Connected Vehicle (CV) is a motorized vehicle that can communicate with its interior and exterior surroundings. Connected Vehicle focuses on localized vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) to support safety, mobility and environmental applications. In this work, a simulation framework is presented. The framework quantifies Connected Vehicle performance in a forward collision warning situation. The simulation framework evaluates the performance using a vehicular traffic simulator with data from an intersection in Toronto, ON Canada. Various communication methodologies are evaluated at different Connected Vehicle market penetration rates. While DSRC is an interference limited communication methodology and visible light communications is a line-of-sight communication, the combination of both is evaluated to quantify the vehicular network safety performance in terms of time to collision. The performance of DSRC in a vehicular network is quantified in an interference dominant environment and the VLC performance in the vehicular network is evaluated at different weather conditions. In a specific vehicular traffic situation namely for- ward collision warning, this research quantified the VLC performance improvement in vehicular network safety to be 11% in addition to DSRC.This work concludes with the simulation and prototyping of camera communications for vehicular applications. Specifically this thesis presents multiple input / multiple output camera communications link utilizing a luminary array as a transmitter and two orthogonal low cost rolling shutter cameras as a receiver with the purpose of increasing the achievable data rate with one camera. This work has demonstrated that there is at most a doubling in the data rate using two cameras over a single one. This data rate increase is achievable using a specific camera setup namely orthogonal cameras.

Master of Applied Science (MASc)

Thesis