Behavior and interaction-aware motion planning for autonomous driving vehicles based on hierarchical intention and motion prediction
Safe motion planning in complex and interactive environments is one of the major
challenges for developing autonomous vehicles. In this paper, we propose an interaction …
challenges for developing autonomous vehicles. In this paper, we propose an interaction …
Conditional predictive behavior planning with inverse reinforcement learning for human-like autonomous driving
Making safe and human-like decisions is an essential capability of autonomous driving
systems, and learning-based behavior planning presents a promising pathway toward …
systems, and learning-based behavior planning presents a promising pathway toward …
[HTML][HTML] A hybrid motion planning framework for autonomous driving in mixed traffic flow
As a core part of an autonomous driving system, motion planning plays an important role in
safe driving. However, traditional model-and rule-based methods lack the ability to learn …
safe driving. However, traditional model-and rule-based methods lack the ability to learn …
An automatic driving trajectory planning approach in complex traffic scenarios based on integrated driver style inference and deep reinforcement learning
Y Liu, S Diao - PLoS one, 2024 - journals.plos.org
As autonomous driving technology continues to advance and gradually become a reality,
ensuring the safety of autonomous driving in complex traffic scenarios has become a key …
ensuring the safety of autonomous driving in complex traffic scenarios has become a key …
Differentiable integrated motion prediction and planning with learnable cost function for autonomous driving
Predicting the future states of surrounding traffic participants and planning a safe, smooth,
and socially compliant trajectory accordingly are crucial for autonomous vehicles (AVs) …
and socially compliant trajectory accordingly are crucial for autonomous vehicles (AVs) …
Teaching Autonomous Vehicles to Express Interaction Intent during Unprotected Left Turns: A Human-Driving-Prior-Based Trajectory Planning Approach
With the integration of Autonomous Vehicles (AVs) into our transportation systems, their
harmonious coexistence with Human-driven Vehicles (HVs) in mixed traffic settings …
harmonious coexistence with Human-driven Vehicles (HVs) in mixed traffic settings …
Multimodal vehicular trajectory prediction with inverse reinforcement learning and risk aversion at urban unsignalized intersections
Understanding human drivers' intentions and predicting their future motions are significant to
connected and autonomous vehicles and traffic safety and surveillance systems. Predicting …
connected and autonomous vehicles and traffic safety and surveillance systems. Predicting …
Interaction-Aware Planning With Deep Inverse Reinforcement Learning for Human-Like Autonomous Driving in Merge Scenarios
J Nan, W Deng, R Zhang, Y Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Merge scenarios on highway are often challenging for autonomous driving, due to its lack of
sufficient tacit understanding on and subtle interaction with human drivers in the traffic flow …
sufficient tacit understanding on and subtle interaction with human drivers in the traffic flow …
Reinforcement learning based negotiation-aware motion planning of autonomous vehicles
Z Wang, Y Zhuang, Q Gu, D Chen… - 2021 IEEE/RSJ …, 2021 - ieeexplore.ieee.org
For autonomous vehicles integrating onto road-ways with human traffic participants, it
requires understanding and adapting to the participants' intention by responding in …
requires understanding and adapting to the participants' intention by responding in …
Learning interaction-aware guidance policies for motion planning in dense traffic scenarios
B Brito, A Agarwal, J Alonso-Mora - arXiv preprint arXiv:2107.04538, 2021 - arxiv.org
Autonomous navigation in dense traffic scenarios remains challenging for autonomous
vehicles (AVs) because the intentions of other drivers are not directly observable and AVs …
vehicles (AVs) because the intentions of other drivers are not directly observable and AVs …
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