2017-05-05 – David Levinson, Transportist

I will appear on ABC (Australian Broadcasting Corporation) RN (Radio National) show Future Tense Sunday 7 May 2017 10:30AM. They also have a podcast.

In Japan they’re constructing a passenger train system that will travel at speeds in excess of 600 kilometres an hour. Now that’s fast, but it’s not fast enough for some. New Hyperloop technology promises the speed of sound. But can a train really go that fast? And why would it need to travel in a vacuum tube?

Also, we meet a man with a revolutionary new approach to runway design. He wants airports to look and function like velodromes, with planes landing and taking off on a donut-shaped runway.

Guests:

Zachary McClelland – project leader, VicHyper, RIMT University

Edouard Schneiders – team leader, Delft Hyperloop, Delft University of Technology

Dirk Ahlborn – CEO and founder, Hyperloop Transportation Technologies

Steve Artis – Director, Ultraspeed Australia

Professor David Levinson – School of Civil Engineering, University of Sydney

Hesse Hesselink, Researcher, Netherlands Aerospace Centre

Update, with Transcript

Anthony Funnell wrote this up: Hyperloop or hyper-loopy? The race to make high-speed tube travel a reality. I abstract my bits below.

‘Human factor’ a complication

Both HTT and Hyperloop One are yet to do field tests using human passengers.

For this reason, the University of Sydney’s David Levinson argued it was premature to be building a business case.

Listen to the program

Hyperloop tech promises travel at the speed of sound. But can a train really go that fast?

“They’re going to put people into a sealed container and accelerate them at very high rates of acceleration, sometimes around curves,” he said.

“We don’t know how normal people will react to that because we haven’t done that before with normal people.

“This is sort of test pilot territory. People aren’t going to be really excited about being in a rollercoaster for a very long period of time.

“Yes, people have flown at 1,000kph in the Concorde — but there’s a different type of acceleration and deceleration profile associated with that.”

Dr Levinson, a professor of transport engineering, also has safety concerns.

“Track inside a tube is really pretty vulnerable to attack,” he said.

“How does such a thing respond if the tube gets punctured? What happens to the capsules that are inside of it? Does it gracefully decelerate or does some sort of implosion happen?

“People are going to expect something like this to be as safe or safer than trains or aeroplanes if they are going to be entrusting such a company with their lives.”

Recently published:

Ermagun, Alireza, Chatterjee, Snigdhansu, and Levinson, D. (2016) Using Temporal Detrending to Observe the Spatial Correlation of Traffic PLoS One. 12(5): e0176853. [doi]

This empirical study sheds light on the correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the correlation between 140 freeway traffic links in a sub-network of the Minneapolis – St. Paul highway system with a grid-like network topology. This topology enables us to juxtapose positive correlation with negative correlation, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective to the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted correlation structure can augment the accuracy of short-term traffic forecasting models.