Artificial Intelligence (AI) is much in the news. The development of Large Language Models (LLMs) has been crucial to recent advances. These are general purpose models based on artificial neural networks that can be trained on large quantities of unlabelled text using self-supervised learning. The breakthrough came from OpenAI, a US company originally set up to develop open source software, but which received $10bn investment from Microsoft so may be shifting to a more commercial mode of operation. For the moment at least, ChatGPT, its basic offering, is available without charge (https://openai.com/blog/chatgpt ).

There has been a full range of claims about this advance in AI, from offering a step change increase in productivity, which is why the prime minister wants Britain to lead the world, to concerns from knowledgeable experts that it would allow bad people to do bad things, or worse. So I thought it would be interesting to see what ChatGTP could do in practice. I posed two initial questions, and show the answers in full:

Q1 What are the causes of road traffic congestion?

‘Road traffic congestion can be caused by various factors, including:

  1. High volume of vehicles: An excessive number of vehicles on the road can lead to congestion, especially during peak travel times. As the number of vehicles increases, the capacity of the road may be exceeded, resulting in slower speeds and increased delays.
  2. Inadequate infrastructure: insufficient road capacity, poorly designed intersections, narrow lanes, lack of alternative routes, and inadequate public transportation systems can contribute to traffic congestion.
  3. Traffic incidents and accidents: Road accidents, breakdowns, and other incidents can disrupt the flow of traffic and cause congestion. When lanes are blocked or vehicles are immobilized, it can lead to significant delays.
  4. Roadworks and construction: Construction activities, maintenance work, and road repairs often require the closure of lanes or the diversion of traffic. These temporary disruptions can cause congestion, especially if they are not well managed or scheduled during off-peak hours.
  5. Traffic signal timing: Inefficient traffic signal timing can lead to congestion. If signals are not properly synchronized or do not consider the actual traffic demand, it can result in stop-and-go traffic patterns and delays.
  6. Bottlenecks and chokepoints: Certain sections of roads, such as narrow bridges, tunnels, or interchanges, may have limited capacity and create bottlenecks. When traffic volume exceeds the capacity of these areas, congestion can occur.
  7. Lack of public transportation options: In areas where public transportation is limited, unreliable, or inconvenient, more people rely on private vehicles, which can contribute to traffic congestion.
  8. Traffic management and planning: Inadequate traffic management strategies, including poor coordination between traffic control systems, insufficient signage, and improper lane markings, can exacerbate congestion.
  9. Special events and holidays: Large gatherings, festivals, sporting events, or holiday periods can generate additional traffic and cause congestion, especially if the road network is not prepared to handle the increased demand.
  10. Driver behaviour: Aggressive driving, lane weaving, improper lane changes, and lack of adherence to traffic rules and regulations can disrupt the flow of traffic and lead to congestion.

It’s important to note that the causes of traffic congestion can vary based on location, time of day, and other local factors. Addressing congestion often requires a multi-faceted approach involving infrastructure improvements, traffic management strategies, and promoting alternative transportation options.’

Q2 What is the best way to reduce road traffic congestion?

‘Reducing road traffic congestion requires a combination of strategies that focus on improving infrastructure, promoting efficient transportation systems, and encouraging behaviour change. Here are some effective approaches:

