transport statistics


motor mowers and battery powered mobility scooters from Coleraine to Cork. His data capture hardware is, like Bloodhound’s, based on off-the-shelf Intel Atom-based hardware, though his sampling resolution is only five seconds from just over 120 concurrent channels and his analysis is in Maple, R and MiniTab. Tis is an entirely serious undertaking, designed (like Bloodhound) to generate data and starting points for new lines of thinking. Perhaps of more immediate impact


are the studies (see Box: Walking back to happiness?) of links between healthy lifestyle and the development of infrastructures designed to encourage walking and cycling. Infrastructures are at least as much a


result of transport as shapers of it. While Phillip Pullman painted in Te Amber Spyglass[4]


an intriguing picture of a world


where pre-existing geological flows favoured a symbiotic vegetable and animal evolution leading to natural development of the wheel, in our own world it has been very much the other way around. Natural communications such as rivers decided the initial throw of settlement patterns, but then paths were beaten between them. Te wheel required long, flat ribbon roads that were laid as enhancement of, rather than to provide, the routes for transport. Tis ever-expanded network of flat, wheel- friendly surfaces has progressively shaped the landscape wherever humans are found, in a circular structure of cause and effect, but one driven by transport demand. Tis sort of big picture is very easy to see in


historical hindsight, but not always as clearly visible as it happens. It has been hypothesised for a long time that transport foci are laying the foundations for new urban structures and defining new transport configurations in their turn. Any hope of influencing or even


Further information Ansible Motion http://ansiblemotion.com Bloodhound project www.bloodhoundssc.com Boston Dynamics www.bostondynamics.com Connect2


www.sustrans.org.uk/ what-we-do/connect2


DARPA www.darpa.mil


iConnect www.iconnect.ac.uk


Maplesoft www.maplesoſt.com


MathWorks www.mathworks.com


Minitab www.minitab.com


Modelica Association


www.modelica.org


R Project www.r-project.org


SAS www.sas.com


VI-grade www.vi-grade.com


Wolfram Research www.wolfram.co.uk


riding the wave fronts of change relies on attempting to get an overview of development mechanisms from within them, as they happen. In assembling such a big picture on the fly, however rough, data analysis is one of the best tools available. Airports are a particular focus of interest


in this respect, with debate over the posited emergence of ‘airport cities’. A paper[5]


in


Urban Studies for example, due to appear shortly before this issue of Scientific Computing World, analyses data showing that employment density within a four kilometre radius of large US airports runs at around 50 per cent (and increasing) of that in similar proximity to the commercial and business centres of their associated metropolitan areas and, most interestingly, anchors a considerable level of commercial activity unrelated to the transport function of the airport. Similar analytic programmes exist


elsewhere. A consortium of transport and social science specialists from half a dozen


Walking back to happiness?


It’s generally taken for granted that policies favouring the development of environments that make walking and cycling easier, and car driving more difficult, will pay dividends in health and a reduced carbon footprint. A study in the Australian state of Victoria[6]


explored attitudes to public


health promotion policies, and found that those shaping environmental infrastructure earned approval while those that sought to encourage healthy eating environments did not. There is, however, remarkably little research into how true this assumption of infrastructural benefit might be in practice.


www.scientific-computing.com There is currently a major new Sustrans


programme, Connect2, seeking to promote the development of walking and cycling routes in the UK through targeted infrastructure projects in 79 communities. This provides an opportunity for study of the extent to which levels of walking and cycling, physical activity in general, and carbon emissions actually follow implementation of infrastructural changes. That study[7]


is iConnect, which aims


(in partnership with several universities and other academic agencies) to integrate public health and transport research perspectives in the measuring, analysing and evaluating these posited linkages.


Three of the project areas (Cardiff,


Kenilworth, Southampton) were selected for cohort study, with residents living within a five-kilometre radius of these becoming the experimental subjects. Demographic and socioeconomic data were gathered before and after the new infrastructures were opened, along with specific data on travel, car fuel purchasing and physical activity. Potential psychosocial and environmental correlates and mediators of those behaviours were identified. The iConnect study has its own .ac website, which acts as dissemination hub for results as they emerge.


DECEMBER 2012/JANUARY 2013 11


British and German academic institutions, funded by commercial and national development sources, is currently building a generic study model of metropolitan evolution within the catchment areas of European airports. Although generic, the model is being constructed using rules constructed (and allowed to grow in real time) from statistical analyses of real data from real specific locations. Te model core is being built in Modelica, as a common platform, though there is much traffic between it and satellite models involving diverse tools including Matlab, Maple and MapleSim or Mathematica. Te analytic side is similarly structured: a common basis in R, with subsidiary handling in everything from SigmaPlot to SAS.


As always, I have (inevitably) only had


time to scratch the surface of computerised data analytic involvement in transport. Railway logistics is a big consumer; so are the scheduling, procurement, fare distribution and numerous other operations of the world’s airlines. Rapid transit systems are data-intensive; one underground railway systems analysis team I worked with on a research study referred to their data validation procedures with black humour as ‘Te ticking of Pelham: 1, 2, 3’. Te space industry, which transports equipment and other commodities into orbit, draws down streams of data for its own consumption is oſten working in the service of clients for who data collection is the whole point of the mission. Data, data, data, wherever (and however) you go!


References and Sources For a full list of references and sources, visit www.scientific-computing.com/features/ referencesdec12.php


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