RoboBus: A Diverse and Cross-Border Public Transport Dataset

Academic datasets are an important source of information to validate and benchmark novel research concepts. In this paper we present RoboBus, a dataset recorded with a commercial bus on a cross-border public transport route between Luxembourg and France. The dataset contains approximately 8 hours of driving data divided into 15 trips that have been recorded over 4 days. It includes about 1.7 million anonymized images captured by two road-facing cameras, GNSS traces, data from a 9-axis IMU, and information directly retrieved from the CAN interface of the vehicle including speed, steering angle and position of the accelerator/brake pedals. We use an end-to-end autonomous driving approach that relies on imitation learning as use case example for the dataset.