|本期目录/Table of Contents|

[1]王建强,王昕.智能网联汽车体系结构与关键技术[J].长安大学学报(社科版),2017,19(06):18-25.
 WANG Jian-qiang,WANG Xin.Study on the system framework and key technology of Intelligent connected vehicles[J].Journal of Chang'an University(Social Science Edition),2017,19(06):18-25.
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智能网联汽车体系结构与关键技术(PDF)
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《长安大学学报(社科版)》[ISSN:1671-6248/CN:61-1391/C]

卷:
第19卷
期数:
2017年06期
页码:
18-25
栏目:
交通运输经济与管理
出版日期:
2018-02-07

文章信息/Info

Title:
Study on the system framework and key technology of Intelligent connected vehicles
作者:
王建强王昕
兰州交通大学 交通运输学院,甘肃 兰州 730070
Author(s):
WANG Jian-qiangWANG Xin
School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China
关键词:
智能网联汽车无人驾驶自动驾驶人工智能云平台大数据车路协同系统
Keywords:
Intelligent connected vehicles (ICV) driverless automatic driving artificial intelligence cloud platform big data cooperative vehicleinfrastructure system
分类号:
U495
DOI:
-
文献标志码:
A
摘要:
智能网联汽车(Intelligent connected vehicles,ICV)是无人驾驶技术的核心载体,产业链长,市场巨大,吸引了国内外众多汽车厂商和信息企业都纷纷投向ICV的研发与测试,部分ICV车型已进入量产阶段,新的概念车型也陆续提出。针对新型ICV的发展现状与关键技术,从ICV智能化和网联化两个维度对ICV中涉及到的相关技术进行分析,进一步从信息处理的感知层、决策层、控制层3个层次构建了ICV发展过程中的关键技术体系结构。研究表明,车辆环境感知和通信技术技术涵盖自车状态和外部环境,短程通信技术(DSRC)、机器视觉和激光雷达技术是实现车辆环境信息采集功能完善的关键;车路协同系统涉及车—车通信、车—路通信、车—云通信,协同智能交通系统、云平台和大数据技术是车路协同技术的关键;驾驶辅助技术包括自适应巡航控制系统、车道偏离/避免系统、碰撞预警/避免系统等8个构成,这是辅助驾驶、部分自动驾驶和有条件的自动驾驶3个智能化阶段中的关键;具有自主学习、自我决策的人工智能技术和信息安全技术也是智能网联汽车的关键技术,在此基础上,还应该实现多种技术间的相互支撑与融合,克服关键技术协同障碍,才能实现ICV的市场推广与普及应用。
Abstract:
Intelligent connected vehicles are the core carrier of driverless technology, which has attracted many domestic and foreign automobile manufacturers and information enterprises to invest in R&D and test of ICV for their long industry chain and huge market. Some ICVs have been into mass production stage, the new concept models were also put forward one after another. With probing into the development status and key technologies of new ICV, the related technologies in ICV were analyzed from the two dimensions of ICV intelligence and networking, and the key technology and system frameworkin the development of ICV were constructed from three layers of information processing: perception layer, decisionmaking layer and control layer. The results show that the environment perception of vehicles and communication technologies covers vehicle state and external environment, Delicated short Range communication (DSRC), machine vision and laser radar technology are the keys to improve the function on environmental information collection of vehicle; cooperative vehicleinfrastructure system involvesvehiclevehicle communication, vehicleroad communication and vehiclecloud communication, collaborative intelligent transportation system, cloud platform and big data technology are the key of the cooperative vehicleinfrastructure technology; driving assistance technology includes adaptive cruise control system, lane departure / avoidance system, collision warning / avoidance system and other 8 components, which is the key in the three smart intelligent phases of assist driving, partially automatic driving and conditional automatic driving; the artificial intelligence technology and information security technology with independent learning and selfdecisionmaking are also the key technology of ICV. On this basis, the mutual support and integration of various technologies should be realized, and the key technical coordination obstacles should be overcame so as to achieve the marketing and popularization of ICV.

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备注/Memo

备注/Memo:
国家自然科学基金项目(71761025);国家社会科学基金项目(14XGL011)
更新日期/Last Update: 2018-02-07