Making Buses better with Open Data

Taking the bus can have its stresses. Every passenger has stood in the rain worrying that their late bus isn't coming at all and asked: "why didn't I take the other option?"

Some issues around the passenger experience require deep reform – most notably ensuring that buses have sufficient priority and road space. According to the UK passenger survey, congestion puts off more riders than any other factor1. Statistical evidence bears this out: a recent study finds a 10% decline in operating speeds corresponds to a 10% fall in patronage2. This is reflected even in London which has 50% of England's bus journeys3. Despite the congestion charge, extensive bus lanes, and scarce parking, bus speeds have declined and had a knock-on impact on passenger demand.

However, KPMG considers that softer measures can also be implemented to make buses more pleasant, and so hopefully more popular. Amongst these are providing more data to passengers to better inform travel choices.

There is a lot of bus data out there, but it's not always obvious to passengers how to get to it. With a quick Google, you can find PDF routes and timetables for all regular services. Prices take a little bit more digging. However, real time information is patchy.

As a teenager, I remember walking an extra five minutes to the bus stop that had a simple digital screen showing arrivals. Since then, increasing real time data has improved journeys in select areas of the country. With this data, instead of arriving just-too-late, you plan when to leave your house. If the service has serious trouble, instead of waiting in the rain, you can use real time data to choose another route.

Examples from around the world show how real time data, even in inconsistent closed formats, saves users time and improve the journey experience.

For example, in an experiment in The Hague, users reported waiting 20% less after a real-time data system was installed4. Intriguingly, this early 2004 project only provided real-time data on platforms, suggesting this reduced wait time was purely subjective – time dragged less when passengers knew when the tram was coming. A similar US study found a 30% gap: riders overestimated their wait time without real time data5.

If all extra data did was make individual bus customers feel better it would be a worthwhile outcome. But the realistic alternative to the bus in most of the UK is driving. Therefore, if people chose to take the bus, the result is less congestion, and less pollution - we could be killing several birds with a single stone.

Real time bus data launched in New York City borough by borough. This natural experiment allowed economists to study the effect on ridership6. This suggested that the availability of real time raised ridership by 1.7%. Similar studies have also shown modest, but significant results.

To this end the Department for Transport is requiring bus operators to submit their data, and creating a portal that makes it simple and painless to do so. They are then making this data open, so that app developers can create software that will deliver the data to passengers and other users in convenient and intuitive apps. And they are taking steps so that this will eventually encompass the holy grail – real time data on where buses are and will be.

Taking the bus needn't be a pain. If you can sit at home and work out when your bus is coming and how much it will cost, then you won't waste your time standing at the stop fretting. There are 2.2bn English bus journeys per year outside London. Hopefully we can make them better with open data.

Ben Southwood, Analyst, Infrastructure, Government and Health – Data Analytics, KPMG

1. TransportFocus. "Bus Passenger Survey: Autumn 2017 Report." (Mar 2018)
2. Begg, David. The impact of congestion on bus passengers. Greener Journeys, (2016)
3. Department for Transport. "Transport Statistics, Great Britain 2018: Moving Britain Ahead." (Nov 2018)
4. Dziekan, Katrin, and Arjan Vermeulen. "Psychological effects of and design preferences for real-time information displays." Journal of Public Transportation 9, no. 1 (2006): 1.
5. Watkins, Kari Edison, Brian Ferris, Alan Borning, G. Scott Rutherford, and David Layton. "Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders." Transportation Research Part A: Policy and Practice 45, no. 8 (2011): 839-848.
6. Brakewood, Candace, Gregory S. Macfarlane, and Kari Watkins. "The impact of real-time information on bus ridership in New York City." Transportation Research Part C: Emerging Technologies 53 (2015): 59-75.