Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

96
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
96
Force Classification01:22

Force Classification

1.1K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.1K
Prediction Intervals01:03

Prediction Intervals

2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.2K
Improving Translational Accuracy02:07

Improving Translational Accuracy

8.7K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
8.7K
Language and Cognition01:27

Language and Cognition

321
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
321
Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

729
Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
729

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Manure fertilizer-derived soil emerging pollutants compromises its fertility benefits for vegetable quality: At the scale of soil aggregates.

Ecotoxicology and environmental safety·2026
Same author

Distinct polyp recurrence timing and STK11 mutation status underlie clinical heterogeneity in pediatric Peutz-Jeghers syndrome.

Journal of pediatric gastroenterology and nutrition·2026
Same author

BETAV: A Unified BEV-Transformer and Bézier Optimization Framework for Jointly Optimized End-to-End Autonomous Driving.

Sensors (Basel, Switzerland)·2025
Same author

Hybrid Supervised and Reinforcement Learning for Motion-Sickness-Aware Path Tracking in Autonomous Vehicles.

Sensors (Basel, Switzerland)·2025
Same author

Knowledge Distillation-Enhanced Behavior Transformer for Decision-Making of Autonomous Driving.

Sensors (Basel, Switzerland)·2025
Same author

Gallium-68 Labeled Positron Emission Computed Tomography Tracer Targeting Glypican-3 with High Contrast for Hepatocellular Carcinoma Imaging.

ACS pharmacology & translational science·2024

相关实验视频

Updated: Jun 3, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

498

驾驶-拉玛:通过大型语言模型在智能驾驶中预测驾驶员意图.

Yi Chen1, Chengzhe Li1, Qirui Yuan1

  • 1College of Automotive Engineering, Jilin University, Changchun 130025, China.

Sensors (Basel, Switzerland)
|January 11, 2025
PubMed
概括

一个新的语言模型,Cockpit-Llama,通过分析动作和环境状态,准确地预测驾驶员的意图. 这增强了智能驾驶中的主动交互,优于现有的模型.

关键词:
人机交互的人机交互智能驾驶智能驾驶预测的意图预测的预测.大型语言模型

更多相关视频

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K
Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research
07:15

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Published on: December 18, 2020

4.4K

相关实验视频

Last Updated: Jun 3, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

498
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K
Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research
07:15

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Published on: December 18, 2020

4.4K

科学领域:

  • 人与计算机的交互
  • 人工智能的人工智能
  • 汽车工程 汽车工程

背景情况:

  • 汽车驾驶正在从反应性互动过渡到主动性互动,需要准确的驾驶员意图预测.
  • 加强主动互动需要了解驾驶员的行为和驾驶环境中的认知状态.

研究的目的:

  • 介绍Cockpit-Llama,一种用于预测驾驶员行为意图的新型语言模型.
  • 通过利用多属性驾驶数据来提高驾驶员意图预测的准确性和合理性.

主要方法:

  • 开发了Cockpit-Llama,这是一个基于动作,历史交互和环境状态的驾驶员意图预测的语言模型.
  • 构建了一个多属性驾驶数据集,包括驾驶员的情绪,驾驶,车辆,身体和环境状态.
  • 使用低级调整 (LoRA) 方法对Llama3-8b-Instruct模型进行了微调,以实现高效的参数优化.

主要成果:

  • 在多属性驾驶数据集上,Cockpit-Llama与先进方法相比,显示出更高的预测性能.
  • 获得的高分数:蓝色-4 (71.32),红色-1 (80.01),红色-2 (76.89),和红色-L (81.42).
  • 与ChatGPT-4相比,显示出显著的相对改善,包括ROUGE-1的183.61%和ROUGE-L.的201.27%.

结论:

  • Cockpit-Llama有效地预测驾驶员的意图,增强智能驾驶中的主动互动.
  • 该模型显著提高了汽车系统的推理和解释能力.
  • 开发的多属性数据集和LoRA微调有助于高效和准确的驾驶员行为建模.