Brainport, Urban driving, car rebalancing, VRU detection, rerouting

Scenario description: Precondition: - AD Vehicle (3177) is at starting position - VRU with Smartphone (3120) is at end position - VRU with Smartphone (3121) and FlowRadar (3175) is positioned halfway the vehicle track - CEMA device is on route 2 and detecting crowd Initiate Rebalancing phase: 1. Smartphone 3120: send taxi request (send end location to vehicle (lon / lat)) Initiate Routing phase: 2. CEMA devices detect crowds on route 1 or route 2 --> dynamically change routes base on CEMA 3. Motion planning: Vehicle uses CEMA detection and call taxi request as input for choosing one of the two routes Initiate Urban Driving phase (incl. VRU detection) 4. Vehicle starts driving 5. Underway VRU (3121) is detected using smartphone and FlowRadar ITS-G5 6. With GeoFenching, vehicle starts slowing down on smartphone 7. With camera detection vehicle brakes when VRU is inline of camera 8. After VRU passes, vehicle continues journey 9. Vehicle arrives at requested end point (at VRU 3120). Session description: Rebalancing: - relocate the vehicle on request Urban Driving: - rerouting on crowd estimation (CEMA) - VRU detection with GeoFenching in vehicle (speed reduction) and warning on VRU smartphone Datasets descriptions: AUTOPILOT_BrainPort_UrbanDriving_DriverVehicleInteraction: Data extracted from the CAN of the vehicle Dataset Description This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle AUTOPILOT_BrainPort_UrbanDriving_EAI2Mobile: Data from the service to the mobile Dataset Description This dataset contains information sent to the mobile about the Estimated Arrival time and position AUTOPILOT_BrainPort_UrbanDriving_EnvironmentSensorsAbsolute: Data extracted from the vehicle environment sensors Dataset Description This dataset contains information about detected object, with absolute coordinates AUTOPILOT_BrainPort_UrbanDriving_EnvironmentSensorsRelative: Data extracted from the vehicle environment sensors Dataset Description This dataset contains information about detected object, with relative coordinates AUTOPILOT_BrainPort_UrbanDriving_IOT_CEMA_Message: Data from the service to the vehicle Dataset Description This dataset contains information from the Crowd Estimation and Mobility Analytics service AUTOPILOT_BrainPort_UrbanDriving_IOT_FlowRadar_Message: Data from the vehicle to the service Dataset Description This dataset contains the GPS informaton (speed,position,heading) from the vehicle AUTOPILOT_BrainPort_UrbanDriving_IotVehicleMessage: Data sent between all devices, vehicles and services Dataset Description 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. AUTOPILOT_BrainPort_UrbanDriving_IOT_VehicleStatus: Data sent from the vehicle to the service Dataset Description This dataset contains the current status of the vehicle AUTOPILOT_BrainPort_UrbanDriving_PositioningSystem: Data from GPS on the vehicle Dataset Description This dataset contains speed,longitude,latitude,heading from the GPS AUTOPILOT_BrainPort_UrbanDriving_SmartphoneGPS: Data sent by the mobile to the service Dataset Description This dataset contains the GPS informaton (speed,position,heading) from the mobile AUTOPILOT_BrainPort_UrbanDriving_SmartphoneStatus: Data sent from the mobile to the service Dataset Description This dataset contains the current status of the mobile AUTOPILOT_BrainPort_UrbanDriving_TaxiRequest: Data sent from the mobile to the service Dataset Description This dataset contains the requests for a taxi from the mobile phones AUTOPILOT_BrainPort_UrbanDriving_Vehicle: Data from the CAN and sensors about the state of the vehicle Dataset Description This dataset contains a.o temperature and battery state of the vehicles AUTOPILOT_BrainPort_UrbanDriving_VehicleDynamics: Data from the CAN and sensors about the state of the vehicle Dataset Description This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors

场景说明：
前置条件：
1. 自动驾驶车辆（AD Vehicle）3177处于起始位置
2. 携带智能手机的弱势道路使用者（VRU, Vulnerable Road User）3120位于终点位置
3. 携带智能手机的弱势道路使用者（VRU, Vulnerable Road User）3121与FlowRadar设备3175布置在车辆行驶路径的中点处
4. 人群估计与移动分析（CEMA）设备部署于路线2上，正在进行人群检测

初始化重平衡阶段：
1. 智能手机3120发送打车请求（将终点经纬度发送至车辆）

初始化路径规划阶段：
2. CEMA设备检测到路线1或路线2上的人群，基于CEMA检测结果动态调整行驶路线
3. 运动规划：车辆以CEMA检测结果与打车请求作为输入，从两条路线中选择其一

