A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning
This paper serves as an introduction and overview of the potentially useful models and
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
Implicit personalization in driving assistance: State-of-the-art and open issues
In recent decades, driving assistance systems have been evolving towards personalization
for adapting to different drivers. With the consideration of driving preferences and driver …
for adapting to different drivers. With the consideration of driving preferences and driver …
Decentralized structural-rnn for robot crowd navigation with deep reinforcement learning
Safe and efficient navigation through human crowds is an essential capability for mobile
robots. Previous work on robot crowd navigation assumes that the dynamics of all agents …
robots. Previous work on robot crowd navigation assumes that the dynamics of all agents …
Set-based prediction of traffic participants considering occlusions and traffic rules
M Koschi, M Althoff - IEEE Transactions on Intelligent Vehicles, 2020 - ieeexplore.ieee.org
Provably safe motion planning for automated road vehicles must ensure that planned
motions do not result in a collision with other traffic participants. This is a major challenge in …
motions do not result in a collision with other traffic participants. This is a major challenge in …
Confidence-aware motion prediction for real-time collision avoidance1
One of the most difficult challenges in robot motion planning is to account for the behavior of
other moving agents, such as humans. Commonly, practitioners employ predictive models to …
other moving agents, such as humans. Commonly, practitioners employ predictive models to …
Formal certification methods for automated vehicle safety assessment
Challenges related to automated driving are no longer focused on just the construction of
such automated vehicles (AVs) but also on assuring the safety of operation. Recent …
such automated vehicles (AVs) but also on assuring the safety of operation. Recent …
Safety assurances for human-robot interaction via confidence-aware game-theoretic human models
An outstanding challenge with safety methods for human-robot interaction is reducing their
conservatism while maintaining robustness to variations in human behavior. In this work, we …
conservatism while maintaining robustness to variations in human behavior. In this work, we …
Improved robustness and safety for autonomous vehicle control with adversarial reinforcement learning
X Ma, K Driggs-Campbell… - 2018 IEEE Intelligent …, 2018 - ieeexplore.ieee.org
To improve efficiency and reduce failures in autonomous vehicles, research has focused on
developing robust and safe learning methods that take into account disturbances in the …
developing robust and safe learning methods that take into account disturbances in the …
A taxonomy and review of algorithms for modeling and predicting human driver behavior
K Brown, K Driggs-Campbell… - arXiv preprint arXiv …, 2020 - arxiv.org
We present a review and taxonomy of 200 models from the literature on driver behavior
modeling. We begin by introducing a mathematical framework for describing the dynamics of …
modeling. We begin by introducing a mathematical framework for describing the dynamics of …
Integrating intuitive driver models in autonomous planning for interactive maneuvers
K Driggs-Campbell, V Govindarajan… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Given the current capabilities of autonomous vehicles, one can easily imagine autonomous
vehicles being released on the road in the near future. However, it can be assumed that this …
vehicles being released on the road in the near future. However, it can be assumed that this …