article-journal

Measuring and Understanding Trust in Motion: Behavioral Archetypes in Human-Automated Guided Vehicle Interactions
A virtual manufacturing study compares behavioral patterns and subjective trust ratings during interactions with automated guided …
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Coding Robots for Empathy: Teacher Candidates Learning to Teach STEAM Integration in Communities of Practice
This study examines a community-partnered teacher education course in which elementary teacher candidates design and facilitate …
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A Systematic Review of Human-in-the-Loop Adaptive Systems: Design, Implications, and Future Directions
Using the PRISMA methodology, this systematic review synthesizes 34 empirical studies of adaptive systems that respond to human states. …
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TARS: Trust-Aware Reward Shaping for Vehicle Lane Change Automation
This study introduces Trust-Aware Reward Shaping (TARS), an interactive reinforcement learning method that uses real-time trust as an …
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An Inverse Reinforcement Learning Approach for Customizing Automated Lane Change Systems
Vehicle automation seeks to enhance road safety and improve the driving experience. However, a standard system does not account for …
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A Predictive Analytics Tool to Provide Visibility Into Completion of Work Orders in Supply Chain Systems
In current supply chain operations, original equipment manufacturers (OEMs) procure parts from hundreds of globally distributed …
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Predicting Interstate Motor Carrier Crash Rate Level using Classification M odels
Ensuring safe operations of large commercial vehicles (motor carriers) remains an important challenge, particularly in the United …
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Auction Bidding Methods for Multi-Agent Consensus Optimization in Supply-Demand Networks
Multiagent systems are characterized by decentralized decision-making by the (semi)autonomous agents and localized communication or …
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