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04/25/2022
A Hybrid Defense Method against Adversarial Attacks on Traffic Sign Classifiers in Autonomous Vehicles
Adversarial attacks can make deep neural network (DNN) models predict in...
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10/14/2021
Hybrid Quantum-Classical Neural Network for Cloud-supported In-Vehicle Cyberattack Detection
A classical computer works with ones and zeros, whereas a quantum comput...
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08/02/2021
Hybrid Quantum-Classical Neural Network for Incident Detection
The efficiency and reliability of real-time incident detection models di...
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08/02/2021
Hybrid Classical-Quantum Deep Learning Models for Autonomous Vehicle Traffic Image Classification Under Adversarial Attack
Image classification must work for autonomous vehicles (AV) operating on...
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12/24/2020
Security of Connected and Automated Vehicles
The transportation system is rapidly evolving with new connected and aut...
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08/14/2020
An Evaluation Framework of End-to-End 5G Millimeter Wave Communication for Connected Vehicle Applications
The internet-of-things (IoT) environment connects different intelligent ...
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12/29/2019
Grey Models for Short-Term Queue Length Predictions for Adaptive Traffic Signal Control
Traffic congestion at a signalized intersection greatly reduces the trav...
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10/23/2019
Development and evaluation of an open-source, machine learning-based average annual daily traffic estimation software
Traditionally, Departments of Transportation (DOTs) use the factor-based...
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06/24/2019
In-Vehicle False Information Attack Detection and Mitigation Framework using Machine Learning and Software Defined Networking
A modern vehicle contains many electronic control units (ECUs), which co...
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12/06/2017
