“Predicting Accidents in Conditional Autonomous Driving: A Multimodal Approach Integrating Human Misuse, Biometric Indicators, and Spatial Complexity” by Jang, Chang, Kim and Yoon
Conference:
Type(s):
Title:
- Predicting Accidents in Conditional Autonomous Driving: A Multimodal Approach Integrating Human Misuse, Biometric Indicators, and Spatial Complexity
Session/Category Title:
- Interactive Techniques
Presenter(s)/Author(s):
Abstract:
This study presents a multimodal framework integrating human factors(workload, situation awareness), biometrics(heart rate variability, eye-tracking), and spatial complexity to predict Level 2 autonomous driving accidents, achieving 73.7% accuracy via logistic regression, with age and workload as key predictors and elevated cognitive load in complex environments informing real-time adaptive safety interventions.
References:
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