Zobrazeno 1 - 10
of 5 022
pro vyhledávání: '"automated driving"'
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 8, Pp 1477-1493 (2024)
Abstract A lightweight, high‐definition vector map (HDVM) enables fully autonomous vehicles. However, the generation of HDVM remains a challenging problem, especially in complex urban scenarios. Moreover, numerous factors in the urban environment c
Externí odkaz:
https://doaj.org/article/36a1303fe6854f529b70334f0d4db3d4
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 8, Pp 1445-1458 (2024)
Abstract Aiming to address the challenge where existing methods struggle to predict accurate disparities for imperfectly rectified stereo images, and that supervised training requires a considerable amount of ground truth, a self‐supervised binocul
Externí odkaz:
https://doaj.org/article/3948519a1acd487c9223feacd52fb901
Autor:
Mohit Kumar Singh, Nicolette Formosa, Cheuk Ki Man, Craig Morton, Cansu Bahar Masera, Mohammed Quddus
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 7, Pp 1210-1226 (2024)
Abstract Connected and automated vehicles (CAVs) are being developed and designed to operate on existing roads. Their safe and efficient operation during roadworks, where traffic management measures are often introduced, is crucial. Two alternative m
Externí odkaz:
https://doaj.org/article/0fd055f8daba46f7800543cb30c6df53
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 7, Pp 1272-1288 (2024)
Abstract Speed curve planning is one of the most important functions of automatic train operation (ATO). To improve the real‐time optimization capability and driver‐friendliness of the existing ATO, an extended ATO framework considering both auto
Externí odkaz:
https://doaj.org/article/312a8143a2714a879944c645c2a61664
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 7, Pp 1259-1271 (2024)
Abstract The key motivation of this paper lies in the development of a high‐level decision‐making framework for autonomous overtaking maneuvers on two‐lane country roads with dynamic oncoming traffic. To generate an optimal and safe decision se
Externí odkaz:
https://doaj.org/article/a8c8cdcea9894233af18bc22bbb3e4f3
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 7, Pp 1227-1236 (2024)
Abstract In order to enhance the performance of safety and fuel economy of connected hybrid electric vehicles (CHEVs), a novel distributed hierarchical platoon control scheme of CHEVs is proposed. First, the non‐linear dynamic model of CHEVs platoo
Externí odkaz:
https://doaj.org/article/79cf6163f7bd4154b037c2c40f1068b1
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 7, Pp 1355-1368 (2024)
Abstract Deep images can provide rich spatial structure information, which can effectively exclude the interference of illumination and road texture in road scene segmentation and make better use of the prior knowledge of road area. This paper first
Externí odkaz:
https://doaj.org/article/9d8d1d53be7e4db693a23bc799dcd0e8
Publikováno v:
Journal of Intelligent and Connected Vehicles, Vol 7, Iss 2, Pp 138-150 (2024)
Trajectory prediction for heterogeneous traffic agents plays a crucial role in ensuring the safety and efficiency of automated driving in highly interactive traffic environments. Numerous studies in this area have focused on physics-based approaches
Externí odkaz:
https://doaj.org/article/3be80af6f912430595462b9766f7e282
Autor:
Yurong Li, Liqun Peng
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 6, Pp 1016-1030 (2024)
Abstract In this work, the connected vehicle's messages are used to create an enhanced adaptive traffic signal control (ATSC) system for improved traffic flow. Few existing studies use connected and automated vehicles (CAVs) to develop traffic signal
Externí odkaz:
https://doaj.org/article/0d5d4300cc994ae2a906295cc44ca2d7
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 6, Pp 1121-1136 (2024)
Abstract To eliminate blind spots in the field of vision and achieve a safe and collision‐free path, this paper proposes a path planning method based on multivehicle collaborative mapping in the context of vehicle networking. First, a multi vehicle
Externí odkaz:
https://doaj.org/article/7aead41606c64724831c9a62c80701da