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Hybrid A* Algorithm Based Trajectory Generation for Automated Driving Vehicle
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Su Zhou1, 2, Ruoyi Wang1, Youfa Zhang2, Gang Zhang1
Automotive Digest | 2023, (2) : 44 - 54
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Automotive Digest | 2023, (2): 44-54
Hybrid A* Algorithm Based Trajectory Generation for Automated Driving Vehicle
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Su Zhou1, 2, Ruoyi Wang1, Youfa Zhang2, Gang Zhang1
Affiliations
  • 1 School of Automotive Studies, Tongji University, Shanghai 201804
  • 2 Sino-German College, Tongji University, Shanghai 201804
Published: 2023-02-05 doi: 10.19822/j.cnki.1671-6329.20220270
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The hybrid A* algorithm of automated driving vehicles runs quickly, but it is difficult to ensure the continuity of curvature and comfort of vehicles, and can not guarantee the optimized results without collision. Aiming at the above problems, this paper aims to improve the comfort of vehicles, and optimize A* algorithm based on minimum impact. Algorithm pre-study in MATLAB and raster map is conducted to solve the problem of insufficient comfort during the motion of automated driving vehicles in low-speed scenarios. Then, the optimization algorithm is improved to ensure the safety of vehicles for the problem that the optimization algorithm may lead to trajectory collision, and the strategy of automatic adjustment of the “corridor” is given. The simulation results show that the optimized trajectory is collision-free and the curvature of the trajectory is smaller, and the acceleration does not exceed the normal range, which can meet the normal driving requirements.

Hybrid A* algorithm  /  Trajectory optimization algorithm  /  Bessel curve  /  Automated driving
Su Zhou, Ruoyi Wang, Youfa Zhang, Gang Zhang. Hybrid A* Algorithm Based Trajectory Generation for Automated Driving Vehicle[J]. Automotive Digest, 2023 , (2) : 44 -54 . DOI: 10.19822/j.cnki.1671-6329.20220270
Year 2023 volume Issue 2
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doi: 10.19822/j.cnki.1671-6329.20220270
  • Online Date:2026-01-04
  • Published:2023-02-05
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    1 School of Automotive Studies, Tongji University, Shanghai 201804
    2 Sino-German College, Tongji University, Shanghai 201804
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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
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