Social interactions for autonomous driving: A review and perspectives
No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …
their goals in social traffic scenes. A rational human driver can interact with other road users …
A review of HMM-based approaches of driving behaviors recognition and prediction
Current research and development in recognizing and predicting driving behaviors plays an
important role in the development of Advanced Driver Assistance Systems (ADAS). For this …
important role in the development of Advanced Driver Assistance Systems (ADAS). For this …
The ind dataset: A drone dataset of naturalistic road user trajectories at german intersections
Automated vehicles rely heavily on data-driven methods, especially for complex urban
environments. Large datasets of real world measurement data in the form of road user …
environments. Large datasets of real world measurement data in the form of road user …
TriPField: A 3D potential field model and its applications to local path planning of autonomous vehicles
Potential fields have been integrated with local path-planning algorithms for autonomous
vehicles (AVs) to tackle challenging scenarios with dense and dynamic obstacles. Most …
vehicles (AVs) to tackle challenging scenarios with dense and dynamic obstacles. Most …
Modeling driver's evasive behavior during safety–critical lane changes: Two-dimensional time-to-collision and deep reinforcement learning
Lane changes are complex driving behaviors and frequently involve safety–critical
situations. This study aims to develop a lane-change-related evasive behavior model, which …
situations. This study aims to develop a lane-change-related evasive behavior model, which …
Transferable and adaptable driving behavior prediction
While autonomous vehicles still struggle to solve challenging situations during on-road
driving, humans have long mastered the essence of driving with efficient, transferable, and …
driving, humans have long mastered the essence of driving with efficient, transferable, and …
Interactive trajectory prediction using a driving risk map-integrated deep learning method for surrounding vehicles on highways
X Liu, Y Wang, K Jiang, Z Zhou… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Accurate trajectory prediction of surrounding vehicles is vital for automated vehicles to
achieve high-level driving safety in complex situations. However, most state-of-the-art …
achieve high-level driving safety in complex situations. However, most state-of-the-art …
Bayesian calibration of the intelligent driver model
Accurate calibration of car-following models is essential for understanding human driving
behaviors and implementing high-fidelity microscopic simulations. This work proposes a …
behaviors and implementing high-fidelity microscopic simulations. This work proposes a …
Identifying dynamic interaction patterns in mandatory and discretionary lane changes using graph structure
A quantitative understanding of dynamic lane‐changing interaction patterns is
indispensable for improving the decision‐making of autonomous vehicles (AVs), especially …
indispensable for improving the decision‐making of autonomous vehicles (AVs), especially …
Improvement of maneuverability within a multiagent fuzzy transportation system with the use of parallel biobjective real-coded genetic algorithm
AS Akopov, LA Beklaryan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Over the past two decades, several simulation-based approaches have been developed to
seek optimal solutions in complex multiagent systems (MASs). One example of these …
seek optimal solutions in complex multiagent systems (MASs). One example of these …