Biblio

Today's increasingly populous cities require intelligent transportation systems that make efficient use of existing transportation infrastructure. However, inefficient traffic management is pervasive, costing US\$160 billion in the United States in 2015, including 6.9 billion hours of additional travel time and 3.1 billion gallons of wasted fuel. To mitigate these costs, the next generation of transportation systems will include connected vehicles, connected infrastructure, and increased automation. In addition, these advances must coexist with legacy technology into the foreseeable future. This complexity makes the goal of improved mobility and safety even more daunting.

We propose a framework for generating a signal control policy for a traffic network of signalized intersections to accomplish control objectives expressible using linear temporal logic. By applying techniques from model checking and formal methods, we obtain a correct-by-construction controller that is guaranteed to satisfy complex specifications. To apply these tools, we identify and exploit structural properties particular to traffic networks that allow for efficient computation of a finite-state abstraction. In particular, traffic networks exhibit a componentwise monotonicity property which enables reaching set computations that scale linearly with the dimension of the continuous state space.}, %keywords={Indexes;Roads;Throughput;Trajectory;Vehicle dynamics;Vehicles;Finite state abstraction;linear temporal logic;transportation networks