  1. Improve public transportation: Enhancing public transportation systems, such as buses, trains, and trams, can provide people with reliable and convenient alternatives to driving. This includes increasing the frequency and coverage of services, improving the quality of vehicles, and integrating different modes of transport.
  2. Encourage carpooling and ridesharing: Promoting carpooling and ridesharing programs can reduce the number of vehicles on the road. Incentives like preferential parking or reduced tolls for carpoolers can encourage more people to share rides.
  3. Implement congestion pricing: Congestion pricing involves charging fees for driving in congested areas or during peak hours. By making it more expensive to drive during times of high demand, it encourages people to shift their travel times or modes, reducing congestion.
  4. Develop and promote active transportation: Creating infrastructure for pedestrians and cyclists, such as sidewalks, bike lanes, and bike-sharing programs, can encourage people to choose walking or cycling for shorter trips. This reduces the number of vehicles on the road and eases congestion.
  5. Enhance traffic management and signal coordination: Optimizing traffic signal timing and coordinating signal systems can improve traffic flow and reduce congestion. Advanced technologies, such as adaptive signal control systems, can adjust signal timings based on real-time traffic conditions.
  6. Invest in road infrastructure: Expanding road capacity, building additional lanes, and constructing new roads in areas with high congestion can increase the overall capacity of the transportation network. Additionally, improving road design and addressing bottlenecks can help alleviate congestion.
  7. Implement smart transportation systems: Intelligent transportation systems (ITS) use technologies like real-time traffic monitoring, dynamic message signs, and navigation apps to provide drivers with information about traffic conditions and alternative routes. This helps drivers make informed decisions and reduces congestion by distributing traffic across different routes.
  8. Encourage telecommuting and flexible work hours: Promoting telecommuting and flexible work hours can reduce peak-time traffic by allowing employees to work from home or choose non-peak hours for commuting. This can help spread out the traffic demand and alleviate congestion during rush hours.
  9. Develop land-use planning strategies: Efficient land-use planning can reduce the need for long commutes by locating residential areas closer to workplaces, schools, and amenities. This reduces overall travel distances and decreases congestion.
  10. Promote behaviour change and education: Encouraging responsible driving behaviour, such as obeying traffic rules, avoiding aggressive driving, and practicing eco-friendly driving techniques, can help improve traffic flow and reduce congestion. Public awareness campaigns and educational programs can play a role in promoting these behaviours.

It’s important to note that no single solution can completely eliminate traffic congestion. A combination of these strategies, tailored to the specific needs and characteristics of each location, is typically the most effective approach to reducing road traffic congestion.’

I was impressed by these pretty good summaries of conventional wisdom. They lack penetrating insight and do not cite sources, but each would serve as a useful summary, perhaps as an introduction to a substantial analysis, for an article by a non-specialist journalist, or as the basis for a student essay. ChatGPT looks to be a real competitor for Google and Wikipedia, and indeed Google has entered the field with its own offering, known as Bard.

However, the limits of ChatGPT can be illustrated by a further question:

Q3 What do you know about David Metz, Centre for Transport Studies, University College London?

‘David Metz is a prominent transport expert and researcher associated with the Centre for Transport Studies (CTS) at University College London (UCL). He has made significant contributions to the field of transport planning and policy over the course of his career.

David Metz has an extensive background in transportation and urban planning. He obtained his Ph.D. in Transport Economics from UCL and has since held various academic positions, including Professor of Transport Studies at UCL and Honorary Professor at the Institute for Transport Studies, University of Leeds.

At the Centre for Transport Studies, David Metz has conducted research on a wide range of transport-related topics, including travel behaviour, sustainability, transport policy, and the relationship between transport and climate change. His research often focuses on understanding the complex interactions between transport, society, and the environment.

David Metz is known for his critical analysis of transport policies and his ability to challenge conventional thinking. He has emphasized the importance of considering the social and behavioural aspects of transport planning and policy-making, highlighting the need to move beyond purely technical solutions.

In addition to his research work, David Metz has been involved in advisory roles and has provided expert advice to governments and organizations on transport policy matters. He has served on various committees and panels, including the UK Sustainable Development Commission and the Scientific Advisory Committee of the UK Department for Transport.

David Metz’s contributions to the field of transport have been recognized through numerous awards and honours. He is a Fellow of the Academy of Social Sciences and has received the Wolfson Prize for Transport Policy. His research publications, including books and academic papers, have made a significant impact on the field and are widely cited by transport professionals and researchers.

Overall, David Metz is a respected figure in the field of transport studies, known for his research on transport policy, sustainability, and the social dimensions of transportation. His work at the Centre for Transport Studies, UCL, has contributed to advancing knowledge and understanding in the field of transportation.’

This is all very flattering. However, key ‘facts’ are quite wrong. I do not have a PhD in transport economics. I have not had an affiliation with the University of Leeds. I have not served on the UK Sustainable Development Commission or the Scientific Advisory Committee of the UK Department for Transport. I am not a Fellow of the Academy of Social Sciences and have not received the (non-existent) Wolfson Prize for Transport Policy. Regrettably, I have not received ‘numerous awards and honours’.  It would be going too far to say that my books and papers are widely cited by transport professionals and researchers. And my one small claim to fame, that I was Chief Scientist at the Department for Transport, was overlooked.

