Results 101 to 110 of about 1,101,470 (312)

Other title: Teen safe driving in Connecticut

, 2014
Annual; "Annual Report on Effectiveness of Connecticut's Teen Driving Laws.

core  

Anticipatory experience in everyday autonomous driving [PDF]

, 2020
In this paper, we discuss how people’s user experience (UX) of autonomous driving (AD) cars can be understood as a shifting anticipatory experience, as people experience degrees of AD through evolving advanced driver assistance systems (ADAS) in their ...
Fors, Vaike,, Fors, Vaike, Osz, Katalin, Lindgren, Thomas, Pink, Sarah, Pink, Sarah,, Lindgren, Thomas,, Osz, Katalin,   +7 more
core   +1 more source

Reinforcement-Learning-Based Trajectory Learning in Frenet Frame for Autonomous Driving

Applied Sciences
Autonomous driving is a complex problem that requires intelligent decision making, and it has recently garnered significant interest due to its potential advantages in convenience and safety.
Sangho Yoon, Youngjoon Kwon, Jaesung Ryu, Sungkwan Kim, Sungwoo Choi, Kyungjae Lee   +5 more
doaj   +1 more source

Driving policies of V2X autonomous vehicles based on reinforcement learning methods

IET Intelligent Transport Systems, 2020
Autonomous driving has been achieving great progress since last several years. However, the autonomous vehicles always ignore the important traffic information on the road because of the uncertainties of driving environment and the limitations of onboard
Zhenyu Wu, Kai Qiu, Hongbo Gao
doaj   +1 more source

Design and analysis strategies for robust microbiome ageing research

FEBS Letters, EarlyView.
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik, İsmail Güderer, Yi Wang, Tayyaba Alvi, Prasoon Pandey, Handan Melike Dönertaş   +5 more
wiley   +1 more source

An interactive enhanced driving dataset for autonomous driving

Scientific Data
Abstract Driving interaction data are important for training and evaluating autonomous driving Vision-Language-Action (VLA) models, but existing datasets contain limited dense interaction samples and weak alignment between trajectories, visual inputs, and language annotations.
Haojie Feng, Peizhi Zhang, Mengjie Tian, Xinrui Zhang 0004, Zhuoren Li, Junpeng Huang, Xiurong Wang, Junfan Zhu, Jianzhou Wang, Dongxiao Yin, Lu Xiong 0001   +10 more
openaire   +2 more sources

Autonomous driving goes downtown

IEEE Intelligent Systems, 1998
Most computer-vision systems for vehicle guidance are for highway scenarios. Developing autonomous or driver-assistance systems for complex urban traffic poses new algorithmic and system-architecture challenges. To address these issues, the authors introduce their intelligent Stop&Go system and discuss appropriate algorithms and approaches for vision ...
Uwe Franke, Dariu Gavrila, Steffen Görzig, Frank Lindner, Frank Paetzold, Christian Wöhler   +5 more
openaire   +1 more source

ABL kinase‐dependent phosphorylation of SH proteins promotes their direct interaction with CRK family SH2 domains

FEBS Letters, EarlyView.
CT10 regulator of kinase (CRK) and CRK‐Like (CRKL) are signaling adaptors driving cell adhesion, motility, differentiation, and proliferation. SH2‐domain containing (SH) proteins are enriched in YXXP motifs which when phosphorylated create preferred binding sites for CRK family SH2 domains.
Phoebe M. Cousens, Brendan W. Chandler, Anna M. Schmoker, Jaye L. Weinert, Charlotte A. Kearns, Warren T. Yacawych, Amila Šemić, Alicia M. Ebert, Bryan A. Ballif   +8 more
wiley   +1 more source

Improving training dynamics of projected GAN-CLC via state feedback control theory

npj Artificial Intelligence
Generative adversarial networks (GANs) are pivotal for generative artificial intelligence, but their training is plagued by three intertwined core challenges: instability, gradient vanishing, and mode collapse.
Mingxing Li, Chenlong Li, Hong Lu
doaj   +1 more source

Legal AI for All: Reducing Perplexity and Boosting Accuracy in Normative Texts With Fine-Tuned LLMs and RAG

IEEE Access
This study investigates the potential of open-source Large Language Models (LLMs) to enhance the accessibility and understanding of complex legal information.
Patricio Santiago Garcia-Montero, Paulina Vizcaino, Ivan Galo Reyes-Chacon, Manuel Eugenio Morocho-Cayamcela   +3 more
doaj   +1 more source