Along with other intelligent traffi c control schemes, autonomous
vehicles present new opportunities for addressing traffi c congestion.
Traffi c simulators enable researchers to explore these possibilities be-
fore such vehicles are widespread. This thesis describes a new open
source, agent-based simulator: the Approximately Orchestrated Routing and Transportation Analyzer, or AORTA. AORTA is designed to
provide reasonably realistic simulation of any city in the world with
zero con figuration, to run on cheap machines, and with an emphasis
on easy use and simple code. Experiments described in this thesis
can be set up on a new city in about five minutes. Two applications
are built on AORTA by creating new intersection control policies and
specifying new strategies for routing drivers. The first application,
intersection auctions, allows humans to instruct their autonomous vehicle to bid on their behalf at intersections, granting them entry before
other drivers who desire conflicting movements. The second, externality pricing, learns the travel time of a variety of di fferent routes and
defi nes a localized notion of cost imposed on other drivers by following the route. This information is used to tax drivers who choose to
improve their own trip by inconveniencing others. These two systems
demonstrate AORTA's utility for simulating control of the traffi c of
the near future.http://www.aorta-traffic.orgComputer Science
