  This paper extends our previous work in [1],[2], on optimal scheduling of
autonomous vehicle arrivals at intersections, from one to a grid of
intersections. A scalable distributed Mixed Integer Linear Program (MILP) is
devised that solves the scheduling problem for a grid of intersections. A
computational control node is allocated to each intersection and regularly
receives position and velocity information from subscribed vehicles. Each node
assigns an intersection access time to every subscribed vehicle by solving a
local MILP. Neighboring intersections will coordinate with each other in
real-time by sharing their solutions for vehicles' access times with each
other. Our proposed approach is applied to a grid of nine intersections and its
positive impact on traffic flow and vehicles' fuel economy is demonstrated in
comparison to conventional intersection control scenarios.
