CN+: Vehicular Dataset at Traffic Light Regulated Intersection in Bremen, Germany

Vehicular ad-Hoc Networks (VANETs) were created to reduce traffic accidents and enhance the safety of both passengers and other road users. In VANETs, vehicles communicate with nearby vehicles using V2V (vehicle-to-vehicle) communication links to improve awareness of their surroundings. Since their inception, considerable research has focused on developing cutting-edge algorithms to boost safety. However, testing these algorithms in real-world conditions is difficult due to high costs and various logistical challenges. Therefore, simulation-based testing is frequently used for VANET applications. Utilizing real datasets in simulations can significantly improve accuracy and yield realistic results. In this study, we introduce a dataset called 'CN+', which comprises data from over 25,000 vehicles collected over 32 hours at a signalized intersection in Bremen, Germany. The dataset is presented in two different formats: 1-CSV format and 2-SUMO converted format.