Bus commuting made tolerable with real-time data

Thursday July 14th, 2011

Most of the whining and moaning about Sydney’s public transport is usually directed at the rail network. But just think a minute about having to commute by bus in Sydney to/from locations not serviced by trains – eg. the northern beaches. I have a long history bus commuting in Sydney so I am a qualified authority on the matter.

First of all you need to put up with a lot of old buses that leak and smell or you might get a new bus whose seats mistake your legs for sardines. Whichever bus you get, odds are you’ll be standing and wondering where your next molecule of oxygen is coming from as all the seated passengers keep the windows shut to keep the rain and wind out – and where do you put your bag? Try the laps of one of the seated enemy. Then your bus needs to deal with Sydney’s traffic…… Now’s about the time I start screaming.

On top of all this, before you even plan your commute, you need to navigate one of the most complex set of bus routes, timetables and numbering schemes known to man. And get this; even routes of the same number go to different destinations at different times of day. This system was not designed with simplicity as a driving principle.

But, after planning your trip and contemplating the “comfortable” journey ahead, you get to the worst bit: is the bus still coming or has it gone? Is it early or late? Is it on the road at all? Should I keep standing here in the rain and wait another 10 minutes for the next one or should I take the one that’s here now but goes to a slightly different place but might get me there faster? When the next one gets here, will it stop or will it be full and not allow me on? Gosh, I can’t wait to get to work and start my high-stress day in my high-stress job – then I’ll really be able to relax. Sydney’s traffic, bus congestion levels and other “Sydney” factors make relying on the buses a bit like relying on your cat to take out the garbage.

Not having up-to-the-minute information about where your bus is and when it is expected to arrive is the most annoying and frustrating aspect among all the challenges of bus commuting listed above. It is the one thing that has driven me, with rage, into a 2nd family car. Yes, I am one of those losers that sits in a 5-seater car on my own clogging up Sydney’s roads and doing my bit for global warming. If there was some real-time information guiding me and smoothing my daily commute then I probably would not have switched.

If all bus commuters had that real-time information, how much more efficiently would the bus network be used and how many more commuters would it attract? There is massive value to the state government even before you consider the benefits to the general community derived from happier bus commuters.

That is why when I read this newspaper article I was so disillusioned.

In summary, the article talks about how State Transit provided real-time bus location information for public consumption; a developer built an iPhone app to deliver the information out to passengers; the app then became so popular that State Transit had to shut down the data service because it couldn’t provide a “reliable and sustainable” feed.

No wonder there were 200,000 views in 2 weeks – the depth and the timeliness of the information, along with GPS and radio networks and mobile computing technology combine to provide a very powerful application. And with today’s technology and tools, it’s not really that hard to deliver.

Although, State Transit obviously found that sourcing and integrating the data, then making them available to service thousands of users with quick responses to many different types of targeted queries while minimising outages can be the hard bit …… that is, if you are using sub-standard database technology. If you are using database technology that scales linearly and is engineered from hardware components through to application layer to be highly resilient, then the “sustainable” part of the puzzle is solved. Add to that; parallel streaming data loading mechanisms, best-in-class query optimisation and workload management and the “reliable” part is also solved.

So come on State Transit, think outside the square and employ the right technology so you can turn that data hose back on again.

Get me back on the buses. 


Greg Taranto

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One thought on “Bus commuting made tolerable with real-time data

  1. avatarSundara Raman

    Greg, Good on you mate! Very nicely written blog! Good use of visual imagery and sense of humour! Best of luck getting back on public transport!


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