Thursday, April 23, 2015

Big data could power on-demand public transport



SINGAPORE — The authorities are looking at piloting a public transportation service, which can be activated at the drop of a hat for deployment at places where demand for both taxis and buses heats up, the Infocomm Development Authority (IDA) has revealed.

It is envisioning 20-seater mini-buses for this on-demand express shuttle service, which can run ad-hoc routes with limited stops and levies fares that fall between what commuters pay for taxis and buses — somewhere between S$5 and S$10. Pre-booking should also be an option.

The IDA’s deputy director of Government Analytics Liu Feng Yuan floated the idea at the Smart Nation Innovations Forum yesterday, saying his agency is looking at engaging user groups to start a pilot. With big data, routes where express services such as this could be popular can be spotted, he added, noting that Finland already has something similar.

“Why do we have fixed bus routes instead of flexible timings? It is because we didn’t have the data,” he told participants at a forum called Adaptive Transportation with Data Science.

Flashing data of the number of taxi pick-ups and bus traffic in various areas on a screen, he cited one possible route plying from Marine Parade to OUE Bayfront, where demand for cabs and buses was heaviest between 8am and 8.30am.

“I don’t know how many are willing to pay for an express shuttle, but I know there is a demand ... There are quite a lot of large areas where we can potentially run such an express shuttle,” said Mr Liu.

No details were given as to who would oversee the service or when it could be rolled out.

But several conditions are needed for something like this to work, said Mr Liu.

For example, 20 passengers must be gathered within 15 minutes and the number of drop-offs must be kept to a minimum, so as to ensure a faster commute.

Mr Liu added: “You need to know where (to deploy the service), because if it is going all over the island, it makes no economic sense. You need to know where all the popular corridors are.”

Commenting on the idea, Dr Park Byung Joon, head of the Urban Transport Management programme at SIM University, said that while the idea is “great”, it is not working so well in Helsinki, where the service is run with public money.

“They did not really think it through and used big data to identify the routes. They tried to cover too big an area with a small number of buses, and it became very random,” he said.

“The result was that not enough routes were created and not enough people were pulled in.

Policymakers need to really utilise big data in order to make this work, he added.

National University of Singapore transport analyst, Professor Lee Der Horng, also said the idea of using big data to plug service gaps works in theory, “but in terms of actual implementation, it’s a question mark”.

“It will work in countries where public transport is really weak, but I think it is not the case in Singapore,” he said.

“Big data also does not tell you the actual behaviour of people, whether they will take this up, although you can try to infer behaviour from data.”

[I want to believe this will work, but I suspect Prof Lee is correct.

The two existing public transport mode are fixed route buses (and trains - which by definition is fixed), and taxis.

This ad hoc express bus service is to fill the gap between these two existing service. But it is a bus, and it is a twenty seater, so it is closer to the Bus model. Closer to the taxi model is cab sharing. Which was tried out some years back, and never really caught on. But even then it was possible (though not very viable) without big data. With Big Data, perhaps this could be enhanced, more feasible? 

This would be better than the inefficiency of cabs ferrying just one passenger.

What Big Data can do is to link up or adapt to Uber or similar services/platform and provide enhance cab-sharing.

Our existing and growing network of buses and trains will mean there will be low demand for the Ad Hoc Express Bus service. It is unlikely to be that much faster than transit (bus & train), and less convenient that a cab.

I think what will make this work (it it can work) is Big data, and autonomous vehicles. ]

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