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行人意向预测的依赖隐马尔可夫模型：考虑多变量相互作用力

IF 3.6 2区 工程技术 Q2 TRANSPORTATION
Transportmetrica A-Transport Science Pub Date : 2024-07-08 DOI:10.1080/23249935.2024.2373921
Zhuping Zhou, Zixu Wang, Yang Liu, Zheng Chen, Yongneng Xu
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引用次数: 0

摘要

准确识别和预测行人的意图对自动驾驶汽车的安全至关重要。然而，现有的预测模型往往未能全面考虑行人与车辆之间的相互作用。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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Dependent Hidden Markov Model for pedestrian intention prediction: considering Multivariate Interaction Force
Accurately recognizing and predicting pedestrian intentions is crucial for autonomous vehicle safety. However, existing prediction models often fail to comprehensively consider interactions between...
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来源期刊
Transportmetrica A-Transport Science
Transportmetrica A-Transport Science TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
8.10
自引率
12.10%
发文量
55
期刊介绍： Transportmetrica A provides a forum for original discourse in transport science. The international journal''s focus is on the scientific approach to transport research methodology and empirical analysis of moving people and goods. Papers related to all aspects of transportation are welcome. A rigorous peer review that involves editor screening and anonymous refereeing for submitted articles facilitates quality output.
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