had been commissioned by the government to support its intention to prepare an Integrated Rail Plan to identify the most effective scoping, phasing and sequencing of relevant investments and how to integrate HS2, Northern Powerhouse Rail, Midlands Rail Hub and other proposed rail investments.

The projection of benefits departs from the standard transport cost-benefit analysis in which the main economic benefit to users is the saving of travel time. As set out in the annex to the report, the Commission’s approach is to assess the potential for rail investments to support both economic growth and improved quality of life, as these arise through the increase in density in city centres. Such density increase generates the well-known boost to productivity from agglomeration, an approach which is innovatively extended to capture the consumption impacts of agglomeration through access to increased amenities. The latter replaces conventional time saving benefits.

The NIC analysis recognises increased wages for workers accessing better paid jobs through increased rail capacity. Improvements in rail connectivity between cities and towns are also estimated, which contribute to increased productivity.While changes in life cycle carbon emissions and in natural capital are estimated, changes in land use are not.

The NIC’s methodology is used to compare packages of investment, formulated according to both overall cost and emphasis on enhancing links, regional and long distance. Broadly, investment in regional links comes out as a bit more attractive than in long distance links, which implies less importance to building the eastern leg of HS2 to improve journey times to London than in reinforcing connections within the regions. However, in relation to the cost of investment, none of this additional rail capacity seems very attractive, although the Commission concludes that with some assumptions about the non-monetised benefits, its analysis suggests the full benefits should meet or outweigh the costs of the packages. In this respect it is similar to the conventional economic analysis of HS2.


The NIC analysis is particularly interesting in that it is based on the recognition that travel time savings are not a satisfactory basis for estimating the benefits of transport investment, given that average travel time has not changed for at least half a century despite huge investment justified by the expectation of time savings. So the NIC focuses on the benefits of increased density of city centres that could be made possible by better rail connections. The established estimation of productivity benefits arising from higher density, the agglomeration effect, is extended to amenity benefits to consumers, a welcome innovation. Nevertheless, valuation of agglomeration effects is indirect, depending on econometric analysis, as opposed to changes in land use and value that are directly observable. So the omission of changes in land use from the NIC analysis is a pity.

The RAC Foundation has published a report on how information can be conveyed to drivers via connected vehicles. This assessed representative possibilities including In-Vehicles Signage (IVS) to display road signs and warnings to the driver inside the vehicle, and Green Light Optimal Speed Advisory (GLOSA) which tells drivers what speed to adopt to pass through the next set of traffic signals on green. The report discussed the obstacles to implementing these technologies, which it suggested arise mostly from organisational, institutional and human issues.

What was not adequately considered was the elephant in the room – the existing digital navigation (satnav) services, whether available free of charge as smartphone apps (Google Maps, Waze and others) or embedded as an integral part of the vehicle equipment. While the report mentions satnav devices as already providing some signage information, it envisages that a key element of the IVS concept is the ability for highway authorities to communicate directly with drivers, so that they can give them information they want them to receive (for example hazard warnings), as opposed to a satnav provider generating messages themselves.

Yet given the widespread use of digital navigation, it seems likely that the prime deciders of what information is conveyed to drivers will continue to be the satnav providers, not the highway authorities. The latter would need to make timely information available to the former if drivers are to benefit. But while highway authorities are subject to statutory regulation, providers of digital navigation are unregulated and are free to choose what information to provide to road users.

More generally, digital navigation has transformed how very many motorists use the road network, particularly for occasional, as opposed to regular, journeys. A choice of routes is offered at the outset of the trip, with estimated journey times, which mitigates the main perceived problem with traffic congestion – the uncertainty of time of arrival. Alternatives may be offered en route in response to the build-up of congestion. However, because the service providers of digital navigation are very secretive about their methodologies, we have little idea of the impact of their guidance on the overall functioning of the road network. For instance, we do not know if the rerouting in response to a crash on a motorway is optimal for users of the whole road network, or for drivers responding to the advice, or for neither.

There have been many anecdotal reports of digital navigation resulting in problematic use of minor roads (‘rat running’). While traffic on A and B class roads in London has been broadly stable since the mid-1990s, traffic on C roads, which had also previously been stable, increased from 5.4 billion miles in 2009 to 9.3 billion in 2019, suggestive of substantial impact of digital navigation devices.

