收藏切换
Research on Cognitive Decision Integration Mechanism of Human-Machine Collaboration in Automated Driving System
收藏切换
PDF
Wendi Zhang, Shijie Zhou, Hailiang Jin, Xuan Jiao
Automotive Digest | 2023, (9) : 11 - 18
Less
收藏切换
Automotive Digest | 2023, (9): 11-18
Special Topic on Technologies of Intelligent and Connected NEVs
Research on Cognitive Decision Integration Mechanism of Human-Machine Collaboration in Automated Driving System
Full
Wendi Zhang, Shijie Zhou, Hailiang Jin, Xuan Jiao
Affiliations
  • Beijing New Energy Co. LTD, Beijing 100176
Published: 2023-09-05 doi: 10.19822/j.cnki.1671-6329.20230061
Outline
收藏切换

With the maturity of autonomous driving technology, human-machine sharing has become the norm. Automated driving cars are no longer just “machines”, but “partners” who can complete driving tasks together. This requires industrial artificial intelligence to deeply integrate the cognitive information processing of the human brain in the human-machine symbiotic intelligence system. In order to better realize the overall advantages of human-machine cooperation, this paper analyzes the human-machine cooperation and division of labor in advanced autonomous vehicles by constructing a psychological framework of human-machine teamwork, including two-way mixed cognition, shared driving intention and control, so as to complete the integration of human-machine collaborative cognitive decision-making.

Human-machine collaboration  /  Cognitive-decision mechanism  /  Intelligence system  /  Automated driving
Wendi Zhang, Shijie Zhou, Hailiang Jin, Xuan Jiao. Research on Cognitive Decision Integration Mechanism of Human-Machine Collaboration in Automated Driving System[J]. Automotive Digest, 2023 , (9) : 11 -18 . DOI: 10.19822/j.cnki.1671-6329.20230061
Year 2023 volume Issue 9
PDF
254
118
Cite this Article
BibTeX
Article Info
doi: 10.19822/j.cnki.1671-6329.20230061
  • Online Date:2026-01-04
  • Published:2023-09-05
Article Data
Affiliations
History
Affiliations
    Beijing New Energy Co. LTD, Beijing 100176
References
Share
https://castjournals.cast.org.cn/joweb/qcwz/EN/10.19822/j.cnki.1671-6329.20230061
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT