Transport to sports events

When I studied OR as a postgraduate, we were presented with several scenarios to reflect on their logistical problems. One was related to sports transport.

An event is scheduled at time T1 and finishes at time T2. Spectators arrive by public transport in advance of time T1. Their arrivals are spread over a considerable period, as their plans vary. Some may want to be very early, others arrive in the last few minutes. But the general distribution of their arrivals is widely spread. So the transport provision has to reflect this ... with vehicles scheduled over a wide range of times before T1.

On the other hand, at time T2, all those who arrived by public transport are ready to depart at the same time. So the public transport has to be concentrated into a much smaller time window.

These are the same sorts of problem that one meets in other circumstances, but the size of the crowds at some sports events make the contrasting problems particularly difficult.

OR has been used by the organisers of the recent Olympics to cope with this scheduling problem. And already, the London Underground OR team is planning how to cope with the 2012 Games.

Algorithms for better public transport

It is always pleasant when an operational research project is commented on in the media. I spotted this in Boing Boing, an online blog which I find fascinating and also frustrating. The story is about a research project into better algorithms for timetabling public transport, and has the acronym ARRIVAL, meaning
Algorithms for Robust and online Railway optimization: Improving the Validity and reliAbility of Large scale systems.

ARRIVAL is hosted in Greece (here), but has been an international research project, sadly without UK involvement. It has produced several published research papers, as well as practical solutions to transport problems.

Travels in a mathematical world

Throughout my career in O.R., I have had a dilemma about the role of mathematics in what I do. When I talk to other people on a casual, friend to friend basis, I often say that I do mathematics, and immediately add that I do the "Interesting stuff, the stuff with everyday applications". When I talk to clients or those sponsoring projects, I may talk about modelling. With students, I will talk about the mathematics that lies behind models, but will stress that these models need to be appropriate, easy to understand, and applied with political and psychological insights. As has been said many times, "A manager would rather live with a problem s/he can't solve than a solution s/he can't understand".

So I am not sure whether or not I ought to be recommending the website:
www.travelsinamathematicalworld.co.uk. It has accounts of careers in mathematical areas, as part of a process of making information about these available to a wide readership or listeners to podcasts. I came across the account by Professor Mike Maher, whose title is Professor of the Mathematical Analysis of Transport Systems at the (UK) University of Leeds. He describes the use of O.R. models in several areas of transport, mainly traffic assignment. He concludes:

"The skills that I enjoy employing are modelling skills - taking a real-world problem, and trying to formulate it as s mathematical problem with sufficient realism that the outputs can be taken seriously but simply enough to stand a chance of solving it. Then formulating some method, an algorithm, by which the problem can be solved efficiently and robustly. And in the field of transport, there is no shortage of problems!"

Isn't that what O.R. is about? Especially, I hope, "enjoyment".

Commuting Behaviour

A further observation from my trip to London is how there is a great difference between the social mix of commuters on public transport between Exeter and London. In Exeter, relatively few male executives use public transport. The rail lines are reasonably busy, but few males use the buses for commuting. But in London, it is quite normal and acceptable to use public transport. Of course, the infrastructure is better, but there is a difference in psychology as well. I wondered what research had appeared about the popularity of public transport commuting in cities of varying sizes.

It is relevant to O.R. because anyone working on transport models needs to remember the acceptability and feasibility of different modes of transport in different places. Behavioural psychology has its place in operational research.

Google turned up some figures for the United States. The comments are interesting. I wonder how much correlation there is between population and these percentages? And is there a similar set of data for other countries? And are there geographical effects to take into account?

RAW DATA: PUBLIC TRANSIT USE

Top 5 Cities for Public Transit Use

• 54.63% New York, NY
• 37.72% Washington, D.C.
• 32.66% San Francisco, CA
• 31.65% Boston, MA
• 25.92% Philadelphia, PA

With the exception of Washington , D.C. , every city here grew up in the horse and buggy days, with streetcar rail systems. The District of Columbia is part of the 1960-70s "graduating class" of newly subway-enabled cities, along with Atlanta (MARTA) and San Francisco Bay Area cities San Francisco and Oakland (BART). BART reaches regional airports, commuter rail systems CalTrain, ACE and Amtrak, and someday it may even roll down to suburban San Jose . Atlanta is planning to extend MARTA with its back-to-the-future PeachTree Street Trolley and improved bus service.

Bottom 5 Cities for Public Transit Use

• 1.07% Fort Worth, TX
• 1.03% Tulsa, OK
• 0.97% Oklahoma City, OK
• 0.54% Virginia Beach, VA
• 0.40% Arlington, TX

Surprise! These southern cities would benefit from re-installing light rail systems. Adding rail would provide residents relief from high gas prices -- and improve these cities' economic competitiveness. With air-conditioning thrown in, light rail would also provide relief from summer humidity.