There is clearly a case for better coordination between satnav providers and highway authorities to optimise the impact of digital navigation for all road users and to minimise environmental harms. There is in fact a legal basis for achieving this, although it has not been put into practice. The Road Traffic (Driver Licencing and Information Systems) Act 1989 requires dynamic route guidance systems that take account of traffic conditions to be licenced by the Secretary of State. This was enacted to facilitate the introduction of a pilot route guidance system that had been developed by the Transport Research Laboratory (then part of the Department for Transport), which in the event was not taken forward. A licence could include conditions concerning roads that should not be used and information to be supplied about traffic conditions.

There is a need for a review of the impact of digital navigation on the functioning of the highway system with a view to identifying ways of benefiting road users. It is very likely that exploiting digital technologies would be far more cost effective than employing costly civil engineering technologies to increase capacity.

The Department for Transport recently published a document outlining its approach to updating its Transport Analysis Guidance (TAG) ‘during uncertain times’. Two factors imply reduced travel demand: the long-term assumption about GDP growth has been reduced from 1.9% pa to 1.4%; and population growth from 0.3% to 0.15%, reflecting exit from the EU. New values for carbon emissions are also to be provided.

What was missing, I thought, was consideration of the need to update modelling, given the DfT’s intention to published a transport decarbonisation plan. Yet there are a number of shortcomings to existing modelling techniques, particularly in respect of estimating the impact of interventions aimed at reducing transport carbon emissions.

National models

The National Transport Model (NTM) is used to generate the Road Traffic Forecasts, most recently published in 2018. Scenario 7 addresses the consequences of a shift to zero emission vehicles and projects a 51% increase in road traffic 2015-2050, compared with 35% for the reference case, reflecting a reduction in fuel costs and assuming no changes to government policy on taxation.

There are, of course, sensitivities about making assumptions about future taxation. Yet mode share is influenced by levels of tax and subsidy. Arguably, both the growing proportion of SUVs and the decline in bus use have been facilitated by the freezing of road fuel duty since 2011. There is therefore a need for an approach to modelling that allows the full range of policy options to be explored, including changes in relative costs. One possibility might be to seek a remit analogous to that given by HMT to the National Infrastructure Commission, which must be able to demonstrate that its recommendations are consistent with gross public investment in infrastructure of between 1.0% and 1.2% of GDP in each year between 2020 and 2050.

Taxation aside, the growth of traffic projected in Scenario 7 is implausible. Travel time has been measured in the National Travel Survey (NTS) for the past 45 years and on average has remained close to an hour a day. This implies that the time available for travel is constrained. A reduction in fuel costs therefore would not lead straightforwardly to an increase in distance travelled, which would only arise if either higher speeds were possible (not to be expected from a switch to zero emission technology) or higher car ownership occurred (not assumed in the model).

More generally, the three key parameters of the NTS – average travel time, trip rate and distanced travelled per year – have not increased since 2000. I would expect any model to hold these per capita parameters unchanged on a central case projection, unless there were to be a clear causal explanation for a different trend. Population growth is then the main determinant of future traffic growth, but the relative mode share would depend on where the additional inhabitants live: to the extent they are housed on greenfield sites, car use would be important; to the extent they are located within existing urban areas, investment to support active travel and public transport would be relevant. My understanding is that the National Trip End Model (NTEM) provides a single national set of assumptions about demographic factors, and therefore does not allow consideration of policy options in respect of spatial location. If public transport and active travel are to be ‘the natural first choice for daily activities’, then the spatial location implications of population growth need to be incorporated into modelling.

Regional models

Beneath the NTM, there are a number of regional transport models. Those commissioned by Highways England are mainly (entirely?) based on the SATURN software first developed in 1980. Despite very considerable ex ante efforts to refine and update such models, there is a dearth of ex post analysis of modelling validity. A partial exception is the detailed monitoring of traffic for each of the three years after opening of the widened M25 between J23 and J27. Small time savings were found at year one, but these were lost by year two due to increased traffic volumes. The forecast traffic volumes derived from the model were less than observed and the forecast increase in traffic speed did not materialise, hence negating the economic case for the investment. The additional traffic generated externalities beyond forecast, including carbon emissions.

More generally, the whole area of regional modelling lacks transparency. Highways England does not appear to publish information on its models and their validation. It would be timely to review the validity of such models.


Current UK transport modelling as a whole seems mainly concerned to update, refine and apply long established approaches. The bulk of modelling expertise is found within the consultancies, who are concerned to meet the needs of their clients using accepted methodologies, often to provide formal justification for a preferred investment. The Department is conservative in its requirements. Consultants therefore have little incentive to develop innovative approaches. Fresh thinking is needed, yet there is no academic centre of expertise in transport modelling where innovation could be expected.

