64 citations · 79 across the 6 of their papers we have counts for
6 papers
Physical Backdoor Trigger Activation of Autonomous Vehicle using Reachability Analysis
Wenqing Li, Yue Wang, Muhammad Shafique +1
Recent studies reveal that Autonomous Vehicles (AVs) can be manipulated by hidden backdoors, causing them to perform harmful actions when activated by physical triggers. However, i…
Optimal Smoothing Distribution Exploration for Backdoor Neutralization in Deep Learning-based Traffic Systems
Yue Wang, Wending Li, Michail Maniatakos +1
Deep Reinforcement Learning (DRL) enhances the efficiency of Autonomous Vehicles (AV), but also makes them susceptible to backdoor attacks that can result in traffic congestion or…
PiDAn: A Coherence Optimization Approach for Backdoor Attack Detection and Mitigation in Deep Neural Networks
Yue Wang, Wenqing Li, Esha Sarkar +3
Backdoor attacks impose a new threat in Deep Neural Networks (DNNs), where a backdoor is inserted into the neural network by poisoning the training dataset, misclassifying inputs t…
Short-Term Traffic Forecasting Using High-Resolution Traffic Data
Wenqing Li, Chuhan Yang, Saif Eddin Jabari
This paper develops a data-driven toolkit for traffic forecasting using high-resolution (a.k.a. event-based) traffic data. This is the raw data obtained from fixed sensors in urban…
Stop-and-Go: Exploring Backdoor Attacks on Deep Reinforcement Learning-based Traffic Congestion Control Systems
Yue Wang, Esha Sarkar, Wenqing Li +2
Recent work has shown that the introduction of autonomous vehicles (AVs) in traffic could help reduce traffic jams. Deep reinforcement learning methods demonstrate good performance…
Nonlinear Traffic Prediction as a Matrix Completion Problem with Ensemble Learning
Wenqing Li, Chuhan Yang, Saif Eddin Jabari
This paper addresses the problem of short-term traffic prediction for signalized traffic operations management. Specifically, we focus on predicting sensor states in high-resolutio…