Towards the Unified Principles for Level 5 Autonomous Vehicles
The rapid advance of autonomous vehicles (AVs) has motivated new perspectives and potential challenges for existing modes of transportation. Currently, driving assistance systems of Level 3 and below have been widely produced, and several applications of Level 4 systems to specific situations have a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-09-01
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| Series: | Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095809920304008 |
| _version_ | 1830285283202957312 |
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| author | Jianqiang Wang Heye Huang Keqiang Li Jun Li |
| author_facet | Jianqiang Wang Heye Huang Keqiang Li Jun Li |
| author_sort | Jianqiang Wang |
| collection | DOAJ |
| description | The rapid advance of autonomous vehicles (AVs) has motivated new perspectives and potential challenges for existing modes of transportation. Currently, driving assistance systems of Level 3 and below have been widely produced, and several applications of Level 4 systems to specific situations have also been gradually developed. By improving the automation level and vehicle intelligence, these systems can be further advanced towards fully autonomous driving. However, general development concepts for Level 5 AVs remain unclear, and the existing methods employed in the development processes of Levels 0–4 have been mainly based on task-driven function development related to specific scenarios. Therefore, it is difficult to identify the problems encountered by high-level AVs. The essential logical and physical mechanisms of vehicles have hindered further progression towards Level 5 systems. By exploring the physical mechanisms behind high-level autonomous driving systems and analyzing the essence of driving, we put forward a coordinated and balanced framework based on the brain–cerebellum–organ concept through reasoning and deduction. Based on a mixed mode relying on the crow inference and parrot imitation approach, we explore the research paradigm of autonomous learning and prior knowledge to realize the characteristics of self-learning, self-adaptation, and self-transcendence for AVs. From a systematic, unified, and balanced point of view and based on least action principles and unified safety field concepts, we aim to provide a novel research concept and develop an effective approach for the research and development of high-level AVs, specifically at Level 5. |
| first_indexed | 2024-12-19T03:36:20Z |
| format | Article |
| id | doaj.art-881bb5641bca4024ba9f2814ea409bf4 |
| institution | Directory Open Access Journal |
| issn | 2095-8099 |
| language | English |
| last_indexed | 2024-12-19T03:36:20Z |
| publishDate | 2021-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Engineering |
| spelling | doaj.art-881bb5641bca4024ba9f2814ea409bf42022-12-21T20:37:22ZengElsevierEngineering2095-80992021-09-017913131325Towards the Unified Principles for Level 5 Autonomous VehiclesJianqiang Wang0Heye Huang1Keqiang Li2Jun Li3Corresponding author.; State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, ChinaThe rapid advance of autonomous vehicles (AVs) has motivated new perspectives and potential challenges for existing modes of transportation. Currently, driving assistance systems of Level 3 and below have been widely produced, and several applications of Level 4 systems to specific situations have also been gradually developed. By improving the automation level and vehicle intelligence, these systems can be further advanced towards fully autonomous driving. However, general development concepts for Level 5 AVs remain unclear, and the existing methods employed in the development processes of Levels 0–4 have been mainly based on task-driven function development related to specific scenarios. Therefore, it is difficult to identify the problems encountered by high-level AVs. The essential logical and physical mechanisms of vehicles have hindered further progression towards Level 5 systems. By exploring the physical mechanisms behind high-level autonomous driving systems and analyzing the essence of driving, we put forward a coordinated and balanced framework based on the brain–cerebellum–organ concept through reasoning and deduction. Based on a mixed mode relying on the crow inference and parrot imitation approach, we explore the research paradigm of autonomous learning and prior knowledge to realize the characteristics of self-learning, self-adaptation, and self-transcendence for AVs. From a systematic, unified, and balanced point of view and based on least action principles and unified safety field concepts, we aim to provide a novel research concept and develop an effective approach for the research and development of high-level AVs, specifically at Level 5.http://www.sciencedirect.com/science/article/pii/S2095809920304008Autonomous vehiclePrinciple of least actionDriving safety fieldAutonomous learningBasic paradigm |
| spellingShingle | Jianqiang Wang Heye Huang Keqiang Li Jun Li Towards the Unified Principles for Level 5 Autonomous Vehicles Engineering Autonomous vehicle Principle of least action Driving safety field Autonomous learning Basic paradigm |
| title | Towards the Unified Principles for Level 5 Autonomous Vehicles |
| title_full | Towards the Unified Principles for Level 5 Autonomous Vehicles |
| title_fullStr | Towards the Unified Principles for Level 5 Autonomous Vehicles |
| title_full_unstemmed | Towards the Unified Principles for Level 5 Autonomous Vehicles |
| title_short | Towards the Unified Principles for Level 5 Autonomous Vehicles |
| title_sort | towards the unified principles for level 5 autonomous vehicles |
| topic | Autonomous vehicle Principle of least action Driving safety field Autonomous learning Basic paradigm |
| url | http://www.sciencedirect.com/science/article/pii/S2095809920304008 |
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