This somewhat-unexpected topic came up in several offline conversations during the Stuttgart symposium
On day 1, I had a discussion with a guy who gave the lecture “Impact of driverless mobility on vehicle development and testing” (Thomas delos Santos, CEO, Innovative Mobility Automobile GmbH, Germany).
His is a small consultancy house which consults e.g. cities on what AVs will do to them. They use their brains, a whiteboard and at most a spreadsheet.
I liked his lecture, and asked him if he considered using simulations for looking at possible futures. He did not, but after I described what I think such a system could do, he thought it could be useful.
Two days later, I was sitting next to a few Danish guys, and we were discussing AV-related public policy, and how can we foresee its implications. I related to them the story of the consultant (above).
I then mentioned the famous case of the Oresund bridge between Denmark and Malmo, Sweden: The story goes that they tried hard to estimate the future traffic on that bridge, but failed to consider the fact that house prices were so much lower on the Swedish side, that many Danish people simply moved to Malmo and travelled to work back across the bridge each day.
It was lucky that I did not continue talking about this too much, because one of the people at the table (Prof. Per Homann Jespersen, of Roskilde Univ. in Denmark) is a transport policy guy with intimate knowledge of this bridge’s history and similar projects. They are now working on similar, policy-related simulation systems (but they certainly had nothing like that at the time).
Everybody agreed that this is a good direction to go, even considering the usual caveats:
- Simulations don’t give you an “answer”, just a range of possibilities to help your thinking
- You need to take into account the various “unknown unknowns” (the classical “nobody predicted the iPhone” example came up)
- The simulation model becomes stale and has to be updated from time to time.