Cycling and Transport Modelling: slides and audio recordings

Here you’ll find slides and audio recordings of presentations from Modelling on the Move 6: cycling and transport modelling. Click on the links below to download slides and audio where available.

Modelling on the Move 6: Cycling & Transport Modelling

Location: Westminster University, Marylebone Campus, Weds 22nd January

First session: Challenges. Chair: Phil Jones, Phil Jones Associates.
Some limits of current modelling approaches: lessons for modellers and clients (Tim Gent, WSP Group). Slides, audio.
Why do we find it so hard to model cycling? (Helen Bowkett, Head of Transport Evidence, Welsh Government) – slides, audio
A review of the methodologies for modelling cycling within junction appraisal (John Parkin, Professor of Transport Engineering, UWE) – slides, audio

Second session: Developments. Chair: Dianna Smith, QMUL.
Impacts of Re-allocating Space Away from Motor Traffic: lessons from The Hague (Herbert Tiemens, Dutch Cycling Embassy) – slides, audio
Modelling Cycling in London (Yaron Hollander and Aliasgar Inayathusein, Transport for London). Slides.
Modelling the Unbundling of Cycle Routes in The Netherlands (Paul Schepers, Ministry of Infrastructure and the Environment, Centre for Transport and Navigation, The Netherlands) – slides, audio

Third session: Issues. Chair: Philip Loy, Project Centre/London South Bank University.
Carbon and Energy Use (Robin Lovelace, University of Leeds). Slides, audio.
From Cross-Sectional to Dynamic Relationships (James Woodcock, University of Cambridge). Slides, audio.
Physical Activity and Health (Diana Divajeva, UK Health Forum). Slides, audio.
Deliberation and Participation (Geoff Vigar, Newcastle University). Slides, audio.

Cycling and transport modelling

Cross-posted from my personal website.

This linked series of posts represents an initial attempt to think through a few ideas discussed at the second Modelling on the Move seminar on 15th February.

The topic was ‘Public Health Perspectives and Transport Modelling’, and different themes ran through the day, one being the perceived failure of transport modelling to deal adequately with walking and cycling, by comparison to car and public transport trips. Here I just focus on cycling, and from my own perspective. I’d like to thank Helen Bowkett, Tim Gent and John Parkin for helpful comments; of course these posts are solely my responsibility.

Go to Part 1: Where is Cycling in Transport Modelling?

Dynamic Modelling: reality, generality, and precision

At a time when discussions in public health and epidemiology in general  increasingly grapple with ‘complexity’, as well as focusing tightly on specific areas of interest (such of transport and health), it is likewise useful to step back to more abstract considerations. A general shift from the dominance of statistical-based models, which are arguably not well suited to represent change, towards dynamic modelling (Agent Based Modelling and System Dynamic Modelling have become prominent in the literature), and the possibility of including clearly specified local contextual details represent a major advance; however, such attention to technical and contextual issues may potentially move questions about modelling itself into the background. In any case, as someone who doesn’t specialise in work on transport and health, this is where my attention is drawn…

Many years ago (decades in fact), biologist Richard Levins considered the trade-offs involved when developing a modelling strategy. Unless you’re doing exceptionally badly to begin with, trade-offs are almost inevitable.  As ‘new’ modelling methods come into our view, including methods which may appear to offer only benefits, I think Levins’ principles potentially offer useful guidance.

Models can be thought of in terms of three axes: reality, generality, and precision (this typology is not intended to be comprehensive, but rather to capture some critical aspects). In general, gains in any one area are accompanied by losses elsewhere. Briefly, the three situations described by Levins are:

i.            Sacrifice realism for generality and precision

This strategy is very familiar to me as it’s typically used in global scale climate and health impact assessments. The aim to quantify impacts as precisely as possible using general relationships that are applicable to all world regions necessitates a loss of realism; in this case, what is happening nationally or below this level is lost.  An analogous case may be modelling the general impacts of transport policies at UK-level rather than specific impacts in a particular place.

But despite the apparent limitations of this approach compared to adopting a tighter, local focus, it is not without benefits. For instance, the system dynamics operating at a ‘high’ level are likely to play a role in shaping local conditions and possibilities; viewing the system only at the local level may well miss these dynamics. From this perspective, a loss of realism in terms of the local is an advantage.

ii.            Sacrifice generality for realism and precision

‘New’ modelling methods may naturally lead to this strategy as they potentially allow the inclusion of detailed local dynamics. But the degree of detail means generality is lost; the model is only useful for the very specific circumstances being considered. Viewed temporally, the lack of generality may limit the useful lifespan of such a model: as local conditions change, or as conditions at a higher level (e.g. national) change and potentially alter local dynamics, the model may no longer represent reality well.

