Zobrazeno 1 - 10
of 201
pro vyhledávání: '"Tsukada Manabu"'
Panoptic segmentation, which combines instance and semantic segmentation, has gained a lot of attention in autonomous vehicles, due to its comprehensive representation of the scene. This task can be applied for cameras and LiDAR sensors, but there ha
Externí odkaz:
http://arxiv.org/abs/2412.20881
Driving safety and responsibility determination are indispensable pieces of the puzzle for autonomous driving. They are also deeply related to the allocation of right-of-way and the determination of accident liability. Therefore, Intel/Mobileye desig
Externí odkaz:
http://arxiv.org/abs/2409.02503
Large Language Models (LLMs), AI models trained on massive text corpora with remarkable language understanding and generation capabilities, are transforming the field of Autonomous Driving (AD). As AD systems evolve from rule-based and optimization-b
Externí odkaz:
http://arxiv.org/abs/2407.19280
Recent advancements in LiDAR technology have significantly lowered costs and improved both its precision and resolution, thereby solidifying its role as a critical component in autonomous vehicle localization. Using sophisticated 3D registration algo
Externí odkaz:
http://arxiv.org/abs/2407.08384
Pseudonyms are widely used in Cooperative Intelligent Transport Systems (C-ITS) to protect the location privacy of vehicles. However, the unlinkability nature of pseudonyms also enables Sybil attacks, where a malicious vehicle can pretend to be multi
Externí odkaz:
http://arxiv.org/abs/2403.14020
Lane merging is one of the critical tasks for self-driving cars, and how to perform lane-merge maneuvers effectively and safely has become one of the important standards in measuring the capability of autonomous driving systems. However, due to the a
Externí odkaz:
http://arxiv.org/abs/2403.13251
The interactive decision-making in multi-agent autonomous racing offers insights valuable beyond the domain of self-driving cars. Mapless online path planning is particularly of practical appeal but poses a challenge for safely overtaking opponents d
Externí odkaz:
http://arxiv.org/abs/2403.07129
Autor:
Tao, Ye, Javanmardi, Ehsan, Lin, Pengfei, Nakazato, Jin, Jiang, Yuze, Tsukada, Manabu, Esaki, Hiroshi
Cooperative perception is crucial for connected automated vehicles in intelligent transportation systems (ITSs); however, ensuring the authenticity of perception data remains a challenge as the vehicles cannot verify events that they do not witness i
Externí odkaz:
http://arxiv.org/abs/2312.07948
Advancements in LiDAR technology have led to more cost-effective production while simultaneously improving precision and resolution. As a result, LiDAR has become integral to vehicle localization, achieving centimeter-level accuracy through technique
Externí odkaz:
http://arxiv.org/abs/2311.07913
The Potential Field (PF)-based path planning method is widely adopted for autonomous vehicles (AVs) due to its real-time efficiency and simplicity. PF often creates a rigid road boundary, and while this ensures that the ego vehicle consistently opera
Externí odkaz:
http://arxiv.org/abs/2308.10049