Established models do not seem well suited to supporting a strategy aimed at achieving net zero transport carbon emissions by 2050. A related problem is the lack of data for model calibration in respect of the impact of the range of possible policy interventions. For instance, if the encouragement of active travel is successful, from which mode does the shift occur? The experience of the cycling city of Copenhagen is that car use is only slightly less than in London, but public transport mode share is half that of London. This suggest that we can get people off the buses onto bikes, but that it is more difficult to get them out of their cars, even in a city where all motorists are familiar with cycling.

Decarbonisation will be a long game, during which we should be able to gain understanding of the consequences of the various policy interventions, even though these will be difficult to model at the outset. It would be desirable to initiate the development of new models soon, ready for when calibration data becomes available.

The main focus of recent interest in the area of ‘Connected and Autonomous Vehicles’ has been autonomy – driverless cars – where both tech companies and auto manufacturers are attempting to get the technology to the point where it could be used on real roads. In contrast, while the idea of connected vehicles has been around for some years, progress has been slow. There are two kinds of connectedness: vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I); collectively V2X. A recent US webinar and report provided some illumination.

The main motivation of V2X is to improve safety, a real issue in the US where more than 6000 pedestrians a year are killed in traffic-related incidents. The aim is to enhance visual line of sight communication by using other parts of the electromagnetic spectrum.

There are two means of connectivity: WiFi based on a dedicated short-range communications (DSRC) standard approved in 2010 but with little implementation by manufacturers; and a cellular connection (C-V2X), based on smartphone technology, which could connect vehicles directly, independent of the base stations used for normal voice calls. Initially, 4G technology is being used, with the intention to move to the much faster 5G as that is rolled out. The hope is that vehicles will also be able to sense the presence of pedestrians by detecting their smartphones. The V2I capability depends on road authorities being willing to install connectivity in traffic signals and other roadside signs, which they may be reluctant to afford.

Deployment of V2X depends on whether this is mandated by national authorities. The Chinse government is supporting C-V2X. On the other hand, EU states voted against a proposal of the European Commission to adopt a WiFi standard, and the US government has also not supported a similar approach. In the absence of a policy mandate, deployment depends on consumer demand. The VW Golf launched in 2019 has WiFi V2X connectivity. Ford is planning to introduce C-V2X in 2022.

However, consumer interest and willingness to pay for a range of driver assistance and connectivity technologies has remained lukewarm for several years, with substantial levels of ambivalence and even scepticism towards these offerings. Enhanced safety, while desirable, may be insufficient a selling point. And having two technologies in use will not help.

Apart from safety, the other potential use of V2X connectedness would be to increase effective road capacity by permitting shorter headways between autonomous vehicles. This benefit depends on the implementation of robot-driven vehicles with faster reaction times than human drivers. Shorter headways would increase the risk of crashes. Crashes involving autonomous vehicles require allocating responsibilities for fault, more difficult where V2V communication is involved between vehicles of different make under different ownership. Moreover, the benefit from increased road capacity accrues to road authorities more than to road users, so the commercial incentive to develop V2V for this purpose seems quite limited.

Altogether, the case for developing vehicles connectedness does not seem strong.

The Department for Transport (DfT) is consulting on a new aspect of vehicle automation – the Automated Lane Keeping System (ALKS) . Already available are advanced driver assistance systems that include adaptive cruise control and lane keeping, to govern longitudinal and lateral movements, respectively. Inclusion of both would amount to SAE Level 2, referring to the generally accepted categorisation of vehicle automation.

The consultation concerns a proposal to permit a move to SAE Level 3, by relieving the driver of a light vehicle of responsibility for longitudinal and lateral control at speeds of up to 60 kph (37 mph) on motorways. This would allow drivers to attend to other tasks in heavy, slow moving traffic on modern roads not used by cyclists and pedestrians.

DfT hopes that automation will make roads safer, given that 85% of road collisions in Great Britain that result in injury involve human error. However, a requirement for the operation of ALKS is that the individual does not need to monitor the vehicle if, inter alia, the vehicle can ‘avoid collisions which a competent and careful driver could avoid’ (consultation document para 3.13). Presumably, moving at low speed on a traffic-congested motorway ensures that the probability of an injury accident is very low. Hence while ALKS in these circumstances would not improve safety, it would not be likely to worsen it.

