## 1 Introduction  
Transportation impacts every aspect of daily life. For many decades, efforts to improve transportation have been made to ensure quality of life and higher standards of living. However, use of real-time traffic data into our surface transportation system has not been fully accomplished. Recent advancements in sensor, mobile computing, and wireless communication technologies is creating new opportunities to effectively exploit real-time traffic data. Onboard vehicles collect, process, simulate traffic states in a distributed fashion and a local transportation management center coordinates the overall simulation with an optimistic execution technique. Such a distributed approach can provide more up-to-date and robust estimates with decreased communication bandwidth requirements and increased computing capacity [1]. As roadside and in-vehicle sensors are deployed under the Connected Vehicle and autonomous vehicle environments, an increasing variety of traffic data is becoming available in real-time. This real-time traffic data can be shared through wireless communication and used for other purposes, which creates an opportunity for mobile computing and online traffic simulations [2, 3]. However, online traffic simulations require faster than real-time running speed with high simulation resolution, since the purpose of the simulations is to provide immediate future traffic forecast based on real-time traffic data. Simulating at high resolution is often too computationally intensive to process a large-scale network on a single processor in real-time. To mitigate this limitation an online ad hoc distributed simulation with optimistic execution is proposed in this paper. The goal of this paper is to develop an online ad hoc distributed traffic simulation system based on optimistic execution. It is envisioned that in the proposed distributed traffic simulation framework, each in-vehicle simulation models a small portion of the overall network and provides detailed traffic state information. Traffic simulation and data processing are performed in a distributed fashion by multiple vehicles. Each inv-vehicle simulation is designed to run in real-time and update its estimates when it is necessary. A communication middleware is used for the distributed simulation to perform on multiple platforms. A communication middleware developed based on object-oriented client/server technology as a parallel effort is integrated with traffic simulation. This integration manages the distributed network to synchronize the predictions among logical processes. Space-Time Memory management scheme is implemented into a transportation simulation approach. A local central server receives the traffic states from multiple inv-vehicle simulations. Traffic estimates are not guaranteed to be received in time stamp order, since in-vehicles simulations run concurrently. Also, a traffic state can be projected by multiple in-vehicle simulations. A mechanism is needed to coordinate the transmitted data, combine values into a composite value, and save in Space-Time Memory. To handle the data received from all participating vehicles, an optimistic (rollback-based) synchronization protocol is developed. Optimistic execution inspired by Time Warp can mitigate the synchronization problem allowing each logical process to execute asynchronously [4]. This approach provides increased computing capacity with a time-synchronized approach. This paper will review the previous research regarding vehicular ad hoc network and parallel and distributed simulation technologies associated with vehicular ad hoc network. To run a large simulation with fast speed, parallel and distributed simulation has been used in transportation area. Generally, parallel and distributed simulations are differentiated by the geographical distribution, the composition of the processors used, and the network to interconnect the processors. Also, two popular approaches for the synchronization were discussed; (1) conservative time synchronization and (2) optimistic time synchronization.