Large-scale simulations and performance evaluation of connected cars - A V2V communication perspective

Abstract

Performance evaluation is integral to the vast majority of research on Vehicle-to-Vehicle (V2V) technology enabled connected cars. To validate ideas and concepts, researchers have been continuously striving towards the higher accuracy of simulation-based performance evaluation. However, many state-of-the-art network simulators lack comprehensive physical (PHY) layer models. More often, simplified representations of vehicular channel characteristics are used to achieve a trade-off between accuracy and performance. Vehicular channel modeling is a highly complex task because of its unique properties, for example, higher carrier frequency, rapid fluctuations in vehicular channels due to moving scatterers, and propagation in horizontal plane instead of a vertical plane with diffraction and reflection. Efficiently incorporating vehicular channel details into a single network simulator is infeasible; instead, a chain of simulation tools are used together. In this paper, we proposed a two-stage simulation framework which combines several layers of simulation tools into two distinct stages. During the first stage, a Geometry-based vehicular propagation model is used to characterize received signal strength among transmitter-receiver pairs. For this purpose, metropolitan area-wide 2.5D building geometry data and vehicular mobility traces are employed to represent the real-world environment. Subsequently, the output from the first stage is collected and fed as an input to the network simulator. Through extensive simulation-based studies, we analyze the difference between the proposed framework and standard propagation models implemented in the network simulator and their impact on the network-level performance metrics such as packet loss rate (PLR), throughput, latency, and jitter.