Livorno, Urban driving, autonomous speed adaptation approaching intersection

Scenario description: Test session for AD+connected car and connected cars approaching an intersection regulated by a "smart" traffic light with a stereocamera able to detect jaywalking. Session description: A "smart" traffic light (with stereocamera) sends SPaT and MAP messages describing the topology and the actual status of the traffic light. If a jaywalking occurrence is detected (pedestrian crossing with the red light) a DENM message is sent to warn vehicles of the presence of the pedestrian to other connected vehicles. The the hazard warning is also sent to the oneM2M platform on the cloud. An AD vehicle consumes the information and autonomously adapts its speed in order to cross the intersection without violating the traffic light phases, or even stop to avoid collision with pedestrian. The influence of other vehicles moving in front is considered too. Goal is to record data for the technical evaluation. Datasets descriptions: AUTOPILOT_Livorno_UrbanDriving_Vehicle_all: Data generated from the vehicle sensors This dataset refers to the vehicle datasets generated from the vehicle sensors during Urban Driving in Livorno. This includes the data coming from the CAN bus and GPS. It includes following kind of dataset: Vehicle: general data (speed, battery); PositioningSystem: data from GPS; VehicleDynamics: data about dynamic (acceleration...); LateralControl: steering and lane control data AUTOPILOT_Livorno_UrbanDriving_V2X_all: V2V messages during platooning sessions This dataset refers to the V2V messages exchanged between ITS stations (vehicles and RSUs) during the Urban Drining in Livorno. AUTOPILOT_Livorno_UrbanDriving_IoT_all: Data extracted from IoT oneM2M platform This dataset refers to messages exchanged by Urban Driving devices, applications and services across the oneM2M platform