Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Oguchi, Kentaro"'
Conventional control, such as model-based control, is commonly utilized in autonomous driving due to its efficiency and reliability. However, real-world autonomous driving contends with a multitude of diverse traffic scenarios that are challenging fo
Externí odkaz:
http://arxiv.org/abs/2403.04232
Autor:
Bai, Zhengwei, Wu, Guoyuan, Barth, Matthew J., Liu, Yongkang, Sisbot, Emrah Akin, Oguchi, Kentaro
Cooperative perception (CP) is attracting increasing attention and is regarded as the core foundation to support cooperative driving automation, a potential key solution to addressing the safety, mobility, and sustainability issues of contemporary tr
Externí odkaz:
http://arxiv.org/abs/2302.03128
Autor:
Bai, Zhengwei, Wu, Guoyuan, Barth, Matthew J., Liu, Yongkang, Sisbot, Emrah Akin, Oguchi, Kentaro
Utilizing the latest advances in Artificial Intelligence (AI), the computer vision community is now witnessing an unprecedented evolution in all kinds of perception tasks, particularly in object detection. Based on multiple spatially separated percep
Externí odkaz:
http://arxiv.org/abs/2212.07060
Continual reinforcement learning aims to sequentially learn a variety of tasks, retaining the ability to perform previously encountered tasks while simultaneously developing new policies for novel tasks. However, current continual RL approaches overl
Externí odkaz:
http://arxiv.org/abs/2210.12301
Autor:
Bai, Zhengwei, Wu, Guoyuan, Barth, Matthew J., Liu, Yongkang, Sisbot, Emrah Akin, Oguchi, Kentaro, Huang, Zhitong
Perceiving the environment is one of the most fundamental keys to enabling Cooperative Driving Automation (CDA), which is regarded as the revolutionary solution to addressing the safety, mobility, and sustainability issues of contemporary transportat
Externí odkaz:
http://arxiv.org/abs/2208.10590
The prevalence of high-speed vehicle-to-everything (V2X) communication will likely significantly influence the future of vehicle autonomy. In several autonomous driving applications, however, the role such systems will play is seldom understood. In t
Externí odkaz:
http://arxiv.org/abs/2206.14391
Autor:
Bai, Zhengwei, Wu, Guoyuan, Barth, Matthew J., Liu, Yongkang, Sisbot, Emrah Akin, Oguchi, Kentaro
3D object detection plays a fundamental role in enabling autonomous driving, which is regarded as the significant key to unlocking the bottleneck of contemporary transportation systems from the perspectives of safety, mobility, and sustainability. Mo
Externí odkaz:
http://arxiv.org/abs/2203.06319
Autor:
Wei, Zhensong, Qi, Xuewei, Bai, Zhengwei, Wu, Guoyuan, Nayak, Saswat, Hao, Peng, Barth, Matthew, Liu, Yongkang, Oguchi, Kentaro
Environment perception including detection, classification, tracking, and motion prediction are key enablers for automated driving systems and intelligent transportation applications. Fueled by the advances in sensing technologies and machine learnin
Externí odkaz:
http://arxiv.org/abs/2203.00138
Autor:
Bai, Zhengwei, Nayak, Saswat Priyadarshi, Zhao, Xuanpeng, Wu, Guoyuan, Barth, Matthew J., Qi, Xuewei, Liu, Yongkang, Sisbot, Emrah Akin, Oguchi, Kentaro
Object perception plays a fundamental role in Cooperative Driving Automation (CDA) which is regarded as a revolutionary promoter for the next-generation transportation systems. However, the vehicle-based perception may suffer from the limited sensing
Externí odkaz:
http://arxiv.org/abs/2202.13505
Publikováno v:
In International Journal of Transportation Science and Technology September 2024 15:24-34