Development of a MEMS-Based IoV System for Augmenting Road Traffic Survey

Based on in situ measurements, infrastructure-to-vehicle communication, and cloud computing technologies, the "ODOS2020" project introduces an Internet-of-vehicles (IoV) solution that enables the transmission of personalized, safety-related information to a vehicle driver in real-time. In the present work, the architecture and algorithmic approach of the roadside system is presented. The system is based on low-cost, low-energy magnetic microelectromechanical systems (MEMS) sensors that are mounted in a twin-strip architecture, and an on-the-road unit (ORU). Our focus is on the evaluation of the system's efficiency for vehicle speed-direction estimation in real-time. Evaluation tests are organized into two categories. In the first, sensors are placed on the side of the road, while in the second the sensors are laid across the lane. Parametric tests in a fully controlled environment, as well as tests in a real environment, were performed. It is shown that the solution could provide efficient results (1% error rate), while the system's accuracy depends on initial system calibration.