Everyone who thinks about the future of transportation wants to know what will happen to our cities and our lives when autonomous vehicles arrive.

We're exploring how to model demand for autonomous vehicles (AV's) with a passive data model like
CityCast. We've structured our investigations following the thoughts of Lauren Isaac, who proposes that the positive or negative effects of AV's largely rest on whether AV's end up being privately  owned or shared among several users. We covered the shared scenarios in our last post,
and we're now back as promised with private scenarios.
 

We've been doing some explorations at Transport Foundry over the last few months on how to model demand for autonomous vehicles (AV's) with a passive data model like CityCast. In this post we're going to look some scenarios where AV's are shared,  where anyone can access the vehicles for a marginal fare.

Given the long runways inherent to custom surveys, if the data needed to model autonomous vehicle (AV) behavior have not already been collected, then AV's will arrive before models designed to study their effects. In this study, we use demand from a passive data model coupled with the replanning algorithms in [MATSim](http://matsim.org/) to examine how transportation networks might be affected in the near term by autonomous vehicles.