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26 results for “Platooning”
Versailles, Platooning
<p>Scenario description: Automatic fleet rebalancing from one car sharing station to the other. Operator is driving the first car, following the recommendations of Traffic Light Assist service when approaching intersections. Followers are driving automatically.</p> <p>Session description: Platooning between the two car sharing stations with 3 vehicles. Only real traffic lights of intersections 422 and 447 are recorded.</p> <p>Datasets descriptions:</p> <p><strong>AUTOPILOT_Versailles_Platooning_Vehicle</strong>: Data generated from the vehicle sensors</p> <p>Vehicle datasets generated by the vehicle sensors during platooning at Versailles. This includes the data coming from the CAN bus and GPS. It includes following kind of datasets: Vehicle: general data (speed, battery), PositioningSystem: data from GPS, VehicleDynamics: data about dynamic (acceleration...), LateralControl: steering and lane control data</p> <p><strong>AUTOPILOT_Versailles_Platooning_V2X: </strong>V2X messages during platooning sessions</p> <p>This dataset refers to the V2V messages exchanged between the vehicles during the platooning at Versailles. TCPwlan logs contain mainly the identification of sender and receiver and the payload extracted from TCP messages captured on the CAN bus.</p> <p><strong>AUTOPILOT_Versailles_Platooning_IoT: </strong>Data extracted from IoT oneM2M platform</p> <p>This dataset refers to messages exchanged by platooning application and services, Traffic Light Assist service, traffic light controllers across oneM2M platform.</p>
Brainport, Platooning, platoon formation improvement
<p><strong>Scenario description</strong>:</p> <p>Platoon formation with live traffic light data included in planner.<br> - Enabled live traffic light data included in planner<br> - Not using the Android app<br> - Starting at default locations</p> <p><strong>Session description</strong>:</p> <p>Platoon formation improvement by traffic light data.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, platoon with live traffic light
<p><strong>Scenario description</strong>:</p> <p>Platoon formation and platooning, from Helmond to Eindhoven and back to the Automotive Campus.<br> - Starting in urban area with speed limits of 15 and 30 km/h.<br> - Driving East on the Europaweg with speed limits of 50 and 70 km/h. This includes 3 crossings with traffic lights.<br> - Driving on the the N270, along the Automotive Campus. One crossing with traffic lights, just before the A270.<br> - Driving on the A270 (speed limit 100 km/h). Interrupted by one traffic light.<br> - U-turn at the fly-over or at the end of the A270, to return the same way to the Automotive Campus.</p> <p><strong>Session description</strong>:</p> <p>Platoon formation and platooning, with live traffic light data included in planner.<br> - Live traffic light data available for planner<br> - Driver uses the Android app<br> - Starting at default locations<br> - Platooning (CACC and lane keeping) on the A270 when possible.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, formation improvement by traffic light data
<p><strong>Scenario description</strong>:</p> <p>Platoon formation with live traffic light data included in planner.<br> - Enabled live traffic light data included in planner<br> - Not using the Android app<br> - Starting at default locations<br> - This test was filmed, including the GUI.</p> <p><strong>Session description</strong>:</p> <p>Platoon formation improvement by traffic light data.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, platoon formation feasibility
<p><strong>Scenario description</strong>:</p> <p>Platoon formation only.<br> - Disabled live traffic light data included in planner<br> - Not using the Android app<br> - Starting at default locations</p> <p><strong>Session description</strong>:</p> <p>Platoon formation feasibility</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, formation and platooning without traffic
<p><strong>Scenario description</strong>:</p> <p>Platoon formation and platooning, from Helmond to Eindhoven and back to the Automotive Campus.<br> - Starting in urban area with speed limits of 15 and 30 km/h.<br> - Driving East on the Europaweg with speed limits of 50 and 70 km/h. This includes 3 crossings with traffic lights.<br> - Driving on the the N270, along the Automotive Campus. One crossing with traffic lights, just before the A270.<br> - Driving on the A270 (speed limit 100 km/h). Interrupted by one traffic light.<br> - U-turn at the fly-over or at the end of the A270, to return the same way to the Automotive Campus.</p> <p><strong>Session description</strong>:</p> <p>Platoon formation and platooning, without live traffic light data included in planner.<br> - No live traffic light data available for planner<br> - Driver uses the Android app<br> - Starting at default locations<br> - Platooning (CACC and lane keeping) on the A270 when possible.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, formation and platooning with speed advice
