[HTML][HTML] Leveraging reinforcement learning for dynamic traffic control: A survey and challenges for field implementation
In recent years, the advancement of artificial intelligence techniques has led to significant
interest in reinforcement learning (RL) within the traffic and transportation community …
interest in reinforcement learning (RL) within the traffic and transportation community …
Merging control strategies of connected and autonomous vehicles at freeway on-ramps: A comprehensive review
Purpose-On-ramp merging areas are typical bottlenecks in the freeway network since
merging on-ramp vehicles may cause intensive disturbances on the mainline traffic flow and …
merging on-ramp vehicles may cause intensive disturbances on the mainline traffic flow and …
Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform
The vehicle dispatching system is one of the most critical problems in online ride-hailing
platforms, which requires adapting the operation and management strategy to the dynamics …
platforms, which requires adapting the operation and management strategy to the dynamics …
Cooperative incident management in mixed traffic of CAVs and human-driven vehicles
Traffic incident management in metropolitan areas is crucial for the recovery of road systems
from accidents as well as the mobility and safety of the community. With the continuous …
from accidents as well as the mobility and safety of the community. With the continuous …
Deep adaptive control: Deep reinforcement learning-based adaptive vehicle trajectory control algorithms for different risk levels
In this study, we explore the problem of adaptive vehicle trajectory control for different risk
levels. Firstly, we introduce a sliding window-based car-following scenario extraction …
levels. Firstly, we introduce a sliding window-based car-following scenario extraction …
How generative adversarial networks promote the development of intelligent transportation systems: A survey
In current years, the improvement of deep learning has brought about tremendous changes:
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …
Intersection control with connected and automated vehicles: A review
Purpose-This paper aims to review the studies on intersection control with connected and
automated vehicles (CAVs). Design/methodology/approach-The most seminal and recent …
automated vehicles (CAVs). Design/methodology/approach-The most seminal and recent …
[HTML][HTML] GOPS: A general optimal control problem solver for autonomous driving and industrial control applications
Solving optimal control problems serves as the basic demand of industrial control tasks.
Existing methods like model predictive control often suffer from heavy online computational …
Existing methods like model predictive control often suffer from heavy online computational …
[HTML][HTML] Demand management for smart transportation: A review
The current revolutions of automation, electrification, and sharing are reshaping the way we
travel, with broad implications for future mobility management. While much uncertainty …
travel, with broad implications for future mobility management. While much uncertainty …
Multi-agent DRL-based lane change with right-of-way collaboration awareness
Lane change is a common-yet-challenging driving behavior for automated vehicles. To
improve the safety and efficiency of automated vehicles, researchers have proposed various …
improve the safety and efficiency of automated vehicles, researchers have proposed various …