Using big data to avoid Tube crowding (BBC)

Tucked away on Transport for London’s (TfL) website is a glimpse of what the future could hold for passengers so that they can avoid using public transport at busy times. Currently it is rather slow and clunky, but these graphs show when Tube stations are at their busiest.

What is interesting is TfL is using card data from Oyster and contactless on the gate lines to show how busy the station is, and the potential for data use on transport is huge. For example, it could mean transport authorities can be much smarter in how they develop their timetables. It could also influence how they build new infrastructure, set staffing levels and how often they open and close barriers to control the flow of passengers. It could even shift passengers into travelling at quieter times through clever ticket prices.

The data could also influence what messaging transport authorities put out. Commuters can be very receptive to messaging and so perhaps you could do very targeted communications at one station to get passengers to change their habits. Passengers are also creatures of habit. Could it, therefore, tell passengers that there are actually more efficient and quicker routes? In the future, it could help model how infrastructure is designed.

Lauren Sager Weinstein, TfL’s head of analytics, wrote in 2016 that valuable data could be used to “improve safety in London”. “We use big data to analyse trends from death and serious injury on the roads, which has allowed us to identify the major contributory factors and then better target preventative action.”…

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