<p><strong>Scenario description</strong>:</p> <p>Platoon formation and platooning, from Helmond to Eindhoven and back to the Automotive Campus.<br> - Starting in urban area with speed limits of 15 and 30 km/h.<br> - Driving East on the Europaweg with speed limits of 50 and 70 km/h. This includes 3 crossings with traffic lights.<br> - Driving on the the N270, along the Automotive Campus. One crossing with traffic lights, just before the A270.<br> - Driving on the A270 (speed limit 100 km/h). Interrupted by one traffic light.<br> - U-turn at the fly-over or at the end of the A270, to return the same way to the Automotive Campus.</p> <p><strong>Session description</strong>:</p> <p>Platoon formation and platooning, without live traffic light data included in planner, but with automatic speed advice.<br> - No live traffic light data available for planner<br> - Driver uses the Android app if Technolution gives a flexible route<br> - Starting at default locations<br> - Platooning (CACC and lane keeping) on the A270 when possible.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, Baseline
<p><strong>Scenario description</strong>:</p> <p>Driving without speed advice or any services to measure base-line.</p> <p><strong>Session description</strong>:</p> <p>Baseline</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, baseline platoon formation without IoT
<p><strong>Scenario description</strong>:</p> <p>Platoon formation and platooning, from Helmond to Eindhoven and back to the Automotive Campus.<br> - Starting in urban area with speed limits of 15 and 30 km/h.<br> - Driving East on the Europaweg with speed limits of 50 and 70 km/h. This includes 3 crossings with traffic lights.<br> - Driving on the the N270, along the Automotive Campus. One crossing with traffic lights, just before the A270.<br> - Driving on the A270 (speed limit 100 km/h). Interrupted by one traffic light.<br> - U-turn at the fly-over or at the end of the A270, to return the same way to the Automotive Campus.</p> <p><strong>Session description</strong>:</p> <p>Baseline of platoon formation and platooning, without any IoT, so no speed advices.<br> - No live traffic light data available for planner<br> - Starting at default locations<br> - Meeting at the location of vehicle2 on the Automotive Campus<br> - Platooning (CACC and lane keeping) on the A270 when possible.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, baseline, rush hour
<p><strong>Scenario description</strong>:</p> <p>Driving without speed advice or any services to measure base-line.</p> <p><strong>Session description</strong>:</p> <p>Baseline (rush hour)</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, formation variation testing
<p><strong>Scenario description</strong>:</p> <p>Platoon formation, starting from different locations, with live traffic light data included in planner.<br> - Enabled live traffic light data included in planner<br> - Not using the Android app<br> - Starting at different locations</p> <p><strong>Session description</strong>:</p> <p>Platoon formation variation testing</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, Platoon formation improvement
<p><strong>Scenario description</strong>:</p> <p>Platoon formation with ONLY AVERAGE traffic light data included in planner.<br> - Disabled live traffic light data included in planner<br> - Planner advices are based on moving average of a certain amount of past traffic light cycles.<br> - Not using the Android app<br> - Starting at default locations</p> <p><strong>Session description</strong>:</p> <p>Platoon formation improvement by traffic light data.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, formation, platooning, speed advice
<p><strong>Scenario description</strong>:</p> <p>Platoon formation and platooning, from Helmond to Eindhoven and back to the Automotive Campus.<br> - Starting in urban area with speed limits of 15 and 30 km/h.<br> - Driving East on the Europaweg with speed limits of 50 and 70 km/h. This includes 3 crossings with traffic lights.<br> - Driving on the the N270, along the Automotive Campus. One crossing with traffic lights, just before the A270.<br> - Driving on the A270 (speed limit 100 km/h). Interrupted by one traffic light.<br> - U-turn at the fly-over or at the end of the A270, to return the same way to the Automotive Campus.</p> <p><strong>Session description</strong>:</p> <p>Platoon formation and platooning, without live traffic light data included in planner, but with automatic speed advice.<br> - No live traffic light data available for planner<br> - Driver uses the Android app if Technolution gives a flexible route<br> - Automatic speed advice also includes reaction to road-side camera-service objects (LDM closed loop)<br> - Automatic speed advice is turned on, so does actuate the vehicle<br> - Vehicle1 is starting at another location in Helmond (#2), vehicle2 at default location (Automotive Campus)<br> - Platooning (CACC and lane keeping) on the A270 when possible.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, platoon formation variation
