Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Yao Danya"'
The multi-modal perception methods are thriving in the autonomous driving field due to their better usage of complementary data from different sensors. Such methods depend on calibration and synchronization between sensors to get accurate environment
Externí odkaz:
http://arxiv.org/abs/2412.10033
Agent faults pose a significant threat to the performance of multi-agent reinforcement learning (MARL) algorithms, introducing two key challenges. First, agents often struggle to extract critical information from the chaotic state space created by un
Externí odkaz:
http://arxiv.org/abs/2412.00534
Multi-modal object detection in autonomous driving has achieved great breakthroughs due to the usage of fusing complementary information from different sensors. The calibration in fusion between sensors such as LiDAR and camera is always supposed to
Externí odkaz:
http://arxiv.org/abs/2405.16848
Sampling critical testing scenarios is an essential step in intelligence testing for Automated Vehicles (AVs). However, due to the lack of prior knowledge on the distribution of critical scenarios in sampling space, we can hardly efficiently find the
Externí odkaz:
http://arxiv.org/abs/2405.00696
Autor:
Song, Zhihang, He, Zimin, Li, Xingyu, Ma, Qiming, Ming, Ruibo, Mao, Zhiqi, Pei, Huaxin, Peng, Lihui, Hu, Jianming, Yao, Danya, Zhang, Yi
Publikováno v:
in IEEE Transactions on Intelligent Vehicles, vol. 9, no. 1, pp. 1847-1864, Jan. 2024
Autonomous driving techniques have been flourishing in recent years while thirsting for huge amounts of high-quality data. However, it is difficult for real-world datasets to keep up with the pace of changing requirements due to their expensive and t
Externí odkaz:
http://arxiv.org/abs/2304.12205
Scene perception is essential for driving decision-making and traffic safety. However, fog, as a kind of common weather, frequently appears in the real world, especially in the mountain areas, making it difficult to accurately observe the surrounding
Externí odkaz:
http://arxiv.org/abs/2112.04278
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Publikováno v:
In Accident Analysis and Prevention June 2021 155
Publikováno v:
In Transportation Research Interdisciplinary Perspectives March 2021 9
Akademický článek
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