Travel Patterns / Revealed

Travel Patterns / Screenshot

Travel Patterns / Screenshot


This Processing application has the purpose of revealing travel patterns for Disabled Freedom Pass holders (DFPH) and comparing them to non-disabled Oyster card users (NDOCU). When launched, on the left half of the screen, the application shows trips as lines from a station to another throughout each minute of each day of a week. The trips have different coloring, with red representing DFPH trips and white representing DFPH.

On the right half of the screen, seven graphs are plotted, representing the days of the week from Sunday to Saturday. The length of the vertical lines of the graph represents the load of the tube at each time step. Again, the white lines represent NDOCU and the red DFPH. As the week progresses, we clearly see that the white lines have notable peaks during the morning and afternoon rush hours, whereas the red lines have no peaks. This is likely because people with limited mobility may have a tendency to avoid use of the Underground if other options are available to them, particularly during peak times, and as indicated in the data, 83.9% of DFPH trips are made on London Transport Buses.

The app is interactive, and by hovering the mouse over each station, the user can see the name of the station, whether the station is accessible or not, and two line-graphs. One shows the load of the station compared to the mean load of all stations (thus, its popularity) for DFPH and NDOCU. These graphs help us understand how much a station is actually used, also compared to its general load of passengers. Finally, another two options are added, where the user can choose to show all step-free access stations, or all stations ranked according to their total load of passengers (where the radius of each circle represents the percentage).


p.s.: there will soon follow a github link to the code




The city is its people. It is the people it houses and the people it bears on its streets and infrastructure. People move within the city and its public spaces, venues of social interaction and economic exchange, which are the predominant activities that constitute cities. The city must be able to host and accept all of this movement and exchange within and around its public spaces, so that it can offer people the opportunity of being more active and socially engaged. It must truly offer the possibility of limitless exploration of public space and the opportunities it affords. For this to be, the city has to be equiped with adequate infrastructure for people to use and move around its clusters of social and retail spaces. The ever increasing size of cities also means that transportation infrastructure is increasingly essential for the mobility of city citizens. It is, therefore, a fundamental role of the city to provide its residents with sufficient and equitable access to its streets, public spaces, and transportation network.


If public space is not available for all, then it is no longer truly public. It is limited-to-those-who-have-access-to-it space. What defines a space as public is its accessibility. The term accessibility refers to a space being and feeling open and accessible to all. Accessibility issues are raised when a space is not accessible to all. Many spaces seem to be designed for the stereotypical white (western) successful male in his prime. The more a person deviates from this “ideal” the more inaccessible a space might be or seem. And deviations can have the nature of race (asian or african), gender (woman or homosexual) or ease of mobility (disabled, blind, deaf, elderly, pregnant women, new parents carrying buggies).


For our project, we chose to focus on the work that has been done to make public transport available for people with limited physical mobility, such as wheelchair users. Observing London, we can see, seemingly everywhere, a significant attempt to make spaces, buildings, and public transport, accessible to this group of the population. Our goal is to explore to what extent these are used in relation to the general population and the general use of these spaces. It is an attempt, in a sense, to derive how effective the efforts towards improving accessibility have been.

We believe that a city can only be truly active and engaged when all of its citizens are afforded the same opportunities to fully engage with it across space and time. We recognise that London is developing mechanisms and techniques to get everyone involved in its daily activities, to help it breathe and grow. We therefore want to detect whether these techniques work effectively enough, and how they contribute in making London active. How successful is London in getting everyone involved in its somewhat frenetic pace?!


As mentioned before, in order to answer some of our questions, we are focusing our exploration and research on the use of the public transport network by people with disabilities. We will try to show, through the data we have available, to what extent the public transportation network is used by Oyster Disabled Free Pass holders. We hope that this approach and visualisation will illustrate a number of potential issues concerning the accessibility of public transport.


We recognise that we are setting off with quite a goal, and what we have at hand is hardly able to prove anything conclusively. What we will try to do, however, is to visualise and representat the information we can extract from the data that we have available. A lot of assumptions are made, and a lot of numbers are generalised to make the results communicate the most they can. We know that our sample is limited, because not all residents of London that have a disability request a free oyster pass. We also know that not all Oyster Disabled Free Pass holders use public transport. We are keeping the process open to the reader/viewer, so that they themselves can choose what conclusions to keep or derive from this exploration.

We have obtained a 5% sample of Oyster Card trips made in November 2009 within London’s public transport network. We have data on the types of users using each means of transport. Initially, we extract the data related to disabled pass holders and we present this data in contrast with the rest of the users. The results are yet to be seen.