AIMC Topic: Safety
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Comprehensive Assessment of Artificial Intelligence Tools for Driver Monitoring and Analyzing Safety Critical Events in Vehicles.
Sensors (Basel, Switzerland)
Apr 12, 2024
Human factors are a primary cause of vehicle accidents. Driver monitoring systems, utilizing a range of sensors and techniques, offer an effective method to monitor and alert drivers to minimize driver error and reduce risky driving behaviors, thus h...
Perceptions of vulnerable roadway users on autonomous vehicle regulations.
Journal of safety research
Feb 23, 2024
INTRODUCTION: Development and implementation of autonomous vehicle (AV) related regulations are necessary to ensure safe AV deployment and wide acceptance among all roadway users. Assessment of vulnerable roadway users' perceptions on AV regulations ...
Can we trust our eyes? Interpreting the misperception of road safety from street view images and deep learning.
Accident; analysis and prevention
Jan 12, 2024
Road safety is a critical concern that impacts both human lives and urban development, drawing significant attention from city managers and researchers. The perception of road safety has gained increasing research interest due to its close connection...
A Literature Review on Safety Perception and Trust during Human-Robot Interaction with Autonomous Mobile Robots That Apply to Industrial Environments.
IISE transactions on occupational ergonomics and human factors
Jan 8, 2024
Occupational ApplicationsAutonomous mobile robots are used in manufacturing and warehousing industries, to transport material across the facility and deliver parts to work cells. Human workers might encounter or interact with these robots in aisle wa...
A spatio-temporal deep learning approach to simulating conflict risk propagation on freeways with trajectory data.
Accident; analysis and prevention
Nov 18, 2023
On freeways, sudden deceleration or lane-changing by vehicles can trigger conflict risk that propagates backward in a specific pattern. Simulating this pattern of conflict risk propagation can not only help prevent crashes but is also vital for the d...
Before-after safety evaluation of part-time protected right-turn signals: An extreme value theory approach by applying artificial intelligence-based video analytics.
Accident; analysis and prevention
Oct 19, 2023
Extreme value theory models have opened doors for before-after safety evaluation of engineering treatments using traffic conflict techniques. Recent advancements in automated conflict extraction technologies have further expedited conflict-based safe...
A Fuzzy Clustering Approach to Identify Pedestrians' Traffic Behavior Patterns.
Journal of research in health sciences
Sep 29, 2023
BACKGROUND: Pattern recognition of pedestrians' traffic behavior can enhance the management efficiency of interested groups by targeting access to them and facilitating planning via more specific surveys. This study aimed to evaluate the pedestrians'...
LiDAR-Based Maintenance of a Safe Distance between a Human and a Robot Arm.
Sensors (Basel, Switzerland)
Apr 26, 2023
This paper demonstrates the capabilities of three-dimensional (3D) LiDAR scanners in supporting a safe distance maintenance functionality in human-robot collaborative applications. The use of such sensors is severely under-utilised in collaborative w...
Dense reinforcement learning for safety validation of autonomous vehicles.
Nature
Mar 22, 2023
One critical bottleneck that impedes the development and deployment of autonomous vehicles is the prohibitively high economic and time costs required to validate their safety in a naturalistic driving environment, owing to the rarity of safety-critic...
How Do Autonomous Vehicles Decide?
Sensors (Basel, Switzerland)
Dec 28, 2022
The advancement in sensor technologies, mobile network technologies, and artificial intelligence has pushed the boundaries of different verticals, e.g., eHealth and autonomous driving. Statistics show that more than one million people are killed in t...
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