Another limitation is the amount of data and knowledge required to construct and parameterise such a model: to make precise estimates of the outcome of interest, precise representation of relations and variables is necessary. Often the data or knowledge, particularly for a specific local setting, are not available. In the absence of the required inputs, the model, despite looking ‘fancy’, may tell us little of use about the situation of interest.  This leads on to the third strategy…

iii.            “Sacrifice precision for generality and realism”

At least in my experience, the goal of producing precise quantitative estimates is beyond discussion: of course precise quantification is the (or at least, a major) goal!

But is this sensible? In any case, it comes at a cost. If no data or quantification of a relation is available, it is either left out or crudely represented.  In many cases, so much is left out or represented by ‘best guesses’ (maybe named as ‘expert opinion’) that the resulting quantifications are accompanied by the qualification that they should only be interpreted in terms of magnitude; that  is, in a sense, qualitatively. The very sacrifices made to achieve ‘precision’ undermine the value of that precision.

Why not then – in some models, but of course not all – relax the relentless drive for precision and instead aim simply to understand system behaviour generally? Instead of asking, ‘How much will this increase if we do that’, you can ask, for example, ‘If we do this, will this increase of decrease?’. At the very least this type of strategy can be used to get a general understanding of the system of interest, and guide attention to specific aspects that appear to be critical to behaviour.

Because of the inevitable trade-offs, a mixture of strategies seems appropriate, with which is used at any moment being guided by what we know and want to know.

The final strategy is of particular interest to me.  We’ll be discussing and developing its potential for transport and health during the second event of the seminar series. It will no doubt require some imaginative input from those who come along…

“Stakeholder” involvement in transport modelling

Recently I finished a 5-year transport policy modelling exercise, attempting to engage a wide range of policy, public health, academic and community stakeholders – with only partial success. This has led me to reflect further on the notions of transdisciplinarity and participation in transport modelling. Rachel Aldred’s recent blog provoked me into re-visiting these challenges – her identified tension between small scale participatory narratives and Big Data modelling particularly struck a chord.

People from across disciplines emphasise notions of participation and transdisciplinarity as principles for decision-making that might improve outcomes for wellbeing, environmental sustainability and fairness (Dominique Charron and her colleagues at IDRC did a great job summarising this “ecosystem health” approach last year in a developing world context). Transdisciplinarity in this context tends to mean bringing knowledge from community, policy and academic stakeholders together on an equal footing. This involves the participation of community stakeholders in developing questions and decision-making, as well as increasing citizen control over solutions.

Community participation in urban planning has long been argued as a good thing – particularly if it is empowering and involves handing over some control over decisions to communities (see for example the work of Popay). A large number of health promotion and urban planning practitioners support the notion that empowering community participation in urban planning is required to achieve successful change for equity and sustainability, partly because of the limitations of representative democracy (giving a voice to the voiceless) and partly because successful joint learning can increase the support for resulting policies. In health promotion, empowering participation is also seen as a wellbeing end in itself – by increasing skill levels and a sense of agency over people’s lives (see for example the work of Glenn Laverack, Fikret Adaman and Pat Devine).

This is all sounds great, but very few attempts have been made to review the effectiveness of participation at achieving these outcomes. Beth Milton and her colleagues at the University of Liverpool systematically reviewed some of the evidence last year. Although participatory initiatives may have positively affected empowerment, information and relationships (intermediate capacity-building outcomes) there wasn’t much evidence that social or health outcomes were improved through changes to decisions.   Others argue that a focus only on empowerment as a positive outcome ignores a more complex set of roles and responsibilities on the part of individuals and authorities. For example, authorities may devolve the “work” of decision-making to community members without providing the resources to support this. There may be different levels of participation that are appropriate for different planning circumstances (Wilcox’s ideas about effective participation are getting old but are still useful).

A number of questions and challenges emerged from my own experience using a participatory modelling method to try and improve transport decision-making in Auckland.

  1. The priorities and knowledge of “community” stakeholders were best elicited through narratives about place – at a local level, yet to influence regional or national policy, there is a need to move from this local focus to regional/national level modelling. In my experience this transition resulted in losing the engagement of community stakeholders.
  2. It’s very difficult to keep any kind of transport model transparent and easily understood by the full range of stakeholders – there are methodological and skill (or art) questions here. Although it is necessary to understand system complexity, increasing model complexity can easily reduce transparency without improving decisions.
  3. It’s extremely easy for a participatory decision-making process to disempower and disappoint community stakeholders – especially when they are located within our current  neoliberal approaches to deliberative democracy (see a good recent critique in Paul Hanson’s recent Geoforum article, Toward a More Transformative Participation) – in other words, the priorities and solutions put forward by non-governance stakeholders are often in direct conflict with the limited set of possible policies within the governance framework.

I hope these challenges provoke interesting debate on the blog and during the seminars – particularly in one of the later seminars when we will focus specifically on participatory modelling.