面向自动驾驶的远程多维信息实时交互系统设计

doi:10.3969/j.issn.1674-8484.2024.06.015

摘要/Abstract

摘要：

为了提高低速、半封闭场景下自动驾驶车辆的安全性和运行效率，该文设计了一个基于第2代机器人操作系统（ROS2）框架的客户端/服务器（C/S）模式远程多维信息实时交互系统。采用数据传输融合技术，即配合多种数据预处理算法和统一的网络传输协议，实现了图像、点云和车辆状态信息的高效传输和实时交互。结果表明:在优良网络条件下，该系统的平均延时低于0.063 s，接收频率与发送频率几乎相等，丢包率不超过3.5%；集成的远程控制模块确保了操作的精确性; 在长时间稳定运行下系统的性能仍保持2.7%的中央处理器（CPU）低占用率，体现了出色的资源效率。该系统在确保实时性、可靠性和低资源消耗方面显示出有效性，可为自动驾驶领域的信息交互提供有力支持。

关键词: 自动驾驶, 半封闭场景, 多维信息交互, 实时性, 数据传输融合技术, 云控制

Abstract:

A design for a C/S (Client/Server) model-based real-time multidimensional information interaction system was presented to enhance the safety and operational efficiency of autonomous vehicles in low-speed, semi-closed scenarios, utilizing the Robot Operating System 2 (ROS2) framework. The research incorporated data transmission fusion technology, which combined various data preprocessing algorithms with a unified network transmission protocol, enabling efficient transmission and real-time interaction of images, point clouds, and vehicle status information. The results show that under excellent network conditions, the average delay of the system is less than 0.063 seconds, the receiving frequency is almost equal to the sending frequency, and the packet loss rate does not exceed 3.5%; The integrated remote control module ensures the accuracy of operations; Under long-term stable operation, the system still maintains a low central processing unit (CPU) usage rate of 2.7%, demonstrating excellent resource efficiency. The system has demonstrated effectiveness in ensuring real-time, reliability, and low resource consumption, and can provide strong support for information exchange in the field of autonomous driving.

Key words: autonomous driving, semi enclosed scenes, multidimensional information exchange, real time performance, data transmission fusion technology, cloud control

中图分类号:

TP39

曹莉凌, 刘君丽, 金升烨, 曹守启, 周国峰. 面向自动驾驶的远程多维信息实时交互系统设计[J]. 汽车安全与节能学报, 2024, 15(6): 934-942.

CAO Liling, LIU Junli, JIN Shengye, CAO Shouqi, ZHOU Guofeng. Design of a remote multidimensional information real time interaction system for autonomous driving[J]. Journal of Automotive Safety and Energy, 2024, 15(6): 934-942.

图/表 21

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传感器	消息类型	Protobuf自定义类型
IMU	sensor_msgs∶∶msg∶∶Imu	Imu_msgs∶∶ImuProto
远程控制	geometry_ msgs∶∶msg∶∶Twist	geometry_ msgs∶∶TwistProto

传感器	消息类型	Protobuf自定义类型
IMU	sensor_msgs∶∶msg∶∶Imu	Imu_msgs∶∶ImuProto
远程控制	geometry_ msgs∶∶msg∶∶Twist	geometry_ msgs∶∶TwistProto

硬件环境
车端计算机	NVIDIA Orin
车载摄像头	IMX307
车载激光雷达	Livox
车载IMU	Xsens 680G
客户端内存	64G
客户端CPU型号	i7-13700KF
软件环境
编程语言	C++
机器人操作系统	ROS-humble
交互界面可视化库QT	5.12
点云可视化的vtk库和pcl库	8.2.0、1.10
Protobuf	3.20.3
MQTT	paho-MQTT
车端操作系统	Ubuntu20.04
客户端操作系统	Ubuntu20.04

硬件环境
车端计算机	NVIDIA Orin
车载摄像头	IMX307
车载激光雷达	Livox
车载IMU	Xsens 680G
客户端内存	64G
客户端CPU型号	i7-13700KF
软件环境
编程语言	C++
机器人操作系统	ROS-humble
交互界面可视化库QT	5.12
点云可视化的vtk库和pcl库	8.2.0、1.10
Protobuf	3.20.3
MQTT	paho-MQTT
车端操作系统	Ubuntu20.04
客户端操作系统	Ubuntu20.04

实验	平均延时/ s	平均频率/ Hz	丢包/ %
①	0.036	29.8	3.3
②	0.028	29.7	3.5
③	0.063	30.2	3.3