Privacy-Preserving Intersection Management for Autonomous Vehicles

Traffic lights are a common instrument to regulate
the traffic in junctions. However, when a vehicle
has an urgency, it may violate the traffic lights.
Since the other vehicles do not expect this, such violations
lead to road accidents. Connected and autonomous
vehicles can coordinate their actions and
decide on the priority of passing without the need
of traffic lights if they can share information about
their current situation. That is, a vehicle with an urgency
can communicate this with justifications to
others and ask to go first. However, the shared information
can potentially yield privacy violations
while helping vehicles attain priority. We propose a
privacy-preserving decision making framework for
managing traffic at junctions. The vehicles are represented
as autonomous agents that can communicate
with each other and make priority-based decisions
using auctions. The bids in the auctions are
not monetary but contain information that each vehicle
is willing to declare. Our experiments on realworld
accident data show that our proposed bidding
strategies help vehicles preserve their privacy while
still enabling them to receive priority at junctions.