CN, Advanced Driving, Cloud-assisted advanced driving

Use Case Category: Advanced Driving User Story: Cloud-assisted advanced driving Location: Chinese (CN) trial site According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency”. User Story: Cloud-assisted advanced driving In the China site, the roadside unit, remote control centre and cloud server will monitor and control the autonomous vehicles in real time, to realize the various testes of Internet-connected applications of vehicles safely and efficiently. In the high-level abstraction of the user story, Vehicle A and Vehicle B are both running in a straight line along the right lane. Vehicle B is traveling at a constant speed in front of Vehicle A, and both vehicles keep a small distance. In the beginning, the remote-control centre (MEC) issues the overtaking order to vehicle A through the RSU. After receiving the order, Vehicle A sends the overtaking information to Vehicle B through V2V communication and receive the real-time information from Vehicle B via V2V, which includes the position, speed and heading angle of the vehicle. Thus, Vehicle A makes an automatic decision according to the information of Vehicle B. The decision-making of Vehicle A is detailed as follows: First, it changes to the left lane; then it accelerates to overtake according to the speed of Vehicle B. Finally, it changes lane back to the right lane, and sends its information to Vehicle B. In this way, these two cars complete overtaking operation. In this process, Vehicle A exchanges messages related to CoCA (Coordinated collision avoidance) through the 3GPP V2X communication service, while other vehicles transmit messages through the 3GPP communication service as well, finally they will achieve coordinated manoeuvring.用例分类：高级驾驶 用户场景：云辅助高级驾驶 部署地点：中国（CN）试验场 根据3GPP TS 22.186 R16版本标准，高级驾驶（Advanced Driving）可实现半自动化或全自动化驾驶。该场景假设车辆间保持更长间距，每台车辆及/或路边单元（Road Side Unit, RSU）将自身本地传感器获取的数据共享给邻近车辆，从而支持车辆协同规划行驶轨迹或操作动作。此外，每台车辆还会向邻近车辆共享自身的驾驶意图。该用例组的优势在于提升出行安全性、实现碰撞规避以及优化交通效率。 用户场景：云辅助高级驾驶 在中国试验场中，路边单元、远程控制中心与云服务器将对自动驾驶车辆进行实时监控与管控，以安全高效地开展各类车联网应用测试。 在该用户场景的高层抽象模型中，车辆A与车辆B均沿右侧车道直线行驶。车辆B以恒定速度行驶于车辆A前方，两车保持较小间距。初始阶段，远程控制中心（Multi-Access Edge Computing, MEC）通过路边单元向车辆A下发超车指令。车辆A接收指令后，通过车车通信（Vehicle-to-Vehicle, V2V）向车辆B发送超车信息，并通过V2V接收来自车辆B的实时状态信息，包括车辆的位置、速度与航向角。据此，车辆A基于车辆B的信息自主做出决策。车辆A的决策流程详述如下：首先，变更至左侧车道；随后，根据车辆B的车速加速完成超车；最终，驶回右侧车道，并向车辆B发送自身的状态信息。至此，两车完成超车操作。 在此过程中，车辆A通过3GPP车万物互联（Vehicle-to-Everything, V2X）通信服务交换与协同避撞（Coordinated Collision Avoidance, CoCA）相关的消息，其他车辆同样通过3GPP通信服务传输消息，最终实现协同操作动作。