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Found 26 papers, 3 papers with code
Why Studying Cut-ins? Comparing Cut-ins and Other Lane Changes Based on Naturalistic Driving Data
In this paper, we explore to compare driving characteristics of cut-ins and other lane changes based on naturalistic driving data.
On Decidability of Existence of Fortified Supervisors Against Covert Actuator Attackers
We also discuss how to extend the decidability result to the case against the worst-case attacker.
STGIN: A Spatial Temporal Graph-Informer Network for Long Sequence Traffic Speed Forecasting
Accurate long series forecasting of traffic information is critical for the development of intelligent traffic systems.
Dense-TNT: Efficient Vehicle Type Classification Neural Network Using Satellite Imagery
Accurate vehicle type classification serves a significant role in the intelligent transportation system.
A SUMO Framework for Deep Reinforcement Learning Experiments Solving Electric Vehicle Charging Dispatching Problem
To better serve further research on various related Deep Reinforcment Learning (DRL) EV dispatching algorithms, an efficient simulation environment is necessary to ensure success.
AST-GIN: Attribute-Augmented Spatial-Temporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting
Electric Vehicle (EV) charging demand and charging station availability forecasting is one of the challenges in the intelligent transportation system.
Distributed Observers-based Cooperative Platooning Tracking Control and Intermittent Optimization for Connected Automated Vehicles with Unknown Jerk Dynamics
Then, a novel distributed platooning tracking control protocol is proposed to construct the cooperative tracking controllers under identical inter-vehicle constraints, which can ensure a desired safety distance among the CAVs and allow each follower CAV to track their leader CAV by using only local information interaction.
Distributed Dynamic Platoons Control and Junction Crossing Optimization for Mixed Traffic Flows in Smart Cities- Part I. Fundamentals, Theoretical and Automatic Decision Framework
The goal of this two-part article is to provide an automatic decision framework to ensure the safe and efficient cruising and crossing junctions with multiple dynamic and resilient platoons CAVs, while against the social driving behaviors(SDBs) of the HDVs considered as surrounding vehicles(SVs) and unknown traffic lights connected by Cellular-Vehicle-to-X (C-V2X) infrastructure.
Distributed Dynamic Platoons Control and Junction Crossing Optimization for Mixed Traffic Flow in Smart Cities- Part II. Stability, Optimization, and Performance Analysis
In part II, we present a fully distributed nonlinear variable time headway space strategy to ensure the subsequent safe cruising and junction crossing, where the cooperative perception of multiple neighbors stimuli and the cooperative tracking of the follower connected automated vehicles(CAVs) to the leader CAV are developed, which will result in a heterogeneous traffic flow dynamic.
Distributed Cooperative Control and Optimization of Connected Automated Vehicles Platoon Against Cut-in Behaviors of Social Drivers
When the HDVs approach the communication range of the platoon, in the prediction stage, the trajectories of the HDVs as the target vehicles will be estimated and the reference trajectory planning for the leader CAV and the cooperative controller design for the follower CAVs will be respectively activated by using C-V2X infrastructure.
Supervisor Obfuscation Against Covert Actuator Attackers
This work investigates the problem of synthesizing obfuscated supervisors against covert actuator attackers.
Interpretable Fault Diagnosis of Rolling Element Bearings with Temporal Logic Neural Network
Machine learning-based methods have achieved successful applications in machinery fault diagnosis.
Synthesis of the Supremal Covert Attacker Against Unknown Supervisors by Using Observations
In this paper, we consider the problem of synthesizing the supremal covert damage-reachable attacker, in the setup where the model of the supervisor is unknown to the adversary but the adversary has recorded a (prefix-closed) finite set of observations of the runs of the closed-loop system.
Identification of System Vulnerability under a Smart Sensor Attack via Attack Model Reduction
In this work, we investigate how to make use of model reduction techniques to identify the vulnerability of a closed-loop system, consisting of a plant and a supervisor, that might invite attacks.
Nash equilibrium of multi-agent graphical game with a privacy information encrypted learning algorithm
With the secure hierarchical structure, the relationship between the secure consensus problem and global Nash equilibrium is discussed under potential packet loss attacks, and the necessary and sufficient condition for the existence of global Nash equilibrium is provided regarding the soft-constrained graphical game.
Retrieval & Interaction Machine for Tabular Data Prediction
Prediction over tabular data is an essential task in many data science applications such as recommender systems, online advertising, medical treatment, etc.
Synthesis of Maximally Permissive Covert Attackers Against Unknown Supervisors by Using Observations
In this paper, we consider the problem of synthesis of maximally permissive covert damage-reachable attackers in the setup where the model of the supervisor is unknown to the adversary but the adversary has recorded a (prefix-closed) finite set of observations of the runs of the closed-loop system.
AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction
The field-wise transfer policy decides how the pre-trained embedding representations are frozen or fine-tuned based on the given instance from the target domain.
Dual Graph enhanced Embedding Neural Network for CTR Prediction
To solve these problems, we propose a novel module named Dual Graph enhanced Embedding, which is compatible with various CTR prediction models to alleviate these two problems.
Optimal Estimator Design and Properties Analysis for Interconnected Systems with Asymmetric Information Structure
We found that there exists a critical probability such that the EEC is bounded if the delay probability is below the critical probability.
Privacy-Preserving Co-synthesis Against Sensor-Actuator Eavesdropping Intruder
Our approach is to model the co-synthesis problem as a distributed supervisor synthesis problem in the Ramadge-Wonham supervisory control framework, and we propose an incremental synthesis heuristic to incrementally synthesize a dynamic mask, an edit function, and a supervisor, which consists of three steps: 1) we first synthesize an ensemble ME of dynamic mask and edit function to ensure the opacity and the covertness against a sensor eavesdropping but command non-eavesdropping intruder, and marker-reachability; 2) we then decompose ME into a dynamic mask and an edit function by using a constraint-based approach, with the help of a Boolean satisfiability (SAT) solver; 3) finally, we synthesize a supervisor such that opacity and covertness can be ensured against the sensor-actuator eavesdropping intruder, and at the same time safety and nonblockingness requirement can be ensured.
Distributed Eco-Driving Algorithm of Vehicle Platoon Using Traffic Light and Road Slope Information
This paper investigates the problem of ecological driving (eco-driving) of vehicle platoons.
Privacy-Preserving Supervisory Control of Discrete-Event Systems via Co-Synthesis of Edit Function and Supervisor for Opacity Enforcement and Requirement Satisfaction
We focus on the class of edit functions that satisfy the following properties: 1) the observation capability of the edit function in general can be different from those of the supervisor and the intruder; 2) the edit function can implement insertion, deletion, and replacement operations; 3) the edit function performs bounded edit operations, i. e., the length of each string output of the edit function is upper bounded by a given constant.
Networked Supervisor Synthesis Against Lossy Channels with Bounded Network Delays as Non-Networked Synthesis
In this work, we study the problem of supervisory control of networked discrete event systems.
Observation-Assisted Heuristic Synthesis of Covert Attackers Against Unknown Supervisors
In this work, we address the problem of synthesis of covert attackers in the setup where the model of the plant is available, but the model of the supervisor is unknown, to the adversary.
Automatic Generation of Optimal Reductions of Distributions
A (partial) solution to this problem is provided, which consists of 1) an incremental algorithm for the production of candidate reductions and 2) a reduction validation procedure.
Systems and Control Formal Languages and Automata Theory Optimization and Control
