A survey of autonomous driving frameworks and simulators
Since autonomous driving (AD) is one of the most critical problems in the automobile
industry, it has garnered the interest of many academics in recent years. An AD framework or …
industry, it has garnered the interest of many academics in recent years. An AD framework or …
Event-triggered based trajectory tracking control of under-actuated unmanned surface vehicle with state and input quantization
This paper is dedicated to the trajectory tracking control of under-actuated unmanned
surface vessel (USV) with state and input quantization. In terms of kinematics, a distributed …
surface vessel (USV) with state and input quantization. In terms of kinematics, a distributed …
Event-triggered model predictive control with deep reinforcement learning for autonomous driving
Event-triggered model predictive control (eMPC) is a popular optimal control method with an
aim to alleviate the computation and/or communication burden of MPC. However, it …
aim to alleviate the computation and/or communication burden of MPC. However, it …
Development of a four-wheel steering scale vehicle for research and education on autonomous vehicle motion control
Autonomous vehicle motion control development requires testing and evaluation at all
stages of the process. The development phase involving the instrumentation and operation …
stages of the process. The development phase involving the instrumentation and operation …
[HTML][HTML] A Review on Reinforcement Learning-based Highway Autonomous Vehicle Control
Autonomous driving is an active area of research in artificial intelligence and robotics.
Recent advances in deep reinforcement learning (DRL) show promise for training …
Recent advances in deep reinforcement learning (DRL) show promise for training …
NMPC-based integrated thermal management of battery and cabin for electric vehicles in cold weather conditions
One of the major obstacles along the way of electric vehicles'(EVs') wider global adoption is
their limited driving range. Extreme cold or hot environments can further impact the EV's …
their limited driving range. Extreme cold or hot environments can further impact the EV's …
Two-Layer MPC Architecture for Efficient Mixed-Integer-Informed Obstacle Avoidance in Real-Time
AL Gratzer, MM Broger, A Schirrer… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Safe and efficient obstacle avoidance in complex traffic situations is a major challenge for
real-time motion control of connected and automated vehicles (CAVs). Limited processing …
real-time motion control of connected and automated vehicles (CAVs). Limited processing …
D-tracking: digital twin enabled trajectory tracking system of autonomous vehicles
The precision of trajectory tracking significantly influences the driving safety of autonomous
vehicles. Therefore, it is crucial to accurately estimate and use control algorithms to reduce …
vehicles. Therefore, it is crucial to accurately estimate and use control algorithms to reduce …
Dynamic event-triggered model predictive control under channel fading and denial-of-service attacks
T Shi, P Shi, J Chambers - IEEE Transactions on Automation …, 2023 - ieeexplore.ieee.org
This article presents a model predictive control (MPC) design based on dynamic event-
triggered mechanism (DETM). In the sensor-to-controller channel, the networks are …
triggered mechanism (DETM). In the sensor-to-controller channel, the networks are …
Exploring the design of reward functions in deep reinforcement learning-based vehicle velocity control algorithms
The application of deep reinforcement learning (DRL) techniques in intelligent transportation
systems garners significant attention. In this field, reward function design is a crucial factor …
systems garners significant attention. In this field, reward function design is a crucial factor …