Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Weiping, Fu"'
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 2, Pp 315-331 (2024)
Abstract With the development of deep learning technology, the problem of data‐driven trajectory prediction and intention recognition has been widely studied. However, the pedestrian trajectory prediction and intention recognition methods based sol
Externí odkaz:
https://doaj.org/article/6a762e27ceb5404e977e160701234c4a
Publikováno v:
IEEE Access, Vol 12, Pp 46907-46918 (2024)
In the domain of pedestrian trajectory prediction(PTP) from a roadbed perspective, the visibility of pedestrian feature points is inevitably compromised by external noise interference, impacting both pedestrian pose estimation(PPE) and PTP. This pape
Externí odkaz:
https://doaj.org/article/e5d4d864b7a843e1b1ba708e5767a4f6
Publikováno v:
IEEE Access, Vol 12, Pp 9382-9391 (2024)
In order to analyze and predict the performance of mechanical structure and system, the tangential contact of solid-liquid interface under normal and tangential loads is studied, and the tangential stiffness model of rough surfaces is established by
Externí odkaz:
https://doaj.org/article/a3aae74d4068470e8f581f403ca5ed9f
Publikováno v:
IEEE Access, Vol 11, Pp 109104-109120 (2023)
The macroscopic relative motion solid-liquid interface widely exists in the contact motion pairs of machine tools and other mechanical equipment. In order to accurately obtain the tangential contact stiffness and damping parameters, the Savkoor asper
Externí odkaz:
https://doaj.org/article/de271f9191ba45bbb2ace184aa36f16f
Publikováno v:
IEEE Access, Vol 11, Pp 42809-42823 (2023)
Motion planning for autonomous vehicles remains a challenge in urban road environments with occlusions. In this study, we present a motion planning framework that prioritizes safety, comfort, and efficiency to enable autonomous vehicles to navigate s
Externí odkaz:
https://doaj.org/article/b9410ec16b184859b9f94e6be51ba843
Autor:
Shouguan Xiao, Weiping Fu
Publikováno v:
IEEE Access, Vol 11, Pp 13996-14005 (2023)
In order to solve outdoor mobile robots’ dependence on geographic information systems, and to realize automatic navigation in the face of complex and changeable scenes, we propose a method that selects landmark and adds prompt guidance so that the
Externí odkaz:
https://doaj.org/article/3ec388be1f684b98af5413ccb272faab
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Abstract The behavior intention estimation and interaction between Autonomous Vehicles (AV) and human traffic participants are the key problems in Automatic Driving System (ADS). When the classical decision theory studies implicitly assume that the b
Externí odkaz:
https://doaj.org/article/89507e11e27b41ac9f655881b9a1559b
Publikováno v:
Jixie chuandong, Vol 46, Pp 135-139 (2022)
Considering the status quo of processing，to avoid conventional spatial meshing theory，and relying on actual production projects，the forming principle of straight profile hourglass worm is analyzed in terms of geometry. After processing verifica
Externí odkaz:
https://doaj.org/article/d91f349b8d404fccae9ef73990c017a0
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
Abstract This study aimed to explore how autonomous vehicles can predict potential risks and efficiently pass through the dangerous interaction areas in the face of occluded scenes or limited visual scope. First, a Dynamic Bayesian Network based mode
Externí odkaz:
https://doaj.org/article/67a19a93b5e7460f85959fac532db3b6
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-16 (2022)
Abstract Autonomous vehicles for the intention of human behavior of the estimated traffic participants and their interaction is the main problem in automatic driving system. Classical cognitive theory assumes that the behavior of human traffic partic
Externí odkaz:
https://doaj.org/article/c69541085eeb40fb8b4b4940aaafa40a