## 2 Literature Review
Windows Sockets were used as the communication middleware to transfer vehicle information and synchronize the simulation time between the client controller and server simulators. Researchers at the University of California, Irvine [27] developed ParamGrid as a scalable and synchronized framework. They distributed the simulation across low-cost personal computers (PCs) connected by local area network (LAN). A large traffic network was divided into a grid of smaller, rectangular sub-networks. Each sub-network was called a tile and ran on a single-process simulator on a single PC. They developed methodologies to transfer vehicles across tiles and synchronize the simulation time globally using CORBA middleware. They found the simulation performance increased approximately linearly with the number of added low-cost processors. [PERSON] et al. [28] proposed Mobile Wireless Vehicular Environment Simulation (MoVES) as a scalable and efficient framework for the parallel and distributed simulation of vehicular ad hoc networks. MoVES was implemented on the ARTIS (Advanced Run Time Infrastructure System) simulation middleware which partially adopted the High Level Architecture (HLA) standard IEEE 1516 and supported conservative time management \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Parallelization Type** & **Parallelization Detail** \\ \hline MITSIM & Task Parallelization & Master controller is used to synchronize the execution of all modules \\  & & Demand simulator estimates O-D flows. Supply \\ DynaMIT & Task Parallelization & simulator represents mesoscopic traffic \\  & & network model \\ DYNASMART & Task Parallelization & Different modules are deployed on a distributed computational platform using the CORBA architecture \\ TRANSIMS & Domain & Each CPU is responsible for a different geographical \\  & Decomposition & area of the simulated region \\ AIMSUN2 & Domain & Network is partitioned into blocks and layers \\  & Decomposition & Network is divided into several regions and run \\ PARAMICS & Domain & Network is distributed into several regions and run \\  & Decomposition & simultaneously with synchronization algorithm \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parallel and distributed computing in traffic simulation. based on time-stepped approach. They developed solutions for communication overhead reduction and computational/communational load balancing. Their vehicular model followed a microscopic approach including car following model. However, lane changing policies were not implemented. Their performance analysis demonstrated that MoVES had better performance in scalability, efficiency, and accuracy. [PERSON] et al. [29] developed a distributed real-time traffic simulation for autonomous vehicle testing in urban environments. In their model, the synchronization of the Automotive Data and Time Triggered Framework instance and the traffic simulation in Virtual Test Drive is done by the connection toolbox to synchronize Electronic Control Unit and Runtime Data Bus/Simulation Control Protocol data exchange. [PERSON] et al. [30] proposed distributed agent-based traffic simulations and [PERSON] and [PERSON] [31] developed a distributed, integrated, and interactive traffic simulations. In their model, all the components are distributed and communicate over the network using TCP/IP or UDP. The Data/Control API, the Time Synchronization API, access control to the database and other services such as logic for procedural modeling and so on are implemented using Microsoft's Web Communication Framework (WCF). [PERSON] et al. [32] developed Mobiliti, a proof-of-concept simulator enabling distributed memory parallelism with an asynchronous execution strategy. Mobiliti was built on top of the Devastator parallel discrete event simulation runtime.