Choosing how to travel

When operational research was in its infancy, many O.R. teams prided themselves that they were interdisciplinary.  As the subject has matured, it has become increasingly specialised and a little distant from the idealism of the infant interdisciplinary pattern.  Before I am targeted by correspondents who do work in interdisciplinary or multidisciplinary teams, I know that there are many teams where insights from  biology, engineering, mathematics, physics, psychology and zoology are brought together to solve problems.  But for many people doing O.R., the impact of disciplines other than the corpus of operational research techniques only comes from the language of the client, whether the client is in advertising, production or finance.

What makes me think of this?  A friend was sent a U.K. government brochure, "Britain in 2014", subtitled "Your essential guide to the issues that matter" and produced by the U.K.'s Economic and Social Research Council (E.S.R.C.).  The contents describe a number of sponsored research programmes, without getting into technical detail.  There were many interdisciplinary programmes, and many were tackling the type of "What happens if?" questions that O.R. specialises in.

So I was both interested and disappointed to read an interesting article about commuting to work by bicycle, which has been using GIS data to study peoples commuting in several cities, and modelling behaviour using agent-based simulation.  (Actually, not many O.R. studies in the literature use agent-based simulation, which is also a shame.)  Interested, because throughout my career, I did commute to work by bicycle.  Disappointed, because it was an ideal piece of work for the skills of O.R. to have contributed to.  The link for the reports is here.   It was part of a wider study of transport options for the future in cities.   I wonder whether there were O.R. people who could have helped but for their own reasons did not.  From my own academic experience, it is difficult to work across academic departments; maybe we have dug our own compartments in the ivory tower?  And to write this is not to be critical of the researchers; they have done an excellent job;  it was a study that I would have loved to be part of.

Commuting patterns vary across the country.  London has a very high proportion of commuters.  Parking cars in the city is very expensive.  But the study draws in the GIS and usage data for the use of "Boris Bikes" (cheap hire bikes available across London) which show how many commuters are using these bicycles every day.  Their behaviour has changed because the bikes are available.  What would happen if similar hire bikes were made available in another city?  Agent-based simulation would help answer such a question.

The data for studying commuting falls into the current themes of "Big Data" and "Analytics"; but some of the modelling tools are well-known from the established O.R.corpus - network flow models, epidemiology, time series analysis, stochastic processes. etc.

So, here is a quote from the short report in "Britain in 2014":

The practice of cycling to work can change, with meanings, abilities and stuff all connected.
For example, in the 1980s, virtually no one wore a cycle helmet in the UK; now it is often seen as essential. But this supports cycling being seen as a dangerous activity requiring specialist gear (in high-cycling countries, people wear everyday clothes). The ‘stuff’ you need to cycle depends on what you think cycling means, and what others do. Similarly, the ‘abilities’ you need depend on the cycling environment, and the demands it places on users. 

The project team is developing a model that will represent these practices and how they change, as people interact with each other. The approach, agent-based modelling, represents decisions of individual cycle commuters (agents) who learn from and influence each other and their environments. An agent will only cycle to work if she/he thinks she has enough abilities and stuff to cycle, and on balance cycling has positive meanings for him or her. The stuff, skills and meanings that make up the practice of cycling will vary from place to place.

The project will then explore the medium term impacts* of policies, such as building cycle paths or providing cycle training, as they affect the stuff and skills people think are necessary or as they change the meanings associated with cycling. The impact is then played out through the social networks. For example, improving infrastructure might reduce the skills needed to cycle meaning a wider range of people feel able to cycle. Other people then see these different kinds of people cycling or hear about their experiences, changing the meanings of cycling.

* "What happens if?"

How do we make other researchers be aware of the skills that operational research might contribute to their programmes?  

I followed links from the project's webpage to find some splendid maps of transport in the UK, and - nothing to do with O.R. - interesting and amusing maps of London. 


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