基于平行测试的认知自动驾驶智能架构研究  

An Intelligent Architecture for Cognitive Autonomous Driving Based on Parallel Testing

作　　者：王晓[1,2,3,4,5] 张翔宇[4] 周锐 田永林[4,5] 王建功 陈龙 孙长银 WANG Xiao;ZHANG Xiang-Yu;ZHOU Rui;TIAN Yong-Lin;WANG Jian-Gong;CHEN Long;SUN Chang-Yin(School of Artificial Intelligence,Anhui University,Hefei 230031;Engineering Research Center of Autonomous Unmanned System Technology,Ministry of Education,Hefei 230031;Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology,Hefei 230031;The State Key Laboratory for Management and Control of Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190;Qingdao Academy of Intelligent Industries,Qingdao 266000;Institute of System Engineering,Faculty of Innovation Engineering,Macao University of Science and Technology,Macao 999078;Vehicle Intelligence Pioneers,Inc.,Qingdao 266109)

机构地区：[1]安徽大学人工智能学院,合肥230031 [2]自主无人系统技术教育部工程研究中心,合肥230031 [3]安徽省无人系统与智能技术工程研究中心,合肥230031 [4]中国科学院自动化研究所复杂系统管理与控制国家重点实验室,北京100190 [5]青岛智能产业技术研究院,青岛266000 [6]澳门科技大学创新工程学院系统工程研究所,中国澳门999078 [7]青岛慧拓智能机器有限公司,青岛266109

出　　处：《自动化学报》2024年第2期356-371,共16页Acta Automatica Sinica

基　　金：广东省重点领域研发计划(2020B0909050003);国家自然科学基金(62173329)资助。

摘　　要：在大数据、云计算和机器学习等新一代人工智能技术的推动下,自动驾驶的感知智能在近年来得到显著的提升与发展.然而,与人类驾驶过程中隐含的以自我目的实现为引导的自探索性和自主性相比,现阶段自动驾驶技术主要以辅助驾驶功能为主,还停留在以被动感知、规划与控制为主的初级智能自动驾驶阶段.为实现车辆智能从数据驱动的环境感知、辅助决策、被动规划到知识驱动的场景认知、推理决策、主动规划的提升,亟需增强车辆自身对复杂外界信息归纳提炼、推理决策、评价估计等类人能力.首先回顾自动驾驶关键技术演化及其应用发展历程;随后分析测试对车辆智能评估的效用;然后基于平行测试理论,提出自动驾驶车辆认知智能训练、测试与评估空间的构建方法,并设计基于平行测试的认知自动驾驶智能训练框架.该项研究工作预期能为推动自动驾驶从感知智能向认知智能的升级提供可行的技术支撑与实现路径.Driven by the new generation of artificial intelligence technologies such as big data,cloud computing and machine learning,the perceptive intelligence of autonomous driving has been significantly improved and progressed in recent years.However,compared with the self-purpose driven human driving process,the current autonomous driving technologies are mainly focusing on the auxiliary driving functions,and still stay in a primary-intelligence stage which is dominated by passive perception,planning and control.In order to cross the“cognition gap”of vehicle intelligence,from data-driven environment perception,assisted decision making and passive planning to knowledge-driven scenario cognition,reasonable decision making and active planning,it is important to enhance the humanoid abilities of the vehicles,including but not limited to summarize and extract complex external informa-tion from the environment,reasoning,evaluation and estimation.This paper reviews the evolution and application of key technologies in autonomous driving,analyzes the effectiveness of testing on vehicle intelligence and perform-ance evaluation.After then,based on the parallel test theory,it puts forward the space construction method for training,testing and evaluating the cognitive intelligence of autonomous vehicle,and proposes an intelligent train-ing framework for cognitive autonomous driving.The work is expected to provide a feasible and possible path for autonomous vehicle cognitive intelligence.

关 键 词：认知自动驾驶 平行测试 平行驾驶 车辆认知智能 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] U463.6[自动化与计算机技术—控制科学与工程]