Video Based Simulation of Daytime and Nighttime Rain Affecting Driver Visibility 2021-01-0854

This paper presents a methodology for generating video realistic computer simulated rain, and the effect rain has on driver visibility. Rain was considered under three different rain rates, light, moderate and heavy, and in nighttime and daytime conditions. The techniques and methodologies presented in this publication rely on techniques of video tracking and projection mapping that have been previous published. Neale et al. [2004, 2016], showed how processes of video tracking can convert two-dimensional image data from video images into three-dimensional scaled computer-generated environments. Further, Neale et al. [2013,2016] demonstrated that video projection mapping, when combined with video tracking, enables the production of video realistic simulated environments, where videographic and photographic baseline footage is combined with three-dimensional computer geometry. This paper augments this existing technology through techniques and methodologies that incorporate the adverse weather condition of rain into the simulated environment. A method for simulating the effect of rain on drivers’ visibility is developed by analyzing and modeling actual video footage obtained in both dry and rain conditions, during the day and at night. Baseline, raw video footage that does not contain adverse weather is video tracked, and through projection mapping and the use of modeling that represent rain, this baseline footage is rendered to properly display the effect rain has on driver visibility. The resulting simulation is then compared to calibrated raw video that shows the same area of the roadway but recorded when the adverse weather condition was actually present. In other words, the computer-simulated effect of rain on drivers’ visibility is compared to calibrated footage of video driving on the same roadway and under actual rainy weather conditions. The paper demonstrates that through these methodologies, video realistic simulated rain can be created that accurately represent the driver’s visibility in adverse weather conditions. When comparing the simulated rain environment to the original video footage that captured baseline rainy condition, the results show that the view from the driver’s perspective are rendered the same.