Travelling a very short distance in the city, whether it be by car, train or bus can take a very long time and there are always some form of delays on the underground.
However, academics are hoping to ease this congestion by collecting data. CASA, the Centre for Advance Spatial Analysis at UCL is aiming to collect enough data on Londoners’ travelling habits to work out where we are going wrong. Dr. Jon Reades is a research associate at CASA and is currently examining data generated from Transport for London to discover where problems are arising and what efforts can be employed to reduce congestion and delays. Reades has only been studying the data feeds for a couple of months but already interesting findings are being discovered.
If there is a problem, you immediately get a message on your phone and you could have signage that updates itself automatically in the station
The fact that it is necessary to touch in and touch out with your oyster card when travelling on the underground is very useful in understanding where people are travelling to – in other cities it is possible to discover which station they went into but after that they disappear into the system.
One discovery is that the difference in the commute by people living in rich areas and more impoverished ones. Reades says, “People from wealthier communities seem to actually travel to fewer places than people from more deprived communities. When you look at the distribution of trips from say, Hackney Central, it is greater than the distribution of trips from South Kensington.”
From this data, one is possible to start making theories on why this is the case and more importantly, ways to alleviate the problem.
Reades says, “I think it connects back to traditional economics. If you are in a high skilled profession like banking there are really only two places you can go: Canary Wharf or the City of London, whereas if you are working in retail, shops are distributed all over London.”
Once this is realised it is possible to reorganise the service to suit the particular needs of the traveller. There could be more services provided from South Kensington going into the City for example and more diversified routes leaving from Hackney.
However, although the data will be helpful in fine tuning London travel services, through analysing the data, Reades has also developed a new found respect for the TFL in how it copes with so many millions of people travelling everyday. Reades says, “In some areas there are 4,000 people coming into the station every ten minutes. That is a small stadium outside of London going into one tiny location and somehow it doesn’t usually fall apart. It’s quite astonishing on that level.”
Resources are so tightly stretched that London travel is just about being held back from meltdown and with more people pouring into London each year the problem is only going to get worse. “We are always right on the edge of a total meltdown but that is because there are so many people trying to use a system that was built 150 years ago.”
As a pioneer of modern travel, London has been hindered somewhat by it’s own progress, whereas other countries have been able to learn from our mistakes before creating their own network systems. By applying knowledge garnered from these data streams it is hoped the transport system won’t be severely crippled in the future.
We are always right on the edge of a total meltdown but that is because there are so many people trying to use a system that was built 150 years ago
One idea Reades has is to use the data in real time to update a traveller with problems and suggestions for the best route. Reades says, “Maybe, if there is a problem, you immediately get a message on your phone and you could have signage that updates itself automatically in the station. So you are trying to interact with people both on an aggregate and individual level to help them get to work.”
The ultimate problem for London is that it is just too popular a destination.
Reades says, “Everybody wants to come and work in central London. Whatever kind of job, London is an attractive place to be. He adds wryly, “Detroit, for example, doesn’t have the same kind of congestion problem.” Let’s just hope that data can provide some more answers, sooner rather than later.