The benefits to road users of low-speed ALKS are relatively modest, and vehicle manufacturers may not think it worthwhile developing this SAE Level 3 technology, with the costs involved that would need to be recovered from sales. However, the consultation raises the possibility of ALKS operation at up to 70 mph, a speed at which fatal and injury accidents occur and where a timely and effective response of the driver to a transition demand would be essential. Doubts about the feasibility of such a response deter many developers from pursuing Level 3 technology, preferring to jump to Level 4 where there is no role for the driver in a defined environment. On the other hand, Level 3 low-speed ALKS may be easier to deploy on motorways, as a first step to autonomy, than Level 4 technology at higher speeds.

The attractions for manufacturers of low-speed ALKS may depend on the prospects for eventually offering this technology for use on motorways at all legal speeds, which would be far more attractive for intending purchasers of vehicles but more a good deal more demanding technically. It would therefore be important for DfT to indicate the likely safety requirement for all-speed ALKS. This would need to be more stringent than the ‘competent driver’ requirement, to meet both high public expectations for transport safety when individuals are not in charge of a vehicle, as well as the aim that automation should make roads safer.

The Prime Minister has announced expenditure of £2bn to kickstart a ‘cycling and walking revolution’. While this reflects his personal predilection for cycling, as was evident when he was Mayor of London, there are two pressing policy imperatives. The coronavirus pandemic necessitates reduced occupancy of buses and trains, for which cycling and walking provide healthier alternatives. And in the longer term, active travel, as it is termed, has a part to play in plans being developed to decarbonise the transport system, as well as to improve urban air quality.

Cities are promoting active travel in response to the pandemic. Manchester has committed £5m to enable socially-distanced cycling and walking.    Sadiq Khan, the current Mayor of London, has reallocated road space with the aim of increasing walking five-fold and cycling ten-fold.

A ten-fold increase in cycling in London would take the present 2.5% share of journeys to the level found in Copenhagen, currently 28%, in a city that has excellent cycling infrastructure and a longstanding cycling culture. However, 32% of trips in Copenhagen are by car, only a little less than London’s 35%. Aside from cycling, the other big difference is public transport use: 19% of journeys in Copenhagen versus 36% in London.

This indicates that we can get people off buses onto bikes, which are cheaper, healthier, better for the environment, and no slower on congested urban streets. But it is harder to get people out of their cars, even in Copenhagen where everyone has experience of safe cycling. Features that make the car attractive include the ability to carry people and goods, including the stuff your lug around in the boot; and trips a bit long for a bike ride, or where you need to appear well dressed at the destination. And many people positively like cars and driving for feel-good reasons – witness the enormous choice of models, including the current fashion for high fuel consumption sports utility vehicles.

Cars typically are parked for 95% of the time, which makes an economic argument for those keen on sharing vehicles or journeys. But conversely, the willingness to pay substantial sums for an item used for only 5% of the time indicates the value people place on personal ownership and the mobility that this make possible.

The fundamental attraction of the car is the access it allows to people and places, opportunities and choices, at least when roads are not too congested and when it is possible to park at both ends of the journey. To achieve access to the wide range of destinations to which we have become accustomed, within the time available for travel during the busy day, the car is the most efficient mode of travel for moderate distances. If you live in a village without a car, and with limited or non-existent bus services, your opportunities and choices of work, shops and services are limited. Acquire a car and the possibilities are expanded substantially. Although there are many ideas and initiatives for replacing cars outside cities, the cumulative impact is unlikely to be transformative.

Where it is certainly possible to replace cars is in cities, where roads are congested and parking is limited. Car use in London was at its peak in the early 1990s, accounting for 50% of journeys. Subsequently the population increased while road capacity for cars was reduced to make room for bus lanes, cycle routes and pedestrian space, and at the same time there was substantial investment in rail capacity, all of which reduced car use to the current 36% of journeys. But beyond densely populated cities, the cost of urban rail is hard to justify, and buses on congested roads are not an attractive alternative to car use. On the other hand, buses on dedicated routes free of general traffic – Bus Rapid Transit – can be attractive as a lower cost alternative to rail.

The pandemic lockdown showed how we could make substantial changes to our travel behaviour, some of which are likely to be long-lasting – less travel for commuting, shopping and on business. Yet such decreases could well be offset by increases in other kinds of trips, reflecting our need to get out of the house and engage with the wider world.

There is much uncertainty about the extent to which we can count on changing travel behaviour to contribute to transport decarbonisation and improve urban air quality. We will therefore need to rely largely on technological change, by replacing oil as the main fuel for motive power – electrification of cars, vans and most trains.

