Advanced Multimodal Sensor Dataset from an Autonomous Vehicle Platform

This dataset collects data from an autonomous vehicle in a controlled scenario. The key novelty is the presence of advanced sensor such as Event Camera, Road surface laser scanner. AUTOMATED VEHICLE DATA COLLECTOR The vehicle used for data collection is an autonomous car prototype retrofitted with the following sensor suite: Inertial Navigation System: OxTS GNSS/INS solution providing global position, IMU data, and odometry. LiDAR: 2x Ouster 360° LiDAR. LiDAR: 1x Innovusion Falkon 120° LiDAR. Cameras: 3x Lucid Vision cameras (Front Center, Front Left, Front Right recorded). Radars: 4x Continental ARS430 radars providing objects list, near and far range detections. Vehicle Sensors: Wheel speed sensors and internal vehicle feedback. Event Camera: 1x Metavision EVK4 – HD EvC. and controllable actuators: Steering & Braking: Wire-controlled actuators for lateral and longitudinal control. The system is designed to detect the position, velocity, and type of other road users. For this specific task, the perception stack utilizes neural networks for image segmentation to build a local map of the lanes. An algorithm processes this data to identify vehicles specifically stopped in the emergency lane. DATASET CONTENT The dataset includes a ~45-second recording in a controlled environment. It contains: ROS2 Bag (.mcap): Contains all raw sensor data, system status, perception outputs. Laserscanner data (.xrc): Contains all frame acquired by the scanner referred to the road surface present in the ROS2 Bag. Example frame such as images and screen recording for dataset rapid evaluation. Key ROS2 Topics included (relevant list): Sensors (Raw Data): /ouster_sensor_center/points (LiDAR Pointcloud) /lucid_vision/*/image_rect/compressed (Camera images) /ces_ars430di/sensor_*/objects_list (Radar object list detections) /oxts/nav_sat_fix & /oxts/imu (GNSS and Inertial data) /event_camera/events (List of events recorded by EvC) SCENARIOS Controlled enviroment: The bag are recorded in private road close to traffic. This is done to include all the data without anonimization. Location: Segrate, road under construction. DATASET ACCESS To request access to the dataset please contact: Alberto Lucchini, Politecnico di Milano, [e-mail] Panzani, Politecnico di Milano, [e-mail]