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Generation Method for Anthropomorphic Continuous Interactive Test Scenarios of Automated Driving
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Bing Zhu1, Tianxin Fan1, Jian Zhao1, Peixing Zhang1, Dongjian Song1, Yue Xue1, Wenbo Zhao2
Automotive Engineering | 2024, 46(9) : 1600 - 1607
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Automotive Engineering | 2024, 46(9): 1600-1607
Generation Method for Anthropomorphic Continuous Interactive Test Scenarios of Automated Driving
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Bing Zhu1, Tianxin Fan1, Jian Zhao1, Peixing Zhang1, Dongjian Song1, Yue Xue1, Wenbo Zhao2
Affiliations
  • 1. Jilin University,National Key Laboratory of Automotive Chassis Integration and Bionics,Changchun 130025
  • 2. China Intelligent and Connected Vehicles (Beijing) Research Institute Co. ,Ltd. ,Beijing 102600
Published: 2024-09-25 doi: 10.19562/j.chinasae.qcgc.2024.09.007
Outline
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Scenario-based simulation test method is an important means of automated driving vehicle safety verification; however, current test scenarios generation methods are mostly for independent scenarios. How to simulate the human real driving process to generate continuous interactive test scenario with challenges has become a problem that needs to be solved urgently in automated driving test evaluation. In this paper, an automated driving anthropomorphic continuous interactive test scenarios generation method is proposed. Firstly, the architecture for anthropomorphic continuous interactive test scenarios generation is established, and the vehicle motion behavior analysis is conducted based on the HighD dataset. On this basis, the current behavior of tested automated driving vehicle based on the trajectory similarity feature is analyzed, and the prediction of the future trajectory through the state transfer matrix is realized. Then, the type of the future behaviors of the traffic vehicles based on the trajectory interaction rules are determined, and the specific trajectory is generated by Transform network. Finally, the key performance indicators such as danger and anthropomorphism of the generated test scenarios are evaluated in simulation test environment, which proves the effectiveness of the method proposed in this paper.

automated driving  /  continuous interactive test scenario  /  trajectory prediction  /  anthropomorphic interactive trajectory generation
Bing Zhu, Tianxin Fan, Jian Zhao, Peixing Zhang, Dongjian Song, Yue Xue, Wenbo Zhao. Generation Method for Anthropomorphic Continuous Interactive Test Scenarios of Automated Driving[J]. Automotive Engineering, 2024 , 46 (9) : 1600 -1607 . DOI: 10.19562/j.chinasae.qcgc.2024.09.007
Year 2024 volume 46 Issue 9
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Article Info
doi: 10.19562/j.chinasae.qcgc.2024.09.007
  • Receive Date:2024-07-01
  • Online Date:2025-07-29
  • Published:2024-09-25
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History
  • Received:2024-07-01
  • Revised:2024-07-24
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Affiliations
    1. Jilin University,National Key Laboratory of Automotive Chassis Integration and Bionics,Changchun 130025
    2. China Intelligent and Connected Vehicles (Beijing) Research Institute Co. ,Ltd. ,Beijing 102600
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表12种不同金属材料的力学参数

Family
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Number of
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Number of
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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
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