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Effects of Explanation Specificity on Passengers in Autonomous Driving
In this paper, we investigate the effects of natural language explanations' specificity on passengers in autonomous driving.
A Hybrid Rule-Based and Data-Driven Approach to Driver Modeling through Particle Filtering
While the rules are governed by interpretable parameters of the driver model, these parameters are learned online from driving demonstration data using particle filtering.
Modeling Human Driving Behavior through Generative Adversarial Imitation Learning
Imitation learning is an approach for generating intelligent behavior when the cost function is unknown or difficult to specify.
Online Parameter Estimation for Human Driver Behavior Prediction
In this article, we show that online parameter estimation applied to the Intelligent Driver Model captures nuanced individual driving behavior while providing collision free trajectories.
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