Kaidi Yang
YOU?
Author Swipe
View article: Farming the Green Future economically based on Lotka-Volterra model and firefly algorithm
Farming the Green Future economically based on Lotka-Volterra model and firefly algorithm Open
With the global agricultural environment changes, agroecosystems face the challenges of inefficient resource utilization and ecological imbalance. This paper explores the relationship between agricultural activities and species dynamics by…
View article: Scalable Synthesis and Verification of String Stable Neural Certificates for Interconnected Systems
Scalable Synthesis and Verification of String Stable Neural Certificates for Interconnected Systems Open
Ensuring string stability is critical for the safety and efficiency of large-scale interconnected systems. Although learning-based controllers (e.g., those based on reinforcement learning) have demonstrated strong performance in complex co…
View article: Robust Nonlinear Data-Driven Predictive Control for Mixed Vehicle Platoons via Koopman Operator and Reachability Analysis
Robust Nonlinear Data-Driven Predictive Control for Mixed Vehicle Platoons via Koopman Operator and Reachability Analysis Open
Mixed vehicle platoons, comprising connected and automated vehicles (CAVs) and human-driven vehicles (HDVs), hold significant potential for enhancing traffic performance. However, most existing control strategies assume linear system dynam…
View article: Connected Vehicle Data-driven Robust Optimization for Traffic Signal Timing: Modeling Traffic Flow Variability and Errors
Connected Vehicle Data-driven Robust Optimization for Traffic Signal Timing: Modeling Traffic Flow Variability and Errors Open
Recent advancements in Connected Vehicle (CV) technology have prompted research on leveraging CV data for more effective traffic management. Despite the low penetration rate, such detailed CV data has demonstrated great potential in improv…
View article: Safe Reinforcement Learning-Based Eco-Driving Control for Mixed Traffic Flows With Disturbances
Safe Reinforcement Learning-Based Eco-Driving Control for Mixed Traffic Flows With Disturbances Open
This paper presents a safe learning-based eco-driving framework tailored for mixed traffic flows, which aims to optimize energy efficiency while guaranteeing safety during real-system operations. Even though reinforcement learning (RL) is …
View article: Control-Aware Trajectory Predictions for Communication-Efficient Drone Swarm Coordination in Cluttered Environments
Control-Aware Trajectory Predictions for Communication-Efficient Drone Swarm Coordination in Cluttered Environments Open
Swarms of Unmanned Aerial Vehicles (UAV) have demonstrated enormous potential in many industrial and commercial applications. However, before deploying UAVs in the real world, it is essential to ensure they can operate safely in complex en…
View article: Enhancing System-Level Safety in Mixed-Autonomy Platoon via Safe Reinforcement Learning
Enhancing System-Level Safety in Mixed-Autonomy Platoon via Safe Reinforcement Learning Open
Connected and automated vehicles (CAVs) have recently gained prominence in traffic research due to advances in communication technology and autonomous driving. Various longitudinal control strategies for CAVs have been developed to enhance…
View article: A traffic signal and loop detector dataset of an urban intersection regulated by a fully actuated signal control system
A traffic signal and loop detector dataset of an urban intersection regulated by a fully actuated signal control system Open
View article: Data-Driven Robust Optimization for Fixed-Time Traffic Signal Timing Based on Connected Vehicles
Data-Driven Robust Optimization for Fixed-Time Traffic Signal Timing Based on Connected Vehicles Open
View article: Reinforcement Learning for Autonomous Mobility-on-Demand Systems
Reinforcement Learning for Autonomous Mobility-on-Demand Systems Open
Autonomous mobility-on-demand (AMoD) systems represent a rapidly developing mode of transportation wherein travel requests are dynamically handled by a coordinated fleet of robotic, self-driving vehicles. Given a graph representation of th…
View article: Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand Open
Autonomous Mobility-on-Demand (AMoD) systems represent an attractive alternative to existing transportation paradigms, currently challenged by urbanization and increasing travel needs. By centrally controlling a fleet of self-driving vehic…
View article: Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems
Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems Open
Autonomous mobility-on-demand (AMoD) systems represent a rapidly developing mode of transportation wherein travel requests are dynamically handled by a coordinated fleet of robotic, self-driving vehicles. Given a graph representation of th…
View article: On the design of an optimal flexible bus dispatching system with modular bus units: Using the three-dimensional macroscopic fundamental diagram
On the design of an optimal flexible bus dispatching system with modular bus units: Using the three-dimensional macroscopic fundamental diagram Open