<p><strong>Scenario description</strong>:</p> <p>Platoon formation with live traffic light data included in planner.<br> - Enabled live traffic light data included in planner<br> - Not using the Android app<br> - Starting at default locations<br> - Used for pieces of the film (to be made)</p> <p><strong>Session description</strong>:</p> <p>Platoon formation variation testing</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, formation and platooning from default locations
<p><strong>Scenario description</strong>:</p> <p>Platoon formation and platooning, from Helmond to Eindhoven and back to the Automotive Campus.<br> - Starting in urban area with speed limits of 15 and 30 km/h.<br> - Driving East on the Europaweg with speed limits of 50 and 70 km/h. This includes 3 crossings with traffic lights.<br> - Driving on the the N270, along the Automotive Campus. One crossing with traffic lights, just before the A270.<br> - Driving on the A270 (speed limit 100 km/h). Interrupted by one traffic light.<br> - U-turn at the fly-over or at the end of the A270, to return the same way to the Automotive Campus.</p> <p><strong>Session description</strong>:</p> <p>Platoon formation and platooning, without live traffic light data included in planner, but with automatic speed advice.<br> - No live traffic light data available for planner<br> - Driver uses the Android app if Technolution gives a flexible route<br> - Starting at default locations<br> - Platooning (CACC and lane keeping) on the A270 when possible.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Brainport, Platooning, formation and platooning, with speed advice
<p><strong>Scenario description</strong>:</p> <p>Platoon formation and platooning, from Helmond to Eindhoven and back to the Automotive Campus.<br> - Starting in urban area with speed limits of 15 and 30 km/h.<br> - Driving East on the Europaweg with speed limits of 50 and 70 km/h. This includes 3 crossings with traffic lights.<br> - Driving on the the N270, along the Automotive Campus. One crossing with traffic lights, just before the A270.<br> - Driving on the A270 (speed limit 100 km/h). Interrupted by one traffic light.<br> - U-turn at the fly-over or at the end of the A270, to return the same way to the Automotive Campus.</p> <p><strong>Session description</strong>:</p> <p>Platoon formation and platooning, without live traffic light data included in planner, but with automatic speed advice.<br> - No live traffic light data available for planner<br> - Driver uses the Android app if Technolution gives a flexible route<br> - Vehicle1 is starting at another location in Helmond (#2), vehicle2 at default location (Automotive Campus)<br> - Platooning (CACC and lane keeping) on the A270 when possible.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_Platooning_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_Platooning_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonFormation</strong>: Data sent from PlatoonService to vehicle</p> <p>This dataset contains information about the route and speed for a specific vehicle for forming a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningAction</strong>: Data logged by vehicle</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatooningEvent</strong>: Data logged by vehicle</p> <p>This dataset contains information about the identifiers used for each specific platooning event</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PlatoonStatus</strong>: Data sent by vehicle to PlatoonService</p> <p>This dataset contains information about the current status of the platooning</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PositioningSystemResample</strong>: Data from GPS on the vehicle</p> <p>This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_Platooning_PSInfo</strong>: Data sent by PlatoonService to the vehicle</p> <p>This dataset contains speed and route information for the vehicle to create a platoon</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Target</strong>: Data from sensors on the vehicle</p> <p>Target detection in the vicinity of the host vehicle, by a vehicle sensor or virtual sensor</p> <p><strong>AUTOPILOT_BrainPort_Platooning_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p> <p><strong>AUTOPILOT_BrainPort_Platooning_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
