Vehicular communication based visible light presents an excellent solution to ensure road safety and transportation efficiency in critical environments like tunnels, underground garages, or covered parking lots where traditionally RF solutions cannot provide an efficient communication. In this paper, we propose a new multipath channel model for V2V-VLC in unfavorable situations like in tunnels by using a PSD sensor. The performance of the derived channel model is evaluated using statistical measures based on numerical simulations in terms of channel impulse response, channel DC gain and RMS delay spread to quantify the effects of multipath propagation. Monte Carlo simulation is also used to explore the statistical model obtained for different transmission scenarios. Additionally, we evaluate the influence of various model parameters, such as road width and inter-vehicular distance, on the performance of the V2V channel. The main results are compared with typical Lambertian reflector model to confirm the validity of the proposed model.

Vehicular Visible Light communication (VVLC) presents a new paradigm for providing vehicle connectivity, increasing road safety, and achieving autonomous driving. It can be chosen as an alternative solution to radio frequency-based inter-vehicle communication systems and/or as a complementary solution to ensure redundancy. Nevertheless, there are still significant challenges in incorporating visible light communication systems into vehicular networks. The main purpose of this paper is to provide an outline of the performance metrics of a VVLC system. Furthermore, the study is performed based on a vehicle-to-vehicle dynamic model close to reality, considering the effect of geometrical changes in the LOS path and the variation of the inter-vehicular distance. The analysis of the proposed system is discussed in terms of Signal to noise (SNR), Field of view (FOV), mobility, and average capacity.

In this paper, we explore the use of visible light positioning (VLP) technology in vehicles in intelligent transportation systems (ITS), highlighting its potential for maintaining effective line of sight (LOS) and providing high-accuracy positioning between vehicles. The proposed system (V2V-VLP) is based on a position-sensitive detector (PSD) and exploiting car taillights to determine the position and inter-vehicular distance by angle of arrival (AoA) measurements. The integration of the PSD sensor in vehicles promises exceptional positioning accuracy, opening new prospects for navigation and driving safety. The results revealed that the proposed system enables precise measurement of position and distance between vehicles, including lateral distance. We evaluated the impact of different focal lengths on the system performance, achieving cm-level accuracy for distances up to 35 m, with an optimum focal length of 25 mm, and under low signal-to-noise conditions, which meets the standards required for safe and reliable V2V applications. Several experimental tests were carried out to validate the results of the simulations.