Traffic modelling for the new normal

Traffic modelling, for reasons discussed in this presentation, tends to move in that space where it is comfortable. We have accepted climate change and the need to change our society but our models poorly reflect this. We are reluctant to model for scenarios that we expect and rather follow instead the business as usual approach (BAU). What can be done?

ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, 28 April 2021, accessed 4 April 2022.

Below is the transcript for the presentation of Phil Goodwin, Emeritus Professor of Transfer Policy at UCL. The full transcript is provided and also a summary of key quotes at the top.

Key quotes

Their common philosophical starting point is that the future will be sufficiently like the past that right relationships have observed or thought to be observed in the past will continue to be stable enough to use as a guide to the future, reliable enough to support decisions, maybe with a few modest caveats, but no serious doubt about the conclusions. COVID-19 and climate change both challenge the credibility of that view.

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

A decent model would have been able to give quite a good prediction of the future, different from the past and something like that slide. But nobody wanted to know. That’s not a failing of the models, of course, I suppose it’s a failure of imagination or courage in the way they were used.

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

So why does it seems surprising that the boundaries of human and political response to crisis or to positive feedbacks in policy are quite different from those which appear when we imagine we’re in a steady state, or more precisely, a steady, autonomous growth. Mainstream modelling frameworks have not been built around the understanding from that experience, but this was a choice.

ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, 28 April 2021, accessed 4 April 2022.

If that is the future (climate change), the idea of present infrastructure and transport management policies being usefully informed by business as usual traffic is utter nonsense.

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

What I cannot understand is how we also fail to carry out serious modelling of the other scenario: success. What happens to transport if we are able to reduce carbon output sufficiently to avoid that calamity forced evacuations, migrations and the rest? Now, I’d ask you to agree that the most likely condition for such a success would include rapid progress in reducing the volume and distance of travelled substantially, completely, obviously, by fossil fuel vehicles, but also the total amount of travel including electric vehicles with a cars or planes and therefore also the carbon emissions from manufacture of the vehicles and construction of the infrastructures.

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

It’s commonplace in official statements that we must use our cars less, we must favour walking and cycling and buses metro systems, we must replace short distance flights by better trains. This is no longer a minority or crank idea. It is the very widespread received official wisdom

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

Policies which make local movement easier and more attractive by local public transport – walking, cycling, and indeed, by land use planning – must also affect the amount of long distance travel. We cannot implicitly assume that the journey length distribution is a stable modelling parameter.

ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, 28 April 2021, accessed 4 April 2022.

If we do want to use models to help define and assess policies for success, the questions that arise will they be the same models and will they be used under the same institutional arrangements?

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

The main clients, public or private, are often the main funder and promoter of specific projects. The modeller’s own business plan needs contracts for the sort of model they are good at. All these parties are co-dependent, sometimes complicit.

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

But mostly the errors are not apparent until years or decades later and by then there is no one accepting responsibility or for that matter, accepting that error existed. Models are complex, they’re very rarely transparent, that almost never fully open access. They are run by a sort of priesthood – that is us – with lengthy training and their own language. In those circumstances, the roles of scrutiny and challenge are supremely important

ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, 28 April 2021, accessed 4 April 2022.

What we’re now seeing is that model based assessments are under challenge in circumstances outside professional conferences, and official reports.

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

Statutory restrictions and procedures do not always make scrutiny easy. So how to promote healthy scrutiny and challenge? Does it require independent arbitration, separation of client and promoter? Open access to the models of themselves? Statutory funding for challenge? Could we have a consulting industry of skilled modellers who would be prepared both to provide the models and to critique them?

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

My own position is that there are some inbuilt features of the best established models, which tend to underestimate the dimensions and speed of behavioural change when needed, and therefore contribute less than helpfully to sustainability.

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

I think that now and for the rest of our lives, we will live in a disequilibrium world: chaos is always close and business as usual is an illusion, there is no usual. Therefore, I’d say we need dynamically specified models, which can accommodate imperfectly reversible relationships, discontinuity and past dependence and give outputs of an evolving uncertain pattern in explicit time, not an equilibrium one.

Phil Goodwin, Emeritus Professor of Transport Policy at UCL, ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, accessed 4 April 2022.

Full transcript

Phil Goodwin, Emeritus Professor of Transfer Policy at UCL 2:39

My theme is modelling without business as usual. I’m mainly going to focus on the big models, the ones that you use to forecast future movement and support big projects. Their common philosophical starting point is that the future will be sufficiently like the past that right relationships have observed or thought to be observed in the past will continue to be stable enough to use as a guide to the future, reliable enough to support decisions, maybe with a few modest caveats, but no serious doubt about the conclusions. COVID-19 and climate change both challenge the credibility of that view.