What is the origin of these ‘hallucinations’, as they are known – apparent confident responses not justified by the data on which the model was trained? This training presumably did not include data from a simple Google search that would have generated real facts, or a check with Amazon to find the books I have authored, or a check with LinkedIn for my career. The origin of such hallucinations remains a mystery since the LLMs are not open for inspection or are capable of validation. Nor, evidently, do they have a built-in fact checker.

So, we cannot yet dispense with Google as a source of citations, ranked according to impact, nor with Wikipedia with its editorial oversight of contributions. But Chat GTP and similar AI offerings can offer plausible narrative outlines that should be checked for factual accuracy. And they may improve over time.

One further Q&A for many readers of this blog:

Q4 How to be a better transport planner?

‘To become a better transport planner, consider the following steps:

  1. Gain Knowledge and Expertise: Develop a deep understanding of transportation systems, including various modes of transport, infrastructure, policy frameworks, and relevant technologies. Stay updated with the latest trends and innovations in the field. Pursue formal education or certifications in transportation planning or related disciplines.
  2. Analyze Data: Transportation planning involves analyzing vast amounts of data. Learn to use data analysis tools and software to extract insights from transportation surveys, traffic counts, travel demand models, and other relevant sources. Apply statistical methods and modeling techniques to interpret data accurately.
  3. Understand Stakeholder Needs: Recognize the importance of stakeholder engagement. Collaborate with various stakeholders, such as government agencies, urban planners, community organizations, and transportation providers. Understand their needs, concerns, and aspirations to develop effective transport plans that address their requirements.
  4. Consider Sustainability: Promote sustainable transportation solutions that minimize environmental impact, enhance public health, and prioritize energy efficiency. Integrate strategies for reducing emissions, improving air quality, and promoting active transportation modes like walking and cycling.
  5. Plan for Multimodal Systems: Design transportation systems that accommodate multiple modes of transport, including private vehicles, public transit, walking, and cycling. Aim to create an integrated and seamless network that offers efficient connectivity between different modes and encourages modal shift.
  6. Embrace Technology: Keep up with advancements in transportation technology, such as intelligent transportation systems, autonomous vehicles, and mobility-as-a-service (MaaS) platforms. Understand how these technologies can enhance transport efficiency, safety, and accessibility.
  7. Conduct Impact Assessments: Evaluate the potential impacts of proposed transportation projects or policies. Assess their effects on traffic flow, travel times, air quality, land use, and social equity. Use impact assessment tools and methodologies to inform decision-making and mitigate any adverse consequences.
  8. Collaborate with Other Disciplines: Work closely with urban planners, engineers, architects, and environmental specialists to develop holistic and comprehensive transport plans. Emphasize interdisciplinary collaboration to integrate transportation planning with land use planning, urban design, and environmental sustainability.
  9. Engage in Continuous Learning: Participate in professional development activities, attend conferences, workshops, and seminars related to transportation planning. Stay informed about emerging research, best practices, and policy updates. Actively seek feedback and learn from the experiences of other professionals in the field.
  10. Advocate for Positive Change: Act as a catalyst for change by advocating for sustainable and equitable transportation policies and practices. Engage in public outreach, education, and advocacy to promote awareness and support for transportation initiatives that benefit communities and enhance quality of life.

Remember that becoming a better transport planner is an ongoing journey. Continuously refine your skills, stay open to new ideas, and adapt to evolving societal needs and technological advancements in the transportation sector.’

So there you have it. Who could argue?

This blog was the basis of an article in Local Transport Today of 3 July 2023.

Recent revisions to the road traffic statistics appear to show that there has been a substantial growth of motor vehicle traffic on GB minor roads in recent years, from 108 to 136 billion vehicle miles between 2010 and 2019, an increase of 26%. Traffic on major roads rose from 197 to 221 bvm over the same period, an increase of 12%.  (DfT Road Traffic Statistics TRA0102).

Road traffic statistics are based on a combination of automatic and manual traffic counts. Major roads are well covered in that traffic in all links is counted on typical days, although not every link in every year. Given the vast number of minor roads, however, it is only possible to count traffic at a representative sample of locations every year, and the observed growth is applied to minor road traffic overall. Estimates from a fixed sample may drift over time such that the sample becomes less representative of the changing minor road network. To account for any errors incurred in the fixed sample, the sample is revised through a benchmarking exercise every decade, involving a much larger sample of locations.

