Rerouting light pathways and enhancing signal-to-noise ratio to sustain and optimize vehicle-to-vehicle visible light communication

Visible light communication (VLC) between vehicles is gaining attention as a complementary technology to radio frequency (RF) based communication methods due to its broad, license-free spectrum and immunity to interference. However, vehicle-to-vehicle (V2V) VLC can face interruptions at intersections due to the limited field of view (FOV) of the receiver. To address this challenge, this thesis presents a novel empirical approach to enhance V2V VLC along curvy roads through adjusting the lateral position of self-angle-adjustable mirror-reflective road signs (SAAMRS) and using wide-angle complementary photodiodes (CPDs) circuitry for direction sensing. A real-time image processing-based vehicle detection model is developed to adjust the SAAMRS's angle to effectively reflect the transmitted light from the transmitter vehicle (TV) towards the receiver vehicle (RV). In addition, a novel method is introduced to enhance the performance of V2V VLC by employing different transmitter (Tx) light-emitting diode (LED) array arrangements with different LED orientations. Improving the signal-to-noise ratio (SNR) is crucial for V2V VLC systems to provide long communication ranges. A V2V VLC system using on–off keying (OOK) is modeled to simulate the SNR and bit error rate (BER) for 6 different Tx configurations: single-LED Txs, as well as 3 x 3 square-, single hexagonal-, octagonal-, 5 x 5 square-, and honeycomb hexagonal-shaped LED arrays. My results show that the honeycomb hexagonal Tx design provides a 19\% improvement in system performance with a spacing of 1 cm, and maintains a 16\% improvement when the array size is reduced by a factor of 100, making it smaller than the smallest industrial headlight modules.