Evaluation System of Blind Spot Warning Algorithm Based on Vehicle to Everything - Yanzhao Yang; Jian Wang; Xinyu Yang; Tingyu Zhang; Xinyu Guo (IEEE Access)
The vehicle anti-collision system stands as a pivotal innovation, markedly reducing the frequency of vehicular accidents by issuing timely alerts to drivers about imminent collision risks. This preemptive safety feature is now a standard component within the safety packages provided by many automotive manufacturers. While current anti-collision technologies, predominantly advanced driver assistance systems that synthesize diverse sensor inputs, are sophisticated, their performance can be impeded by the operational constraints of the sensors themselves. This limits their capacity to ensure traffic safety comprehensively and efficiently. To overcome these constraints, there has been a significant shift towards anti-collision systems employing short-range wireless communication technologies. This paper introduces the design and development of a blind spot warning system based on cellular vehicle-to-everything technology. It enables the fluid communication of vehicle and road segment data among the host vehicle, remote vehicles, and roadside units through cellular vehicle-to-everything protocols. The system evaluates spatial relationships of surrounding RVs to the HV and the associated collision risks by analyzing the consolidated vehicle and environmental data, subsequently delivering early warnings to the driver. Utilizing simulation software named Virtual Test Drive, this research constructs detailed collision scenarios and performs exhaustive Hardware-in-the-Loop testing. A comparative analysis of various experimental data sets confirms the algorithm’s proficiency in delivering precise and prompt blind spot collision alerts to the HV, validating its effectiveness in bolstering vehicular safety.