The most recent minor roads benchmarking exercise was published in 2020, based on 10,000 representative locations. Overall, the benchmark adjustment for 2010-2019 was 1.19, which is the factor to be applied to 2019 data from the original sample to bring this to the observed traffic level. Data for minor roads traffic for intermediate years are adjusted pro rata, to avoid a step change in the reported traffic data. There is significant regional variation in the adjustment factor, from 1.35 for Yorkshire to 1.09 for East of England, with London at 1.32. For B roads the factor is 1.25, for C roads 1.17; while for urban roads, 1.22, and for rural roads, 1.15. Applying the regional weightings yields an increase in traffic on minor roads of 26%, as noted above, whereas the increase based on the original sample would have been 6%.

The previous benchmarking exercise published in 2009 found a smaller overall adjustment factor of 0.95, with a regional range of 0.81 to 1.08.

The substantially greater adjustment required following the recent benchmarking, compared with the earlier exercise, suggests that there has been a real change in use of minor roads, beyond errors arising from drift in the sample. Importantly, had the increase in minor road use been spread evenly across the national road network, the traffic estimation based on the sample would have been close to that from the benchmark exercise. Hence the major difference between sample and benchmark indicates considerable heterogeneity of minor road traffic growth. Moreover, the fact that the sample failed to detect the traffic growth suggests either that the process for establishing the sample was deficient in some way, or that significant changes occurred in use of minor roads over a decade.

DfT statisticians have created a revised minor roads representative sample (4,400 locations) from the latest benchmark data, which will be used for the coming decade. It would be desirable to have comparative analysis of the previous and the new samples, to gain insight into what has been happening on the minor road network. Regrettably, the statisticians only report findings, and do not attempt to explain them, which leaves uncertainty as to the nature and cause of the reported changes to traffic volumes. The representative nature of the new sample must be questionable if the reasons for the failure of the previous sample to reflect reality are not understood and addressed.

Transport for London has recognised this uncertainty. The recent Travel in London Report 13 discusses the implications of the minor roads traffic correction (p92). The revisions mean that, for 2018, the DfT estimate of vehicle kilometres was 20% higher than previously reported last year (and included in Travel in London Report 12). The previous estimate suggested a fall of 1.8% in vehicle kilometres in London between 2009 and 2018, whereas the revised series now suggests an increase of 17.9% over the same time period, this change wholly arising from revisions to the minor road estimates. TfL notes that it is currently working through how the DfT have made this assessment, and also what this could mean for London data sets. For the moment, TfL is relying on its own traffic monitoring data, although it does not report traffic on minor roads separately.

The National Travel Survey could provide a cross-check on the traffic data. Average distance travelled by car/van driver decreased from 3388 miles per year in 2010 to 3198 miles in 2019, a decline of 5.6% (NTS0303). The GB population grew from 60.95m in 2010 to 64.90m in 2019, an increase of 6.5%. The net increase in car use of about one percent is inconsistent with the new road traffic statistics which show an increase in traffic for all roads of 17% over the same period. The NTS employs a fresh sample of respondents each year, so sample drift should not be a concern. However, it is not clear that the travel diary technique would pick up rerouting to minor roads, given that respondents are asked to provide their own estimates of distance travelled for each trip.

Possible causes of increase in traffic on minor roads

One factor contributing to the growth of traffic on minor roads is the increase in van traffic, including that arising from the growth of online shopping with home deliveries. The number of vans (light commercial vehicles) registered in Britain increased by 28% between 2010 and 2019. Total van traffic increased by 34% over this period, with an increase of 49% on urban minor roads compared with 10% on urban ‘A’ roads, although ‘delivery/collection of goods’ was less important in respect of journey purpose than ‘carrying equipment, tools or materials’. However, in 2019 van traffic amounted to 15% of traffic on urban minor roads, and 19% on rural minor roads, cars being responsible for 82% and 78% of traffic respectively. So, the growth of van traffic on minor roads is responsible for only part of the overall traffic growth on these roads.

Another possible explanation of the apparent large growth of traffic on minor roads is the widespread use of digital navigation (satnav) that offers routes that take account of traffic conditions and estimated journey times. Such devices make possible the general use of minor roads that previously were largely confined to those with local knowledge. This is likely to occur when major roads are congested and represents an effective increase in the capacity of the road network, so generating additional traffic – the converse of the ‘disappearance’ of traffic when carriageway is reduced. Increased use of minor roads is problematic when policy is concerned to decarbonise the transport system and to promote active travel, which these roads facilitate.

