Reversible Discrete Event Formulation and Optimistic Parallel Execution of Vehicular Traffic Models

Abstract

Vehicular traffic simulations are useful in applications such as emergency planning and traffic management. High speed of traffic simulations translates to speed of response and level of resilience in those applications. Discrete event formulation of traffic flow at the level of individual vehicles affords both the flexibility of simulating complex scenarios of vehicular flow behavior as well as rapid simulation time advances. However, efficient parallel/distributed execution of the models becomes challenging due to synchronization overheads. Here, a parallel traffic simulation approach is presented that is aimed at reducing the time for simulating emergency vehicular traffic scenarios. Our approach resolves the challenges that arise in parallel execution of microscopic, vehicular-level models of traffic. We apply a reverse computation-based optimistic execution approach to address the parallel synchronization problem. This is achieved by formulating a reversible version of a discrete event model of vehicular traffic, and by utilizing this reversible model in an optimistic execution setting. Three unique aspects of this effort are: (1) exploration of optimistic simulation applied to vehicular traffic simulation (2) addressing reverse computation challenges specific to optimistic vehicular traffic simulation (3) achieving absolute (as opposed to self-relative) speedup with a sequential speed close to that of a fast, de facto standard sequential simulator for emergency traffic. The design and development of the parallel simulation system is presented, along with a performance study that demonstrates excellent sequential performance as well as parallel performance. The benefits of optimistic execution are demonstrated, including a speed up of nearly 20 on 32 processors observed on a vehicular network of over 65,000 intersections and over 13 million vehicles.