F1/10 Platooning with ETSI ITS-G5 communication using ROS 2
<p>This dataset is recorded from a platooning scenario using F1/10 vehicles on a scaled-down version of the Aldenhoven testing center. It uses a scaled-down version of the ETSI ITS-G5 standard for the communication via CAM messages. Furthermore, it uses a CACC controller for the control of the vehicles using the information from a motion-capture system and the communicated data of each vehicle. The dataset includes two configurations of the same scenario, with a target velocity of 0.8m/s and 3.0m/s, respectively.</p> <p>The experiments are based on the software of the <a href="https://github.com/HarunTeper/AuNa">AuNa</a> framework by <a href="https://arxiv.org/abs/2207.05544">Teper et al.</a>, while the experiments were conducted during the case studies described by <a href="https://ieeexplore.ieee.org/document/10464605">Krieger et al.</a> and <a href="https://ieeexplore.ieee.org/document/10553459">Priyanta et al.</a>. The dataset can be analyzed using the <a href="https://github.com/tudo-aqua/stars">STARS</a> framework.</p>
CN, Vehicles Platooning, Cloud-assisted platooning
<p>Use Case Category: <strong>Vehicles Platooning</strong><br> User Story: <strong>Cloud-assisted platooning</strong><br> Location: Chinese (CN) trial site</p> <p>According to 3GPP TS 22.186 R16, Vehicles Platooning “enables the vehicles to dynamically form a group travelling together. All the vehicles in the platoon receive periodic data from the leading vehicle, in order to carry on platoon operations. This information allows the distance between vehicles to become extremely small, i.e., the gap distance translated to time can be very low (sub second). Platooning applications may allow the vehicles following to be autonomously driven”.</p> <p>User Story: <strong>Cloud-assisted platooning</strong></p> <p>The autonomous driving vehicle fleet communicates with each other through LTE-V at the start. Among them, the leading vehicle includes the platoon control unit (PCU), which coordinates the vehicles in the fleet to ensure a certain safe distance and to drive in a platoon. The leading vehicle communicates with the control centre deployed in a cloud server through V2N to obtain the test scheme and the global path planning. Then it provides the basic planning for the rear vehicle through V2V communication (including chasing, continuous running, acceleration, deceleration, obstacle avoidance, overall acceleration, and deceleration, etc.). The following vehicle also has a certain perception and planning decision-making ability. Besides, LTE-V communication can be replaced by DSRC technology, and comparison between these two methods will be implemented.</p>
DE, Vehicles Platooning, eRSU-assisted platooning
<p>Use Case Category: <strong>Vehicles Platooning</strong><br> User Story: <strong>eRSU-assisted platooning</strong><br> Location: German (DE) trial site</p> <p>According to 3GPP TS 22.186 R16, Vehicles Platooning “enables the vehicles to dynamically form a group travelling together. All the vehicles in the platoon receive periodic data from the leading vehicle, in order to carry on platoon operations. This information allows the distance between vehicles to become extremely small, i.e., the gap distance translated to time can be very low (sub second). Platooning applications may allow the vehicles following to be autonomously driven”.</p> <p>User Story: eRSU-assisted platooning</p> <p>In this use case, a platoon of 3 AVs is operating along a road. The platoon approaches a truck. At 500m to a junction, the truck signals its intention to take the right turn and slows down.</p> <p>A local EDM instance deployed on an eRSU located at the junction, detects the truck’s changing velocity and trajectory through learned pattern recognition from local sensor data. It updates the global map and notifies the centralized traffic management & planning applications through eRSU’s upstream interfaces.</p> <p>The platoon leader detects a potential collision as it approaches the truck and request the EDM from the eRSU. The route planning service in the eRSU detects a possible overtaking manoeuvre due to low traffic ahead and possibly adapted green light phase for extended free flow based on information from traffic management system.</p> <p>Based on the information provided by the eRSU and its services, the platoon leader initiates an overtaking manoeuvre by communicating context data (location, speed, LDM) to the eRSU. Using the EDM, the route planning service in the eRSU formulates the overtaking manoeuvre and communicates the overtaking plan to the platoon leader.</p> <p>During the overtaking manoeuvre, the platoon enters the coverage of an eRSU of another provider. This results in eRSU handover with upstream gateway relocation from current MNO’s eNB/gNB to new MNO’s. In effect, the ITS instances and context on source eRSU must be handed over to the new eRSU. At mobile network level, this handover is carried out with handover protocol between the MNOs’ core networks. At application level, resource and service allocation are orchestrated by the centralized ITS service entities, which are made aware of mobile network and MEC provisioning.</p>