The possible role of digital navigation might be investigated by an analysis of the correlation of the upward adjustment factor for each minor road sample location with traffic volumes on nearby major roads – to test the hypothesis that there would be more use of minor roads in areas where major roads were most congested. If so, this factor should be taken into account when setting up the new minor roads sample for the coming decade.

The use of digital navigation has been growing and may continue to grow in the future. A better understanding of the phenomenon would be important for forecasting road traffic growth by means of the National Transport Model and models at regional level and below.

A further possible cause of the changed distribution of traffic on minor roads arises from intentional interventions aimed at reducing such traffic. It has long been the practice to discourage ‘rat running’ on urban minor roads by means of suitable physical control measures, as are used in low-traffic neighbourhoods (LTN). Such measures would reduce traffic in certain locations while possibly increasing it in others through diversion. Some locations in the minor roads sample may be so affected. If LTNs and similar measures increase over time, the sample may become increasingly unrepresentative, a factor that should be taken into account in setting up the new sample. However, the net effect of intentional interventions would be to reduce traffic overall, so this cannot account for the reported growth of traffic on minor roads.

The growth of minor road use by through traffic apparently facilitated by digital navigation would strengthen the case for implementing LTN measures. Alternatively, or additionally, the providers of digital navigation might be encouraged to omit routes that direct through traffic along minor roads.

More generally, the impact of digital navigation on the functioning of the whole road network seems likely to be significant and therefore worthy of investigation.

The above considerations prompt a number of questions:

  1. How reliable are the statistics for motor vehicle use of minor roads, given the apparent sensitivity to the sampling of locations?
  2. How reliable are the NTS findings for car use?
  3. What information is available on the likely causes of the increase of traffic on minor roads?
  4. What is known of the impact of digital navigation on the road network?
  5. What are the implications of digital navigation for transport and traffic modelling?

Summary

The reported increase in motor vehicle traffic on minor roads over the past ten years is substantial and locationally heterogenous, for reasons that are unclear. This lack of understanding raises methodological questions about the sampling of minor roads. The reported increase in traffic is not consistent with the findings of the National Travel Survey, as well as being of concern to Transport for London. While interventions to reduce traffic on urban minor roads may increase the heterogeneity of the sample, they would not increase the volume of traffic. Hence this increase is most likely due to the growing use of digital navigation devices that allow minor roads to be used by those without local knowledge. This has implication for transport modelling as well as for policies to decarbonise the transport system and encourage active travel.

This blog post is the text of an article published in Local Transport Today 19 March 2021

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.

I have long been skeptical about the case for a third runway at Heathrow. The argument in favour concerns the growth of demand for business travel, yet most passengers at Heathrow are on leisure trips, so there is plenty of scope for increasing business travel by displacing leisure travel to other airports in the London area with spare capacity. In a blog posted in 2015 I suggested that Emirates Airline might fly from Stansted to its Dubai hub if demand for flights from Heathrow could not be accommodated.

I was therefore gratified to read in the Financial Times that Emirates is indeed launching next month a daily service from Stansted to Dubai. Other airlines are offering services from Stansted to New York: Primera Air and Wow Air. Stansted hosted 190,000 flights in 2017 but could accomodate 274,000 on its single runway.

A recent transport innovation with potentially a big impact is the dockless bike – for hire in urban areas but not linked to a permanent location or installed by or with permission of the local transport authority. Dockless bikes are linked instead to an app on the mobile phone, which allows payment for use, and are installed by entrepreneurs who see a business oportunity.

Dockless bikes have made a striking impact in China, with large numbers flooding the market and huge surpluses piling up – literally, as recent photojournalism in The Atlantic magazine vividly illustrates. Presumably, economic considerations will restore a balance between supply and demand in due course.

A witty follow up article in Slate shows pictures of extensive arrays of dockless vehicles in the US – in this case parked cars.

Another stage on the long-running saga of expanding the capacity of London’s Heathrow Airport is marked by publication of a report from the House of Commons Transport Committee. This considers the Government’s Airports National Policy Statement, which endorses the proposal for a third runway at Heathrow. The Committee goes along with this, subject to quite a number of caveats about environmental impacts and costs.