But actually, I want to start with a small example from a different break in continuity: Brexit. As far as I know, there was not and still has not been a single model test to model the effects of Brexit on the previously modelled traffic forecasts for the current multi-billion pound program of road projects. Well, it’s early days. But within the first couple of months, we already saw one effect a new pattern of freight movement from Ireland to the rest of Europe dozens of new ferry routes, routes, shipping containers or freight lorries between Ireland and the rest of Europe. There are obvious implications on English ports and East West roads across England.

Now the point of this example is that it is exactly the sort of thing that big conventional models are able to deal with, a shift in the well established pattern of movement from a well defined set of origins to a well defined set of destinations, due to a change in the relative cost of different routes. A decent model would have been able to give quite a good prediction of the future, different from the past and something like that slide. But nobody wanted to know. That’s not a failing of the models, of course, I suppose it’s a failure of imagination or courage in the way they were used. Now, let’s think about COVID-19. What lessons are there there. The fact of the pandemic was so predictable. That years ahead, many countries undertook detailed simulation studies, war games in a sense, about what to do. And there was one important feature of the way the pandemic grew. That was also predictable.

It followed aviation routes, epidemics become pandemic, by international travel, which happens in timescales of hours or days, vaccines can be produced far quicker now. But still in timescales of months that best, therefore, future (…) will surely trigger much more immediate control of international travel. And that must be part of the future scenario for aviation, that is completely a transport issue and surely modelling has something to contribute to it. Serious interruptions in travel, in effect, will become part of the definition of business as usual. Rather than uninterrupted growth.

As far as I know, there were no uses of transport models to address the effects of the type of constraints on movement that would necessarily be involved. Maybe I’m wrong on that and it was done, but we never heard about it. Or maybe some people here now were involved in such an exercise, maybe. But I think it was not done, because it would have seemed a waste of time to ask models to forecast effects of something that was so different from the conditions during which they were built up. That’s true. So it would have been very informative to find out how good or bad their predictions would have been. Anyway, it happened uninformed by modelling. And we learned how swiftly and then how many dimensions travel behaviour could and did adjust.

Is that a completely original finding? Well, no, it’s not. There had already been many examples of disasters, which have affected travel patterns very substantially, and very swiftly, volcanoes, earthquakes, tsunamis, bridge collapses. We’ve also had decades of experience of implementing policies and transport provisions, which, for example, give positive feedback to trends in begging car dependent lifestyles, or seeking to reverse that positive feedback. For example, in the pedestrianisation of town centres, we already observed this.

So why does it seems surprising that the boundaries of human and political response to crisis or to positive feedbacks in policy are quite different from those which appear when we imagine we’re in a steady state, or more precisely, a steady, autonomous growth. Mainstream modelling frameworks have not been built around the understanding from that experience, but this was a choice.

The observations were there to be seen, but the choice was that this is not a proper business of models. Business as usual, is also the casualty of what we know about climate change. I don’t want to talk about climate change modelling itself, except to say that it offers us two crucial scenarios, which affect the future of all travel. And neither of these scenarios are taken seriously in transport modelling. The first scenario we completely ignore in mainstream transport modelling is the implications of failure. Suppose we fail to change the production of CO2 and other atmospheric drivers sufficiently to halt warming. We are advised by the climate models that this will mean among other effects, a rise in sea levels drastically affecting populations.

And we’re also advised by climate models that it implies the conversion of many currently hot locations into unlivable ones. Now taken together, those two effects have results for some of the wealthiest, most pleasant and most desirable locations in the coastal cities of the world. And also some of the poorest and most difficult situations, both with mean mass population movements, may be in the order of a billion migrants in our own lifetimes, including some of us. It’s inconceivable that current patterns of international movement and national movement in countries whose geography stretches across equatorial and temperate and cold regions could then continue or recover steady growth along past trends. If that is the future (climate change), the idea of present infrastructure and transport management policies being usefully informed by business as usual traffic is utter nonsense.

If planning is useful to cope with that scenario, it will be about flexible and resilient transport and living arrangement, not fixed infrastructure. The engineering model will not be the norms of civil engineering we’ve inherited, but its predecessor, military engineering, temporary camps, pontoon bridges, managing huge population movements, traffic movements under huge pressure, there could be an important role for contingency modelling to plan for that.

Though I do understand the concern that modelling it might seem to be preparing people to accept it (the worst). I can understand that, but what I cannot understand is how we also fail to carry out serious modelling of the other scenario: success. What happens to transport if we are able to reduce carbon output sufficiently to avoid that calamity forced evacuations, migrations and the rest? Now, I’d ask you to agree that the most likely condition for such a success would include rapid progress in reducing the volume and distance of travelled substantially, completely, obviously, by fossil fuel vehicles, but also the total amount of travel including electric vehicles with a cars or planes and therefore also the carbon emissions from manufacture of the vehicles and construction of the infrastructures.

