Decision-making and planning method for autonomous vehicles based on motivation and risk assessment
Y Wang, C Wang, W Zhao, C Xu - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In order to improve the real-time and computational efficiency of autonomous vehicles'
decision-making process, this paper draws on the decision-making behavior of human …
decision-making process, this paper draws on the decision-making behavior of human …
Joint multi-policy behavior estimation and receding-horizon trajectory planning for automated urban driving
B Zhou, W Schwarting, D Rus… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
When driving in urban environments, an autonomous vehicle must account for the
interaction with other traffic participants. It must reason about their future behavior, how its …
interaction with other traffic participants. It must reason about their future behavior, how its …
Enable faster and smoother spatio-temporal trajectory planning for autonomous vehicles in constrained dynamic environment
Trajectory planning is of vital importance to decision-making for autonomous vehicles.
Currently, there are three popular classes of cost-based trajectory planning methods …
Currently, there are three popular classes of cost-based trajectory planning methods …
Adaptive potential field-based path planning for complex autonomous driving scenarios
An adaptive potential field is designed to adapt the acceleration/deceleration and mass of
the obstacle. The potential fields are established in a transformed road coordinate system to …
the obstacle. The potential fields are established in a transformed road coordinate system to …
Multi-agent driving behavior prediction across different scenarios with self-supervised domain knowledge
How to make precise multi-agent trajectory prediction is a crucial problem in the context of
autonomous driving. It is significant to have the ability to predict surrounding road …
autonomous driving. It is significant to have the ability to predict surrounding road …
Driving environment uncertainty-aware motion planning for autonomous vehicles
Autonomous vehicles require safe motion planning in uncertain environments, which are
largely caused by surrounding vehicles. In this paper, a driving environment uncertainty …
largely caused by surrounding vehicles. In this paper, a driving environment uncertainty …
Dual transformer based prediction for lane change intentions and trajectories in mixed traffic environment
In a mixed traffic environment of human and autonomous driving, it is crucial for an
autonomous vehicle to predict the lane change intentions and trajectories of vehicles that …
autonomous vehicle to predict the lane change intentions and trajectories of vehicles that …
Safety-assured speculative planning with adaptive prediction
Recently significant progress has been made in vehicle prediction and planning algorithms
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …
Prediction failure risk-aware decision-making for autonomous vehicles on signalized intersections
Motion prediction modules are crucial for autonomous vehicles to forecast the future
behavior of surrounding road users. Failures in prediction modules can mislead a …
behavior of surrounding road users. Failures in prediction modules can mislead a …
Multi-modal trajectory prediction for autonomous driving with semantic map and dynamic graph attention network
B Dong, H Liu, Y Bai, J Lin, Z Xu, X Xu… - arXiv preprint arXiv …, 2021 - arxiv.org
Predicting future trajectories of surrounding obstacles is a crucial task for autonomous
driving cars to achieve a high degree of road safety. There are several challenges in …
driving cars to achieve a high degree of road safety. There are several challenges in …