Rule-based safety-critical control design using control barrier functions with application to autonomous lane change
This paper develops a new control design for guaranteeing a vehicle's safety during lane
change maneuvers in a complex traffic environment. The proposed method uses a finite …
change maneuvers in a complex traffic environment. The proposed method uses a finite …
An enabling trajectory planning scheme for lane change collision avoidance on highways
This paper presents a hierarchical three-layer trajectory planning framework to realize real-
time collision avoidance under complex driving conditions. This is mainly ascribed to the …
time collision avoidance under complex driving conditions. This is mainly ascribed to the …
Uncertainty-aware model-based offline reinforcement learning for automated driving
Offline reinforcement learning (RL) provides a framework for learning decision-making from
offline data and therefore constitutes a promising approach for real-world applications such …
offline data and therefore constitutes a promising approach for real-world applications such …
Analyzing the suitability of cost functions for explaining and imitating human driving behavior based on inverse reinforcement learning
Autonomous vehicles are sharing the road with human drivers. In order to facilitate
interactive driving and cooperative behavior in dense traffic, a thorough understanding and …
interactive driving and cooperative behavior in dense traffic, a thorough understanding and …
Autonomous racing with multiple vehicles using a parallelized optimization with safety guarantee using control barrier functions
This paper presents a novel planning and control strategy for competing with multiple
vehicles in a car racing scenario. The proposed racing strategy switches between two …
vehicles in a car racing scenario. The proposed racing strategy switches between two …
Spatiotemporal learning of multivehicle interaction patterns in lane-change scenarios
Interpretation of common-yet-challenging inter-action scenarios can benefit well-founded
decisions for autonomous vehicles. Previous research achieved this using their prior …
decisions for autonomous vehicles. Previous research achieved this using their prior …
Computation of solution spaces for optimization-based trajectory planning
L Schäfer, S Manzinger, M Althoff - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The nonlinear vehicle dynamics and the non-convexity of collision avoidance constraints
pose major challenges for optimization-based trajectory planning of automated vehicles …
pose major challenges for optimization-based trajectory planning of automated vehicles …
[PDF][PDF] An Overview of Motion-Planning Algorithms for Autonomous Ground Vehicles with Various Applications
A Gautam, Y He, X Lin - … of Vehicle Dynamics, Stability, and NVH, 2024 - researchgate.net
With the rapid development and the growing deployment of autonomous ground vehicles
(AGVs) worldwide, there is an increasing need to design reliable, efficient, robust, and …
(AGVs) worldwide, there is an increasing need to design reliable, efficient, robust, and …
Spatio-Temporal Corridor-Based Motion Planning of Lane Change Maneuver for Autonomous Driving in Multi-Vehicle Traffic
This paper presents a methodology of lane change motion planning based on spatio-
temporal corridor for autonomous driving in multi-vehicle traffic environments. The spatio …
temporal corridor for autonomous driving in multi-vehicle traffic environments. The spatio …
[图书][B] Challenges of control barrier functions: Optimization, control, planning, and navigation
J Zeng - 2022 - search.proquest.com
Challenges of Control Barrier Functions: Optimization, Control, Planning, and Navigation by Jun
Zeng A dissertation submitted in Page 1 Challenges of Control Barrier Functions: Optimization …
Zeng A dissertation submitted in Page 1 Challenges of Control Barrier Functions: Optimization …