Automated Intersection Management with MiniZinc
  Ill-managed intersections are the primary reasons behind the increasing
traffic problem in urban areas, leading to nonoptimal traffic-flow and
unnecessary deadlocks. In this paper, we propose an automated intersection
management system that extracts data from a well-defined grid of sensors and
optimizes traffic flow by controlling traffic signals. The data extraction
mechanism is independent of the optimization algorithm and this paper primarily
emphasizes the later one. We have used MiniZinc modeling language to define our
system as a constraint satisfaction problem which can be solved using any
off-the-shelf solver. The proposed system performs much better than the systems
currently in use. Our system reduces the mean waiting time and standard
deviation of the waiting time of vehicles and avoids deadlocks.