GR-TR, Vehicles Platooning, See What I See
<p>Use Case Category: <strong>Vehicles Platooning</strong><br> User Story: <strong>See What I See</strong><br> Location: Greece - Turkey (GR-TR) cross-border corridor</p> <p>According to 3GPP TS 22.186 R16, Vehicles Platooning “enables the vehicles to dynamically form a group travelling together. All the vehicles in the platoon receive periodic data from the leading vehicle, in order to carry on platoon operations. This information allows the distance between vehicles to become extremely small, i.e., the gap distance translated to time can be very low (sub second). Platooning applications may allow the vehicles following to be autonomously driven”.</p> <p>User Story: <strong>Platooning with “see what I see” functionality in cross-border settings</strong></p> <p>Observing that there is at least another vehicle on a road, which does not involve intersections and merging with other lanes for a certain time, the two or more vehicles on the move will decide to form a platoon. In the platoon, while one of the vehicles take on the role of the leader, which may or may not have an active driver depending on the SAE level of the vehicle itself, the rest of the vehicles may be controlled automatically by the movements of the leading vehicle.</p> <p>Once the platoon is formed and the “see-what-I-see” application is informed about the presence of the platoon as well as its members with distinct roles to identify the leader and the follower vehicles, a specific ID is assigned to the platoon by the application. Then, the platoon leader will start transmitting a compressed (with H.265/HEVC codec standard) 4K video stream captured by a camera viewing the road in the front of the vehicle, along with the platoon ID, first to the base station, then to the vEPC, which is to transfer the streaming data to the “see-what-I-see” application server. Matching the video with the recipient vehicles that are the follower trucks in the platoon by using the platoon ID, the application server begins sending the video stream to these through the vEPCs and base stations serving them.</p> <p>All platoon members will be equipped with on board units (OBU) that have the C-V2X communication capability and a connection to the in-cabin displays of the vehicle (such as a dedicated tablet). Additionally, the platoon leader will share road information collected from its sensors such as short and mid-range radars and cameras as well as internal data about its manoeuvres (i.e. emergency brake, speed up-down etc.) over the PC5 interface with the follower vehicles.</p> <p>When the platoon arrives to the customs site between Turkey and Greece borders, the platoon is dissolved for further controls at the borders. At this stage, the objective is to allow the truck drivers handle required documentation while the trucks move autonomously at the customs site to visit each of the checkpoints as dictated by the customs agency. For the autonomous crossing of the trucks between the borders, the customs site will be equipped with several sensors and road side units (RSUs) in addition to the 5G network infrastructure. All sensory information from the vehicles and the surrounding will be gathered at the network edge to be processed by an application, which will determine the safest paths for each of the vehicles at the customs site, dynamically shaping their whole trajectory.</p> <p>After the “truck routing in customs site” is over with no obstacles detected for passage through the border and the drivers have completed their paperwork, they will return to their vehicles. Upon exiting the customs site, the platooning operation and thus the “see-what-I-see” functionality will be initiated again. The final destination of the platoon will be Greece.</p> <p>While the platoon goes from Turkey to Greece, it is anticipated that at some point, which depends specifically on the radio signal propagation characteristics of the 5G networks, the vehicles in the platoon will roam from the Turkish (Turkcell) operator to the Greek (Cosmote) operator, where an uninterrupted video stream will flow from the leader truck to the follower trucks throughout the roaming procedure.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.