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Found 11 papers, 1 papers with code
An Overview of Automated Vehicle Platooning Strategies
Automated vehicle (AV) platooning has the potential to improve the safety, operational, and energy efficiency of surface transportation systems by limiting or eliminating human involvement in the driving tasks.
Development and Evaluation of Ensemble Learning-based Environmental Methane Detection and Intensity Prediction Models
The environmental impacts of global warming driven by methane (CH4) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH4.
A Hybrid Defense Method against Adversarial Attacks on Traffic Sign Classifiers in Autonomous Vehicles
Moreover, the hybrid defense method, presented in this study, improves the accuracy for traffic sign classification compared to the traditional defense methods (i. e., JPEG filtering, feature squeezing, binary filtering, and random filtering) up to 6%, 50%, and 55% for FGSM, MIM, and PGD attacks, respectively.
Hybrid Quantum-Classical Neural Network for Cloud-supported In-Vehicle Cyberattack Detection
A classical computer works with ones and zeros, whereas a quantum computer uses ones, zeros, and superpositions of ones and zeros, which enables quantum computers to perform a vast number of calculations simultaneously compared to classical computers.
Efficacy of Statistical and Artificial Intelligence-based False Information Cyberattack Detection Models for Connected Vehicles
Change point models, can be used for real-time anomaly detection caused by the false information attack.
Hybrid Quantum-Classical Neural Network for Incident Detection
The incident detection performance of the hybrid model is evaluated against baseline classical ML models.
Hybrid Classical-Quantum Deep Learning Models for Autonomous Vehicle Traffic Image Classification Under Adversarial Attack
To make classification models resilient against adversarial attacks, we used a hybrid deep-learning model with both the quantum and classical layers.
Is Third-Party Provided Travel Time Helpful to Estimate Freeway Performance Measures?
Using a simulated I-210 model, the overall framework using multiple data sources is evaluated, and compared with the traditional point detector-based estimation method.
Connected Vehicle Application Development Platform (CVDeP) for Edge-centric Cyber-Physical Systems
Connected vehicle (CV) application developers need a development platform to build, test and debug CV applications, such as safety, mobility, and environmental applications, in an edge-centric Cyber-Physical Systems.
Networking and Internet Architecture
Development and Evaluation of Recurrent Neural Network based Models for Hourly Traffic Volume and AADT Prediction
The analysis indicates that the LSTM model performs better than simple RNN and GRU models, and imputation performs better than masking to predict future traffic volume.
Development of Statewide AADT Estimation Model from Short-Term Counts: A Comparative Study for South Carolina
SVR models are validated for each roadway functional class using the 2016 ATR data and selected short-term count data collected by the South Carolina Department of Transportation (SCDOT).