启动城市驾驶阶段（含VRU检测）：
4. 车辆启动行驶
5. 利用智能手机与FlowRadar ITS-G5设备检测到行进中的弱势道路使用者（VRU, Vulnerable Road User）3121
6. 通过地理围栏（GeoFenching）技术，车辆基于智能手机信号开始减速
7. 搭载摄像头的车辆在弱势道路使用者（VRU, Vulnerable Road User）处于摄像头视野内时执行制动操作
8. 待弱势道路使用者（VRU, Vulnerable Road User）驶离后，车辆继续行程
9. 车辆抵达指定终点（即弱势道路使用者（VRU, Vulnerable Road User）3120所在位置）

会话说明：
重平衡流程：根据请求重新调度车辆
城市驾驶流程：基于人群估计（CEMA）进行路线重规划；通过车载地理围栏（GeoFenching）实现弱势道路使用者（VRU, Vulnerable Road User）检测并减速，同时向VRU的智能手机发送预警信息

数据集说明：
1. AUTOPILOT_BrainPort_UrbanDriving_DriverVehicleInteraction：从车辆CAN总线（Controller Area Network, CAN）提取的数据集
数据集说明：本数据集包含车辆的油门状态、离合器状态、制动状态、制动力、雨刮器状态、方向盘角度等相关数据
2. AUTOPILOT_BrainPort_UrbanDriving_EAI2Mobile：从服务端发送至移动终端的数据集
数据集说明：本数据集包含向移动终端发送的预计到达时间与位置相关信息
3. AUTOPILOT_BrainPort_UrbanDriving_EnvironmentSensorsAbsolute：从车辆环境传感器提取的数据集
数据集说明：本数据集包含已检测目标的绝对坐标相关信息
4. AUTOPILOT_BrainPort_UrbanDriving_EnvironmentSensorsRelative：从车辆环境传感器提取的数据集
数据集说明：本数据集包含已检测目标的相对坐标相关信息
5. AUTOPILOT_BrainPort_UrbanDriving_IOT_CEMA_Message：从服务端发送至车辆的数据集
数据集说明：本数据集包含人群估计与移动分析（CEMA）服务的相关信息
6. AUTOPILOT_BrainPort_UrbanDriving_IOT_FlowRadar_Message：从车辆发送至服务端的数据集
数据集说明：本数据集包含车辆的GPS信息（速度、位置、航向）
7. AUTOPILOT_BrainPort_UrbanDriving_IotVehicleMessage：在所有设备、车辆与服务端之间传输的数据集
数据集说明：每条传感器数据提交均为一条消息（Message）。消息包含信封头（Envelope）、路径（Path），可选（且通常包含）路径事件（Path Events）与路径媒体（Path Media）。信封头包含发送方（即车辆）的基础身份信息，但不会泄露车辆所有者身份，也无法通过该信息区分同一车辆发出的不同消息。
8. AUTOPILOT_BrainPort_UrbanDriving_IOT_VehicleStatus：从车辆发送至服务端的数据集
数据集说明：本数据集包含车辆的当前状态信息
9. AUTOPILOT_BrainPort_UrbanDriving_PositioningSystem：车辆GPS系统产生的数据集
数据集说明：本数据集包含GPS采集的车辆速度、经度、纬度与航向信息
10. AUTOPILOT_BrainPort_UrbanDriving_SmartphoneGPS：从移动终端发送至服务端的数据集
数据集说明：本数据集包含移动终端的GPS信息（速度、位置、航向）
11. AUTOPILOT_BrainPort_UrbanDriving_SmartphoneStatus：从移动终端发送至服务端的数据集
数据集说明：本数据集包含移动终端的当前状态信息
12. AUTOPILOT_BrainPort_UrbanDriving_TaxiRequest：从移动终端发送至服务端的数据集
数据集说明：本数据集包含移动终端发出的打车请求信息
13. AUTOPILOT_BrainPort_UrbanDriving_Vehicle：从车辆CAN总线与传感器提取的车辆状态数据集
数据集说明：本数据集包含车辆的温度与电池状态等相关信息
14. AUTOPILOT_BrainPort_UrbanDriving_VehicleDynamics：从车辆CAN总线与传感器提取的车辆动力学状态数据集
数据集说明：本数据集包含通过CAN总线与外部传感器采集到的车辆加速度与限速值等相关信息

搜集汇总

背景与挑战

背景概述

该数据集是一个专注于自动驾驶和城市驾驶场景的多源数据集，包含车辆状态、环境传感器数据、GPS信息和智能手机交互数据，用于测试和验证自动驾驶技术中的VRU检测、动态路径规划和车辆重新平衡等功能。