Policy to promote walking and cycling is undoubtedly worthwhile and will yield both health and environmental benefits. Yet the attractions of motorised mobility and the experience of Copenhagen suggest that the main impact will be to attract people from public transport, rather out of their cars.

This blog was the basis for an article in The Conversation on 24 August 2020

Lynn Sloman and colleagues of Transport for Quality of Life (TQL) issued a report about carbon emissions arising from the Department for Transport’s second Road Investment Strategy (RIS2). Their detailed analysis reaches the conclusion that the increase in CO2 from RIS2 would negate 80% of potential carbon savings from electric vehicles on the Strategic Road Network (SRN) between now and 2032.

This conclusion struck me as surprising. Although annual expenditure on new capital projects for the SRN has been running at over £2 billion a year, civil engineering is very costly and we don’t get much extra capacity for our money. The recent rate of addition of lane-miles to the SRN has been 0.5% a year, which is less than the rate of population growth. So how could such a low rate of addition of capacity have such a large adverse impact on carbon emissions? We need to question the TQL calculations.

TQL argues that the RIS2 road schemes will increase carbon emissions in a number of ways, particularly by increasing speeds and inducing more traffic, both of which they believe are underestimated in conventional scheme appraisal. They therefore estimate the additional cumulative carbon emissions from these sources, both put at around 6 Mt CO2 for the period 2020-2032. But I wonder if there is not some overstating here, given that more traffic would tend to reduce speeds. For instance, for a scheme to widen part of the M25, I found that outturn traffic flows were higher than forecast, such that there was no increase in traffic speed.

TQL estimate that RIS2 would increase carbon emissions by 20 Mt CO2 for the period 2020-2032, including carbon from construction. This is then compared with the difference in carbon emissions between two scenarios from the DfT Road Traffic Forecasts 2018, the Scenario 1 reference case and Scenario 7 high electric vehicle case, which amounts to a reduction of 25 Mt, hence the conclusion that the increased carbon emissions would negate 80% of the benefit of the shift to EVs.

There are, however, problems with this estimate of carbon reduction from EVs. Scenario 7 assumes no tax on EVs to replace fuel duty, so that the cost of motoring decreases substantially (by 60% by 2050), hence a projected large increase in traffic compared with Scenario 1 (50% increase by 2050 compared with 35% for the reference case). Whatever the realism of the assumption about tax, such a large increase in traffic is implausible as the consequence of electrification. Average travel time has remained constant at about an hour a day for the past 45 years at least, hence to travel further it would be necessary to travel faster, which will not happen through a change in propulsion. The problem is that the Road Traffic Forecasts derive from the National Transport Model, which does not recognise travel  time constraints.

An assumption that electrification has no effect on traffic volumes would substantially increase the scale of carbon reduction under Scenario 7, to which could be added the benefit of bringing forward the phase out of non-electric cars and vans earlier than 2040, as assumed in that Scenario. And if we reduce the additional carbon from the RIS2 programme to allow for some overstating, then we could arrive at a less pessimistic conclusion than the TQL authors about the carbon impact of this programme on future overall SRN emissions.

Nevertheless, despite these caveats, I agree with the conclusions of the TQL report that RIS2 is anachronistic, and that cancellation would free up substantial investment for better uses, not least fast broadband to lessen the need for travel, both for commuting and on business. The SRN is under greatest traffic stress in or near urban centres during the morning and late afternoon peaks, when car travel to and from work interferes with long distance road users. The economic case for road investment needs to be reconsidered in the light of changes in daily travel prompted by the pandemic.

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

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

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

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

I previously noted publication by the Department for Transport of its Second Road Investment Strategy (RIS2). DfT has now issued an economic analysis that concludes that the new programme represents high value for money. I had hope that this document would provide substantiation of the £27 billion, 5-year road investment programme but I was disappointed.

The summary states that overall RIS2 is High Value for Money, meaning £2 return for every £1 spent (Benefit-Cost Ratio of 2). Yet new commitments of major capital enhancement schemes yield a BCR of 1.5, which is unimpressive. The analysis is minimal, offering no breakdown into individual schemes, where some might be expected to have a BCR of 1 or less if the average is 1.5.

These estimates are based on the now rather dated Road Traffic Forecasts published in 2018, which included five distinct scenarios, yet no indication is given as to how the BCR would vary with scenario. The estimates are also derived from new but unpublished regional traffic models, asserted to be ‘world leading’.

