Advancing Autonomous Vehicle ITS with V2X and V2I Periodic Calibration

With the rapid advancement of autonomous driving technology, enhancing the intelligence of individual vehicles and Vehicle-to-Everything (V2X) networking is crucial for improving traffic efficiency and safety. Intelligent Transportation Systems (ITS) face challenges in evolving traditional traffic models, transitioning the focus from human reaction times to vehicle communication and system delays, as exemplified by scenarios like intersection startup delays. This paper presents a comprehensive validation of simultaneous control in Vehicle-to-Infrastructure (V2I) communication. It provides problem mathematical modeling, validation, and quantitative analysis specifically for connected autonomous vehicle lanes at 100% penetration. The real experiment showed that even with identical scenarios, hardware, and communication delays, startup times still varied due to complex internal and external factors affecting command execution. These factors cause cumulative errors over time, diminishing command execution precision despite advanced control algorithms and sensor calibrations. The investigation underscores the imperative for dynamic modifications and systematic recalibrations in control systems of autonomous vehicles, facilitated by fixed infrastructure, to sustain long-term accuracy and effectively navigate real-world complexities.