Now, I know there are some who say this is not necessary, and electrification will in enable businesses as usual growth. I assert that it is already clear that that trajectory is insufficient, and unrealistic, and many governments also assert the same thing. It’s commonplace in official statements that we must use our cars less, we must favour walking and cycling and buses metro systems, we must replace short distance flights by better trains. This is no longer a minority or crank idea. It is the very widespread received official wisdom – in policy statements anyway. So why is there such resistance to making the success scenario the central case for project appraisal and the agenda for systematic appropriate modelling of exactly what projects from what policies would most swiftly bring this success about?

Because there’s a problem, it’s not at all clear that models whose history is the assessment of projects to provide infrastructure for permanent growth, are capable of providing good answers to that question. Now, the first reason for that is obvious. A model that only include vehicle travel cannot say anything useful about sustainable transport policies. That’s surely self-evident in towns, but I’d say it affects the strategic network also. This is because any behavioural model has to allow for destination choice, not only mode choice, and certainly not only route choice.

Now surely, one of the most robust findings from half a century of modelling is that if costs increase over the whole network, redistribution will shorten average journey distances, and vice versa, if costs reduce. What that means is that the mechanisms of changing mode choice interact with those of destination choice. Policies which make local movement easier and more attractive by local public transport – walking, cycling, and indeed, by land use planning – must also affect the amount of long distance travel. We cannot implicitly assume that the journey length distribution is a stable modelling parameter. Or we would substantially underestimate the potential. We’d get an answer but it would be wrong.

So if we do want to use models to help define and assess policies for success, the questions that arise are will they be the same models and will they be used under the same institutional arrangements?

Let’s deal with that latter point first. The modelling industry – that’s us – is an ecosystem of social relationships between clients and contractors, and vested interests, and users. The main clients, public or private, are often the main funder and promoter of specific projects. The modeller’s own business plan needs contracts for the sort of model they are good at. All these parties are co-dependent, sometimes complicit. When things go wrong, like the Australian experience of muddled forecasts of toll revenues, which led to some banks losing money, there is a row about whose fault it was.

But mostly the errors are not apparent until years or decades later and by then there is no one accepting responsibility or for that matter, accepting that error existed. Models are complex, they’re very rarely transparent, that almost never fully open access. They are run by a sort of priesthood – that is us – with lengthy training and their own language. In those circumstances, the roles of scrutiny and challenge are supremely important.

What we’re now seeing is that model based assessments are under challenge in circumstances outside professional conferences, and official reports. I’m involved in one at the moment as an expert witness in our high court, suggesting that official figures underestimate the carbon consequences of road projects. The action was initiated by a quite small campaigning group, crowdfunded and recently reported in a British newspaper, which in turn led to an intervention among others from Greta Thunberg. These are not contexts that most of us are familiar with. In my experience, the main active challenge often comes from political groups who are out of power, and environmental campaigning groups who are well informed but poor.

Statutory restrictions and procedures do not always make scrutiny easy. So how to promote healthy scrutiny and challenge? Does it require independent arbitration, separation of client and promoter? Open access to the models of themselves? Statutory funding for challenge? Could we have a consulting industry of skilled modellers who would be prepared both to provide the models and to critique them? Is there a market niche for professional modellers to make a living from representing the challenges? Would you want to? Would you dare?

My own position is that there are some inbuilt features of the best established models, which tend to underestimate the dimensions and speed of behavioural change when needed, and therefore contribute less than helpfully to sustainability. The modelling concepts of equilibrium and steady, uninterrupted long term growth, do not cope with asymmetrical relationships, for example, with price or income, or cohort effects of ageing, we do not have an approach to transport pricing, which copes with an electricity market, which might be paid for different frequencies, different units, changing prices from minute to minute, offering opportunities for hedging, and buying in advance, or smart charging in two directions. We have not taken seriously the crucial importance of timing, and the speed of change and the sequence of policy interventions.

In a sentence, I think that now and for the rest of our lives, we will live in a disequilibrium world: chaos is always close and business as usual, is an illusion, there is no usual. Therefore, I’d say we need dynamically specified models, which can accommodate imperfectly reversible relationships, discontinuity and past dependence and give outputs of an evolving uncertain pattern in explicit time, not an equilibrium one. So in conclusion, what I’m saying is there is a role for models and there’s a role for modellers many roles, but it’s not the same as it has been, and it needs to be earned.

ANZ6 – Climate change: challenges for transport models, Modelling World International 2021 ANZ6 21 April 2021, YouTube, 28 April 2021, accessed 4 April 2022.

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