面向安防场景的智能网联巡逻车关键技术及应用

刘玉超; 李子月

doi:10.11959/j.issn.1000-0801.2020133

您当前的位置：

首页 >

文章列表页 >

面向安防场景的智能网联巡逻车关键技术及应用

专题：车联网与安全 | 更新时间：2024-06-05

- 面向安防场景的智能网联巡逻车关键技术及应用
- Key technology and application of intelligent connected patrol vehicles for security scenario
- 电信科学 2020年36卷第4期页码：53-60
- 作者机构：
  
  1. 一体化指挥调度技术国家工程实验室，北京 100080
  2. 南京航空航天大学自动化学院导航研究中心，江苏南京 211106
- 作者简介：
  
  [ "刘玉超（1980- ），男，博士，一体化指挥调度技术国家工程实验室主任、高级工程师，主要研究方向为人工智能、智能驾驶、指挥调度" ]
  [ "李子月（1986- ），男，一体化指挥调度技术国家工程实验室技术总监，南京航空航天大学自动化学院导航研究中心博士生，主要研究方向为智能驾驶、数据融合、组合导航" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2020133
  中图分类号： TP393
- 网络出版日期：2020-04，
  
  纸质出版日期：2020-04-20
- 稿件说明：
移动端阅览
刘玉超, 李子月. 面向安防场景的智能网联巡逻车关键技术及应用[J]. 电信科学, 2020,36(4):53-60.

Yuchao LIU, Ziyue LI. Key technology and application of intelligent connected patrol vehicles for security scenario[J]. Telecommunications science, 2020, 36(4): 53-60.
刘玉超, 李子月. 面向安防场景的智能网联巡逻车关键技术及应用[J]. 电信科学, 2020,36(4):53-60. DOI： 10.11959/j.issn.1000-0801.2020133.

Yuchao LIU, Ziyue LI. Key technology and application of intelligent connected patrol vehicles for security scenario[J]. Telecommunications science, 2020, 36(4): 53-60. DOI： 10.11959/j.issn.1000-0801.2020133.

摘要

结合行业场景的实践应用，是当前人工智能技术普遍面临的问题。面向安防应用场景，研究无人驾驶技术的实践落地——智能网联巡逻车。感知系统集成了视觉、雷达、惯性导航等多种传感器，利用人工智能、数据融合等关键技术实现对平台本体、道路环境及目标行为的准确识别。将人类经验（human intelligence， HI）的场景认知和人工智能（artificial intelligence，AI）的计算认知相结合，构建面向安防场景的混合智能认知系统。基于“人在回路”系统架构，依托5G通信、V2X（vehicle to everything）、边缘计算等技术，将自动驾驶和指挥调度融合，设计了人、机器、环境之间等多种交互模式，保证了系统安全、可靠、稳定运行，大幅提高工作效率。

Abstract

Practical applications combined with industry scene is a common problem in the present artificial intelligence technology.Facing the security application scenario

the practice landing of unmanned technology -- intelligent connected patrol vehicle was studied.Integrating different sensors such as camera

LiDAR

inertial navigation system (INS)

etc

the awareness system can accurately identify the platform itself

road conditions and target behavior using key technology such as artificial intelligence (AI)

data fusion.Combining human intelligence (HI) in scene cognition of human experience and artificial intelligence (AI) in cognition of computing

a hybrid intelligent cognitive system using to security scene was built.Based on human in the loop system architecture and technology such as 5G

vehicle to everything (V2X)

edge computing

etc

different interactions between human

machine and environment were designed

which ensured the safe and reliable operation of the system and increased the work efficiency by a wide margin.

关键词

Keywords

references

FULTON J , JOANNE P . DARPA grand challenge a pioneering event for autonomous robotic ground vehicles [J ] . Industrial Robot , 2004 , 31 ( 5 ):414.

PATTERSON D A . Robots in the desert:a research parable for our times [J ] . Communications of ACM , 2005 , 48 ( 12 ):31.

MONTEMERLO M , BECKER J , BHAT S , et al . Junior:the Stanford entry in the urban challenge [J ] . Journal of Field Robotics , 2008 , 25 ( 9 ): 569 - 597 .

HINTON G E , OSINDERO S , TEH Y W . A fast learning algorithm for deep belief nets [J ] . Neural Computation , 2006 , 18 ( 7 ): 1527 - 1554 .

SAE International.Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles [S ] . Warrendale:SAE International , 2018 .

方箭 , 冯大权 , 段海军 , 等 . V2X通信研究概述 [J ] . 电信科学 , 2019 , 35 ( 6 ): 102 - 112 .

FANG J , FENG D Q , DUAN H J , et al . An overview of V2X communications [J ] . Telecommunications Science , 2019 , 35 ( 6 ): 102 - 112 .

范向民 , 范俊君 , 田丰 , 等 . 人机交互与人工智能:从交替浮沉到协同共进 [J ] . 中国科学:信息科学 , 2019 ( 49 ): 361 - 368 .

FAN X M , FAN J J , TIAN F , et al . Human-computer interaction and artificial intelligence:from competition to integration [J ] . Science China Information Sciences , 2019 ( 49 ): 361 - 368 .

胡云峰 , 曲婷 , 刘俊 , 等 . 智能汽车人机协同控制的研究现状与展望 [J ] . 自动化学报 , 2019 , 45 ( 7 ): 1261 - 1280 .

HU Y F , QU T , LIU J , et al . Human-machine cooperative control of intelligent vehicle:recent developments and future perspectives [J ] . ACTA Automatica Sinica , 2019 , 45 ( 7 ): 1261 - 1280 .

3GPP.Technical specification group services and system aspects; service requirements for the 5G system,stage1 (Release 16):3GPP TS22.261 V16.4.0 [S ] . 2018 .

施巍松 , 张星洲 , 王一帆 , 等 . 边缘计算:现状和展望 [J ] . 计算机研究与发展 , 2019 , 56 ( 1 ): 69 - 89 .

SHI W S , ZHANG X Z , WANG Y F , et al . Edge computing:state-of-the-art and future directions [J ] . Journal of Computing Research and Development , 2019 , 56 ( 1 ): 69 - 89 .

马洪源 , 肖子玉 , 卜忠贵 , 等 . 5G边缘计算技术应用与展望 [J ] . 电信科学 , 2019 , 35 ( 6 ): 114 - 123 .

MA H Y , XIAO Z Y , BU Z G , et al . 5G edge computing technology and application prospects [J ] . Telecommunications Science , 2019 , 35 ( 6 ): 114 - 123 .

ETSI . Mobile edge computing (MEC) service scenarios [S ] . 2016 .

3GPP.Study on enhancement of 3GPP support for 5G V2X services:TR22.886,v.15.1.0 [S ] . 2017 .

陈山枝 , 胡金玲 , 时岩 , 等 . LTE-V2X车联网技术、标准与应用 [J ] . 电信科学 , 2018 , 34 ( 4 ): 1 - 11 .

CHEN S Z , HU J L , SHI Y , et al . Technology,standards and applications of LTE-V2X for vehicular networks [J ] . Telecommunications Science , 2018 , 34 ( 4 ): 1 - 11 .

浏览量

783

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

面向垂直行业专网的确定性SLA指标分级研究

5G多路冗余传输技术综述

星地融合下的手机直连关键技术研究

配电网5G通信架构及其时延可靠性研究

基于大数据的5G流量驻留比极限值研究