Big Data – Coming to a Bus Near You

Big Data taking the grind out of the grind

In congested cities, getting from one place to another in good time would be almost impossible without public transport services. The London Underground, for example, handles up to five million journeys per day. Despite the vast amount of passengers that use buses, trains and tubes, very few people would say that they liked public transport. It’s not hard to see why. Delays, traffic and overcrowding are just a few of the components that can make public travel a less than pleasurable experience. Fortunately, there is a solution to these problems. Big data.

Big data in public travel
If you live in a city, you’re probably familiar with the Citymapper app. Set up in 2012, Citymapper is now used in 40 countries worldwide. The app tells users which are the fastest and easiest routes to take to get to where they need to be. It does this by compiling open data, their own travel metrics and data from their partners, including Google, Apple, Yelp and Uber. With such a wealth of information about so many urban centres, it’s a wonder that they haven’t started their own public transport service. Earlier this month, however, they did exactly that. On May 9th, Citymapper launched a pop up bus route called CMX1 that ran for two days in Central London. Bright green, 30 seater ‘Sprinter’ buses ferried passengers between Southwark and Blackfriar’s, equipped with USB charging ports, informative passenger screens and a tablet relaying real time data to the driver. CEO Azmat Yusul explained that the temporary service was the first part of a conversion into fully fledged, dynamic public travel. Looking forward, the company plans to release a fleet of ‘Waze buses’ that will change routes according to data.

How will big data disrupt public transport?
Tech has already changed public travel, from the Citymapper app itself to live departure boards, but this is only the beginning. What makes Citymapper’s Sprinter buses potentially disruptive is their use of real time data to influence the way that vehicles run. Collecting and utilising big data could transform travel by enabling public modes of transportation to react to the surrounding environment. Instead of waiting in traffic queues on one route, the driver can pick another one. This alone could improve the reliability, efficiency and safety of bus services, not to mention passenger comfort. Travel data could help to reduce overcrowding by notifying drivers about how many passengers are on board. This could be very useful for underground services during peak travel times, as well as busy trains and trams. Applying big data to transportation also represents another step towards autonomous vehicles (AVs). The Advanced Autonomous Systems Innovation Centre at the University of Nevada, for example, aims to release autonomous buses by 2019. Perhaps unsurprisingly, Tesla also has plans to develop AVs for public travel. The data that is collected, shared and used by companies like Citymapper will become a vital tool for driverless vehicles, and will help to create successful smart cities by connecting vehicles and road infrastructure. Eventually, buses will be able to operate entirely on transport metrics. This isn’t a welcome prospect for drivers, who will become more or less obsolete. However, an entirely new transportation network will still need an army of central operators and monitors.

The application of big data within public transportation is a clear demonstration that in depth metrics can provide a potential solution to many of the issues that we experience today. As the roads becoming increasingly congested, especially in big cities, it’s more important than ever to solve the many problems associated with public travel. Citymapper isn’t the only company to enhance transportation with data, but they are the first to showcase an exciting proof of concept that uses information to improve the efficiency and flexibility of public journeys. This data will become integral to the integration of self drive technology, allowing vehicles to respond to real time events. In short, public transport will be driven by data.

Is big data the answer to long standing public transport complaints? How else might big data improve passenger experience? Will people trust data driven transportation? Share your thoughts and opinions.