[HTML][HTML] Path planning algorithms in the autonomous driving system: A comprehensive review
This comprehensive review focuses on the Autonomous Driving System (ADS), which aims
to reduce human errors that are the reason for about 95% of car accidents. The ADS …
to reduce human errors that are the reason for about 95% of car accidents. The ADS …
A review of applications of artificial intelligence in heavy duty trucks
Due to the increasing use of automobiles, the transportation industry is facing challenges of
increased emissions, driver safety concerns, travel demand, etc. Hence, automotive …
increased emissions, driver safety concerns, travel demand, etc. Hence, automotive …
An integrated model for autonomous speed and lane change decision-making based on deep reinforcement learning
The implementation of autonomous driving is inseparable from developing intelligent driving
decision-making models, which are facing high scene complexity, poor decision-making …
decision-making models, which are facing high scene complexity, poor decision-making …
Safe-state enhancement method for autonomous driving via direct hierarchical reinforcement learning
Reinforcement learning (RL) has shown excellent performance in the sequential decision-
making problem, where safety in the form of state constraints is of great significance in the …
making problem, where safety in the form of state constraints is of great significance in the …
Physics-aware safety-assured design of hierarchical neural network based planner
Neural networks have shown great promises in planning, control, and general decision
making for learning-enabled cyber-physical systems (LE-CPSs), especially in improving …
making for learning-enabled cyber-physical systems (LE-CPSs), especially in improving …
Hierarchical trajectory planning for narrow-space automated parking with deep reinforcement learning: A federated learning scheme
Collision-free trajectory planning in narrow spaces has become one of the most challenging
tasks in automated parking scenarios. Previous optimization-based approaches can …
tasks in automated parking scenarios. Previous optimization-based approaches can …
Safety-driven interactive planning for neural network-based lane changing
Neural network-based driving planners have shown great promises in improving task
performance of autonomous driving. However, it is critical and yet very challenging to ensure …
performance of autonomous driving. However, it is critical and yet very challenging to ensure …
A hierarchical motion planning system for driving in changing environments: Framework, algorithms, and verifications
In this article, a hierarchical real-time motion planning system is proposed to solve complex
navigation problem in realistic dynamic traffic environments. First, a longitudinal safety …
navigation problem in realistic dynamic traffic environments. First, a longitudinal safety …
Improved hybrid A-star algorithm for path planning in autonomous parking system based on multi-stage dynamic optimization
T Meng, T Yang, J Huang, W Jin, W Zhang… - International journal of …, 2023 - Springer
The recent proliferation of intelligent technologies has promoted autonomous driving. The
autonomous parking system has become a popular feature in autonomous driving. Hybrid A …
autonomous parking system has become a popular feature in autonomous driving. Hybrid A …
A Novel Dynamic Lane‐Changing Trajectory Planning Model for Automated Vehicles Based on Reinforcement Learning
C Yu, A Ni, J Luo, J Wang, C Zhang… - Journal of advanced …, 2022 - Wiley Online Library
Lane changing behavior has a significant impact on traffic efficiency and may lead to traffic
delays or even accidents. It is important to plan a safe and efficient lane‐changing trajectory …
delays or even accidents. It is important to plan a safe and efficient lane‐changing trajectory …