This study proposes a novel flexible bus dispatching system where a fleet of fully automated modular bus units, together with conventional buses, serves the passenger demand. These modular bus units can either operate individually or combi…
View article: Joint Optimization of Intersection Control and Trajectory Planning Accounting for Pedestrians in a Connected and Automated Vehicle Environment
Joint Optimization of Intersection Control and Trajectory Planning Accounting for Pedestrians in a Connected and Automated Vehicle Environment Open
Connected and automated vehicle (CAV) technology makes it possible to track and control the movement of vehicles, thus providing enormous potential to improve intersection operations. In this paper, we study the traffic signal control prob…
View article: Time-to-Green predictions: A framework to enhance SPaT messages using machine learning
Time-to-Green predictions: A framework to enhance SPaT messages using machine learning Open
Recently, efforts were made to standardize Signal Phase and Timing (SPaT) messages. Such messages contain the current signal phase with a prediction for the corresponding residual time for all approaches of a signalized intersection. Hence…
View article: Planning and Operations of Mixed Fleets in Mobility-on-Demand Systems
Planning and Operations of Mixed Fleets in Mobility-on-Demand Systems Open
Automated vehicles (AVs) are expected to be beneficial for Mobility-on-Demand (MoD), thanks to their ability of being globally coordinated. To facilitate the steady transition towards full autonomy, we consider the transition period of AV …
View article: Enhancement of SPaT-messages with machine learning based time-to-green predictions
Enhancement of SPaT-messages with machine learning based time-to-green predictions Open
View article: Providing public transport priority in the perimeter of urban networks: A bimodal strategy
Providing public transport priority in the perimeter of urban networks: A bimodal strategy Open
View article: An auction-based approach for prebooked urban logistics facilities
An auction-based approach for prebooked urban logistics facilities Open
View article: Queue Estimation in a Connected Vehicle Environment: A Convex Approach
Queue Estimation in a Connected Vehicle Environment: A Convex Approach Open
This paper proposes a convex optimization based algorithm for queue profile estimation in a connected vehicle environment, which can also be used for trajectory reconstruction, delay evaluation, etc. This algorithm generalizes the widely-a…
View article: Evaluating the effects of automated vehicle technology on the capacity of freeway weaving sections
Evaluating the effects of automated vehicle technology on the capacity of freeway weaving sections Open
View article: Control strategy for bi-modal highway lanes
Control strategy for bi-modal highway lanes Open
View article: Real-time urban traffic control in a connected and automated vehicle environment
Real-time urban traffic control in a connected and automated vehicle environment Open
View article: Multi-scale perimeter control approach in a connected-vehicle environment
Multi-scale perimeter control approach in a connected-vehicle environment Open
View article: A reinforcement learning based traffic signal control algorithm in a connected vehicle environment
A reinforcement learning based traffic signal control algorithm in a connected vehicle environment Open
View article: Multi-scale Perimeter Control Approach in a Connected-Vehicle Environment
Multi-scale Perimeter Control Approach in a Connected-Vehicle Environment Open
This paper proposes a novel approach to integrate optimal control of perimeter intersections (i.e. to minimize local delay) into the perimeter control scheme (i.e. to optimize traffic performance at the network level). This is a complex co…
View article: Continuous and Discrete-Time Optimal Controls for an Isolated Signalized Intersection
Continuous and Discrete-Time Optimal Controls for an Isolated Signalized Intersection Open
A classical control problem for an isolated oversaturated intersection is revisited with a focus on the optimal control policy to minimize total delay. The difference and connection between existing continuous-time planning models and rece…
View article: Research on cloud model control strategy for wind farm and energy storage system
Research on cloud model control strategy for wind farm and energy storage system Open
This paper is based on the traditional wind-storage combined power generation system.A two-dimensional cloud model is used to control the variable weight filter to analyze the relationship between filter time constant, energy storage capac…
View article: Two-level Perimeter Control Approach in a Connected-Vehicle Environment
Two-level Perimeter Control Approach in a Connected-Vehicle Environment Open
This paper proposes a novel approach to integrate optimal control of perimeter intersections (i.e. to minimize local delay) into the perimeter control scheme (i.e. to optimize traffic performance at the network level). This is a complex co…