| Abstract |
As self-driving vehicles gain popularity, our roads must also adapt to keep pace with this technology. Smart roads will establish seamless communication with vehicles through machine-to-machine (M2M) interaction, enabling more efficient and safer transportation. To achieve this we propose a smart road reflector device that aims to acquire real-time data about weather conditions (e.g., temperature, humidity), monitor traffic locations (ensuring lane and signal adherence), and provide a high-precision lane positioning system. A network of intelligent reflectors will be established to achieve this, with a central hub node connecting multiple smart reflectors. The master node, utilizing Raspberry Pi 3 B+, will lead the network, while the individual smart reflectors, equipped with ESP32, sensors, and GPS receivers, will monitor ongoing traffic and lane changes. These data will be transmitted to the master reflector for further processing. To handle large numbers of reflectors, the master node will deploy a machine learning model (TinyML) to predict road conditions and accurately locate vehicles. This intelligent system will assist vehicles in maintaining proper lanes and provide valuable information about road weather conditions. Our proposed smart reflector will enhance and support cars in adhering to lanes and communicate essential road weather conditions, ensuring smoother, safer transportation in the age of self-driving technology. |
