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

Naturalistic Observations02:30

Naturalistic Observations

15.6K
If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
15.6K
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

1.9K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
1.9K

You might also read

Related Articles

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

Sort by
Same author

Clinical Application of Eyelid Composite Tissue Flap in the Repair of Full-thickness Eyelid Margin Defects.

Plastic and reconstructive surgery. Global open·2026
Same author

AI-Assisted Digital Single-Molecule Activity Tracker for Decoupling Intrinsic Heterogeneity from Photo-Oxidative Damage in High-Photon-Flux Enzymology.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Epitaxial growth of single-crystal violet phosphorus flakes on silicon substrates.

Nanoscale·2026
Same author

Dynamic Occlusion-Predictive Neural Network for Robust Roadside Multi-Vehicle Tracking.

Sensors (Basel, Switzerland)·2026
Same author

Assessing climate-driven treeline dynamics via the habitat suitability index.

Journal of environmental management·2026
Same author

Knee medial tightness after total knee arthroplasty is associated with superior clinical outcomes in Chinese patients: a retrospective cohort study.

Journal of orthopaedic surgery and research·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: Aug 23, 2025

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior
06:38

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Published on: June 9, 2020

4.9K

How Do Human-Driven Vehicles Avoid Pedestrians in Interactive Environments? A Naturalistic Driving Study.

Shulei Sun1,2, Ziqiang Zhang1, Zhiqi Zhang1

  • 1Key Laboratory of Automobile Measurement and Control & Safety, Xihua University, Chengdu 610039, China.

Sensors (Basel, Switzerland)
|October 27, 2022
PubMed
Summary
This summary is machine-generated.

Autonomous vehicles (AVs) struggle with natural pedestrian interactions due to a lack of human-like driving data. This study analyzed naturalistic driving data to understand vehicle-pedestrian behavior, enabling safer AV navigation.

Keywords:
driving behaviournaturalistic driving studypedestrian crossing intentionpedestrian–vehicle interactionscenarios classification

More Related Videos

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
11:12

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects

Published on: September 18, 2012

17.5K
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

4.6K

Related Experiment Videos

Last Updated: Aug 23, 2025

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior
06:38

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Published on: June 9, 2020

4.9K
Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
11:12

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects

Published on: September 18, 2012

17.5K
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

4.6K

Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Transportation Engineering

Background:

  • Autonomous vehicles (AVs) face challenges in safely and naturally navigating shared pedestrian environments.
  • Current AV decision-making lacks human-like responses to diverse pedestrian crossing intentions.
  • Limited naturalistic driving data and unclear interaction rationale hinder AV development.

Purpose of the Study:

  • To investigate the underlying behavioral mechanisms of pedestrian-vehicle interactions.
  • To collect and analyze naturalistic driving data focusing on pedestrian crossing events.
  • To provide insights for developing more natural and safe AV navigation strategies.

Main Methods:

  • Established a naturalistic driving test platform to gather vehicle and pedestrian motion data.
  • Developed a manual system to judge pedestrian crossing intentions during interactions.
  • Screened 98 single pedestrian crossing events from 1274 interaction events.
  • Analyzed metrics like Time-To-Collision (TTC) and vehicle deceleration to evaluate yielding behavior.

Main Results:

  • Quantified vehicle yielding behavior towards pedestrians in various interaction scenarios.
  • Classified avoidance strategies based on vehicle deceleration patterns.
  • Identified key behavioral patterns in human-driven vehicles interacting with pedestrians.

Conclusions:

  • Understanding human driving behavior in pedestrian interactions is crucial for AV development.
  • The analyzed data and behavioral insights can help AVs navigate more naturally and safely.
  • Future AVs can leverage these findings to improve pedestrian interaction and avoid collisions smoothly.