Empirical Evaluation of Connected and Automated Driving Features in Production Vehicles

In recent years, production vehicles have increasingly integrated connected and automated driving features (CADFs) to enhance the driving experience and road safety. Despite their growing prevalence, the real-world performance of these features remains largely unverified outside of manufacturer-led evaluations, which are typically conducted in controlled environments. This article addresses that gap by empirically testing CADFs in six production vehicles from Toyota, Hyundai, Ford, Audi, Honda, and Tesla. The evaluation covers key features, including adaptive cruise control, collision avoidance assist, lane marking detection, static message sign detection, traffic light awareness, and full self-driving, under diverse real-world conditions, such as varying lighting and lane visibility. The results reveal substantial variability in performance across vehicles and scenarios, emphasizing the influence of environmental and operational factors. Based on these findings, the article provides recommendations for automakers and public stakeholders to enhance CADF reliability, supporting future improvements in both vehicle technology and infrastructure.