Zobrazeno 1 - 10
of 190 225
pro vyhledávání: '"P A, Lane"'
Lane detection is a critical and challenging task in autonomous driving, particularly in real-world scenarios where traffic lanes can be slender, lengthy, and often obscured by other vehicles, complicating detection efforts. Existing anchor-based met
Externí odkaz:
http://arxiv.org/abs/2411.01499
Autor:
Liu, Willow, Qiao, Shuxin, Gao, Kyle, He, Hongjie, Chapman, Michael A., Xu, Linlin, Li, Jonathan
This research addresses the need for high-definition (HD) maps for autonomous vehicles (AVs), focusing on road lane information derived from aerial imagery. While Earth observation data offers valuable resources for map creation, specialized models f
Externí odkaz:
http://arxiv.org/abs/2410.05717
Autor:
MohajerAnsari, Pedram, Domeke, Alkim, de Voor, Jan, Mitra, Arkajyoti, Johnson, Grace, Salarpour, Amir, Olufowobi, Habeeb, Hamad, Mohammad, Pesé, Mert D.
Ensuring autonomous vehicle (AV) security remains a critical concern. An area of paramount importance is the study of physical-world adversarial examples (AEs) aimed at exploiting vulnerabilities in perception systems. However, most of the prevailing
Externí odkaz:
http://arxiv.org/abs/2409.18248
Autor:
You, Guoliang, Chu, Xiaomeng, Duan, Yifan, Li, Xingchen, Zhang, Sha, Ji, Jianmin, Zhang, Yanyong
Multi-modal systems enhance performance in autonomous driving but face inefficiencies due to indiscriminate processing within each modality. Additionally, the independent feature learning of each modality lacks interaction, which results in extracted
Externí odkaz:
http://arxiv.org/abs/2409.14170
In autonomous driving, High Definition (HD) maps provide a complete lane model that is not limited by sensor range and occlusions. However, the generation and upkeep of HD maps involves periodic data collection and human annotations, limiting scalabi
Externí odkaz:
http://arxiv.org/abs/2409.12409
Transfer Learning has become one of the standard methods to solve problems to overcome the isolated learning paradigm by utilizing knowledge acquired for one task to solve another related one. However, research needs to be done, to identify the initi
Externí odkaz:
http://arxiv.org/abs/2409.17158
We propose GGS, a Generalizable Gaussian Splatting method for Autonomous Driving which can achieve realistic rendering under large viewpoint changes. Previous generalizable 3D gaussian splatting methods are limited to rendering novel views that are v
Externí odkaz:
http://arxiv.org/abs/2409.02382
Autor:
Tanshi, Foghor, Söffker, Dirk
Lane change assistance system increase safety by providing warnings and other stability assistance to drivers to avert traffic dangers. In this contribution, lane change intention recognition was performed and applied to generate warnings for drivers
Externí odkaz:
http://arxiv.org/abs/2409.10551
The Lane-Emden inequality controls $\iint_{\mathbb{R}^{2d}}\rho(x)\rho(y)|x-y|^{-\lambda}\,dx\,dy$ in terms of the $L^1$ and $L^p$ norms of $\rho$. We provide a remainder estimate for this inequality in terms of a suitable distance of $\rho$ to the m
Externí odkaz:
http://arxiv.org/abs/2410.20113
This paper deals with explicit upper and lower bounds for principal eigenvalues and the maximum principle associated to generalized Lane-Emden systems (GLE systems, for short). Regarding the bounds, we generalize the upper estimate of Berestycki, Nir
Externí odkaz:
http://arxiv.org/abs/2410.06897