I previously pointed out a major discrepancy between traffic forecasts and post-opening outturn for the smart motorway widening of the M25 between Junctions 23 and 27. These forecasts were generated by a regional model of the kind now in general use by Highways England, based on SATURN software that originated in the 1980s. The purpose of these models is to estimate travel time savings that arise from adding carriageway, which feed into an economic model. Yet in the M25 case, no time savings were observed beyond year 1 after opening, putting the validity of such models  in doubt.

The new DfT analysis frequently asserts that its analysis is robust (15 times, in fact), which is usually a sign of intellectual insecurity. In fact, the analysis is pretty thin and seems intended to justify a road construction programme developed in earlier era, before we have had a chance to assess the impact of the coronavirus pandemic and what this might mean for travel demand and for public expenditure priorities, urban vs. inter-urban transport vs. broadband.

An on-line meeting organised by Local Transport Today on 19 June was concerned with the future of car travel after the coronavirus pandemic. I contributed the following thoughts.

The average distance travelled by car in the UK per person ceased to grow at turn of century, following strong growth in the last century. This phenomenon has been called ‘Peak Car’, but ‘Plateau Car’ would be a better term, given the 20-year flat trend. But with the coronavirus pandemic, we have three new influences that could affect the trend of car use in the longer run.

First, a natural preference for the car in place of public transport during the pandemic, which will add to road traffic congestion. Second, less road space for cars in urban areas to allow more room for active travel, both as response to the pandemic and to promote longer term reduction in carbon emissions and improve urban air quality; this also will tend to increase congestion, unless car users could be persuaded to switch to active modes. Third, less car travel due to more working at home, more video-conferencing, and more on-line shopping, accentuating recent trends; this would relieve congestion. We can’t yet estimate the likely magnitude of these influences, so can only speculate in broad terms how they may play out.

Might active travel substitute for some car use? The London Mayor aims to increase cycling 10-fold. That would take mode share to 30%, as Copenhagen, a city with comprehensive cycling infrastructure. Yet car use in Copenhagen only slightly less than in London, while public transport use half that in London – 18% mode share vs 37% in London.

It seems that people can be attracted off buses onto bikes, which are cheaper, healthier, environmentally better, and no slower in congested traffic. Yet this would reduce fare income to public transport and likely the level of service. In contrast, it seems harder to get people out of cars onto bikes, even in Copenhagen where most motorists have bikes at home.

The fundamental problem in getting people to travel by slower modes is the consequent reduction in access. The key historic transport innovations all increased access. Railways, the modern bicycle, motor car, motorised two-wheelers, each offered a step change increase in speed of travel and hence in access to people, places, opportunities and choices. Access increases with the square of the speed of travel. Comparing walking at 3 mph with urban car travel at say 20mph, a 7-fold increase in speed, yielding a 50-fold increase in access to desired destinations. Comparing cycling at 10mph with car travel – twice the speed giving four times the access. People have become used to the access offered by the car and most would be reluctant to settle for less by opting for slower modes.

To reduce car use, we need to offer a mode that is faster and more reliable than the car on congested roads, which is rail – interurban between cities, commuting into cities, and rail in all its forms within cities. Investment in rail in London has been important in reducing car mode share from 50% in early 1990s to the current 36%. But continuation of that shift depends not only on successfully tacking the coronavirus pandemic, but also continuing to invest in urban rail, which is very costly and so limits expansion of rail travel.

The other way of reducing car use is to lessen the need to travel for work. The pandemic has shown us how we can manage to travel much less, but this is undoubtedly suboptimal. The magnitude of the rebound remains to be seen. Investment in broadband could facilitate remote working and could be much more cost-effective than new road capacity.

 All in all, I do not expect to see a substantial change in per capita car use nationally, once the pandemic is behind us, but we could be at the start of a downward trend, reflecting less need to travel and some switching to other modes. It may turn out that we are now at the peak of car travel on a per capita basis, which should prompt review of all those ‘shovel ready’ schemes in the road construction programme.

As a means to decarbonise the transport system, the contribution of behavioural change is problematic to rely on because of the uncertainties of responses to both the easing of lockdown restrictions and policy interventions aimed at changing travel behaviour. This means that we need a strong commitment to technology in the form of electrification, both to cut transport carbon emissions and improve urban air quality.

The other new technology – automation – is not a solution to the problems we face. It will be difficult to deploy autonomous vehicles on the existing road network. The technology is expensive and the benefits limited, so that the appetite of consumers is uncertain. The car manufacturers will give priority of electric vehicles, leaving automation to be developed in the slow lane.