Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Hierarchy of Motor Control01:18

Hierarchy of Motor Control

4.3K
The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
4.3K
Controller Configurations01:22

Controller Configurations

194
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
194
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

56
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
56
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.2K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
1.2K
Motor Units01:13

Motor Units

6.0K
The motor unit is a fundamental component of the neuromuscular system and plays a crucial role in coordinating muscle contractions. It consists of a somatic motor neuron, which connects and controls multiple skeletal muscle fibers, forming a single functional segment. The axon of the motor neuron branches out and establishes synaptic connections known as neuromuscular junctions with individual muscle fibers within the motor unit.
Motor units come in different sizes, with smaller units...
6.0K
Motor Units00:46

Motor Units

60.1K
A motor unit consists of two main components: a single efferent motor neuron (i.e., a neuron that carries impulses away from the central nervous system) and all of the muscle fibers it innervates. The motor neuron may innervate multiple muscle fibers, which are single cells, but only one motor neuron innervates a single muscle fiber.
60.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Multi-omics profiling reveals EMT-driven fibroblast activation in the renal injury niche.

Cellular and molecular life sciences : CMLS·2026
Same author

Effects of macro- and micronutrient intake on bone mineral density, osteoporotic fracture risk, inflammation, and functional rehabilitation outcomes in orthopedic patients: a systematic review and meta-analysis.

Frontiers in nutrition·2026
Same author

Cross-regional characterisation and prediction of reproductive phenology in Prunus cerasoides Buch. -Ham. Ex D. Don using sequential learning.

International journal of biometeorology·2026
Same author

Signal similarity-informed generative adversarial network for prediction of basal wetness conditions in Antarctica: a case study in the AGAP region.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same author

BDNF insufficiency exacerbates ALS progression.

Cell reports. Medicine·2026
Same author

Corrigendum to "A fully human monoclonal antibody targeting Semaphorin 5A alleviates the progression of rheumatoid arthritis" [Biomed. Pharmacother. 168 (2023) 115666].

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Oct 27, 2025

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

4.7K

Human-Machine Shared Driving Control for Semi-Autonomous Vehicles Using Level of Cooperativeness.

Anh-Tu Nguyen1, Jagat Jyoti Rath2, Chen Lv3

  • 1LAMIH Laboratory UMR CNRS 8201, Université Polytechnique Hauts-de-France, 59300 Valenciennes, France.

Sensors (Basel, Switzerland)
|July 24, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel haptic shared control system for semi-autonomous vehicles, enhancing lane keeping by adapting automation assistance based on driver cooperation and workload. This improves driver-automation conflict management.

Keywords:
human-machine shared controllane keeping assistancepolytopic LPV control

More Related Videos

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.1K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.9K

Related Experiment Videos

Last Updated: Oct 27, 2025

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

4.7K
Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.1K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.9K

Area of Science:

  • Automotive Engineering
  • Control Systems
  • Human-Machine Interaction

Background:

  • Semi-autonomous vehicles require effective human-automation collaboration for safe and efficient operation, particularly in lane-keeping tasks.
  • Existing shared control systems often struggle to adapt dynamically to varying driver states and vehicle conditions.
  • Understanding human-machine interaction principles is crucial for designing cooperative driving systems.

Purpose of the Study:

  • To propose and validate a new haptic shared control concept for lane keeping in semi-autonomous vehicles.
  • To introduce a metric for human-machine cooperative status to dynamically adjust automation assistance.
  • To manage driver workload and performance characteristics for optimized control authority.

Main Methods:

  • Development of a human-machine cooperative status metric and driver workload assessment.
  • Design of a time-varying assistance factor modulating torque based on driver performance.
  • Implementation of an integrated driver-in-the-loop vehicle model including yaw-slip, steering, and driver dynamics.
  • Application of a novel ℓ∞ linear parameter varying control technique to handle time-varying parameters.
  • Validation using Lyapunov stability theory and high-fidelity simulations.

Main Results:

  • The proposed haptic shared control method effectively manages driver-automation conflicts during lane keeping.
  • The system dynamically adjusts haptic assistance based on real-time driver cooperation and workload.
  • High-fidelity simulations demonstrate the robustness and effectiveness of the control strategy across various driving scenarios.
  • The ℓ∞ linear parameter varying control technique successfully addresses the time-varying nature of the system.

Conclusions:

  • The novel haptic shared control concept offers a significant advancement in cooperative driving for semi-autonomous vehicles.
  • The adaptive approach enhances safety and performance by optimizing the balance between human control and automation.
  • This research provides a robust framework for future development of intelligent driver-assistance systems.