This is a great article - it's a set of really clear explanations of several complicated topics, and kudos to the author for bringing it all together so well. It reminds me of the research we conducted at Ultra PRT when building the Heathrow Pod (a driverless taxi system) [1] and evaluating much larger networks on campuses and in cities.
One aspect I didn't see in the analysis is the effect of a passenger's willingness to rideshare on the effectiveness of the algorithms - we found it can have a pretty dramatic effect on system efficiency[2], especially when operating near capacity (as you'd expect). Does anyone who's used this system have any experience of this? What happens if passengers refuse to share or request a different ride?
Unlike UberPool or Lyft Carpool, TransLoc OnDemand rides are serviced by transit agencies, most of which use shuttles or even full-size buses. There's no choice to share or not share a ride.
As another Ultra alumnus, I also enjoyed reading this article. It's great to see algorithms like this making a real difference in transit, instead of just being simulated.
It was a somewhat different problem, but FWIW I had more success with the Cross Entropy Method than with Simulated Annealing [1,2]. Maybe one for future research :)
One aspect I didn't see in the analysis is the effect of a passenger's willingness to rideshare on the effectiveness of the algorithms - we found it can have a pretty dramatic effect on system efficiency[2], especially when operating near capacity (as you'd expect). Does anyone who's used this system have any experience of this? What happens if passengers refuse to share or request a different ride?
[1] http://www.ultraglobalprt.com
[2] https://www.researchgate.net/publication/31589946_Ride_Shari...