What struck me were the weakness of the case for a third runway (the Northwest Runway, NWR), as revealed by the Committee’s findings:

Figure 3 on p17 shows that the main impact of the runway would be to increase the numbers of leisure travellers and international transfer passenger. The extra numbers of business travelers are very small, yet the case for the runway is mainly based on the needs of the UK economy.

‘The benefits and costs the NWR scheme are finely balanced. Even small changes in assumptions or methodology could mean that the monetised costs of expansion via a NWR would outweigh the benefits.’ (p19)

While Heathrow is ‘full’ in respect of aircraft movements and landing/takeoff slots, it is not yet full in terms of passenger throughput since each plane is on average only 76% full and is not always an  aircraft with the highest capacity (p40). Luton and Stansted have the equivalent of around one third of a runway to spare through to 2050. This means that passenger throughput for the London airports is forecast to rise by 27% out to 2050 without expansion at Heathrow (p42)

The forecasts  show that an expanded Heathrow would accommodate more than three times more outbound passengers than inbound passengers (p48), a net economic deficit to the UK.

The NWR scheme would only offer only one new destination to emerging and fast-growing economies when compared with no expansion by 2050 (p49).

Airport charges at Heathrow are the highest in the world (p82). Could a further runway be financed without increasing charges, which would erode the economic benefits and deter use?

Assessment

I am struck by the weaknesses in the case for building another runway at Heathrow. A key question for the future will be the ability of the airport to finance construction from private sector investors at a cost – both construction and financing – which the airlines and their passengers will be willing to pay via landing charges. The proposal may achieve planning consent but could prove to be commercially unviable.

Professor Anne Graham and I submitted evidence to the Transport Committee, which argued that the market for air may be more mature than generally supposed, and hence demand growth may be less than projected, with consequences for the business case.

 

The National Infrastructure Commission has sought evidence on how the deployment of intelligent traffic systems could help optimise the road network. I sent a response, found here Metz NIC traffic management 1-9-17

My argument is that we need to move beyond traffic management using traffic signals to management involving collaboration between public sector road authorities and the private sector suppliers of digital maps and route guidance apps, such as Google Maps and Waze. These apps have become very popular for turn-by-turn route guidance that can take account of, and help avoid, traffic congestion and provide estimates of journey time before setting out. These features help tackle the main problem of traffic congestion which is journey time uncertainty.

I would expect that collaboration between public and private sectors would improve both the experience for road users and the efficiency of network operations.

Lord Wolfson offered a prize worth £250,00 for the best proposal in response to the question: ‘How can we pay for better, safer, more reliable roads in a way that is fair to road users and good for the economy and the environment’.

The winner was Gergely Raccuja, a recent UCL graduate, now a transport planner with Amey Consulting. His proposal has the merit of simplicity: replace Fuel Duty and Vehicle Excise Duty, receipts from which are declining as vehicles become more fuel-efficient, with a per-mile charge that would depend on a vehicle’s weight (reflecting the damage caused to the road) and emissions (damage to the environment). The charge would be collected by the insurance companies, the new charge being in effect a supplement to the insurance premium.

The impact of congestion caused by a vehicle is captured in a crude way by a distance-related charge. However, the opportunity to relate the charge to the level of congestion was not taken because of the perception that it would be unpopular and hence prevent the new charging scheme being adopted.

Some of the other finalists for the prize proposed schemes involving charging that reflected in part the contribution of vehicle users to congestion, but these were not favoured by the judges.

Assessment

It is very welcome that a new entrant to the transport planning profession was the prize winner, with a relatively simple proposal. But is it likely to be taken up? My sense is that implementation would not be seen as worth the effort and upheaval. Perhaps the main advantage is that electric vehicles would contribute to the costs of the road system, but for that purpose the proposal might be applied to EVs only, leaving Fuel Duty in place for vehicles with internal combustion engines.

The main shortcoming of the prize-winning proposal is the failure to address the problem of road traffic congestion and how it might be mitigated by charging. Public perceptions are important, of course, but I found it odd that there is no mention of London congestion charging, which has proved quite acceptable.

Any change to how we pay for roads should take the opportunity to ameliorate road traffic congestion, which is the biggest problem of the transport system. Arguably, the question set for the prize was misconceived, with its opening emphasis on ‘How can we pay for….’. It might have been better to ask ‘How can we achieve better, safer, more reliable roads….’