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Found 9 papers, 1 papers with code
Optimal Sequencing and Motion Control in a Roundabout with Safety Guarantees
This paper develops a controller for Connected and Automated Vehicles (CAVs) traversing a single-lane roundabout.
Scaling up the Optimal Safe Control of Connected and Automated Vehicles to a Traffic Network: A Hierarchical Framework of Modular Control Zones
We consider the problem of scaling up optimal and safe controllers for Connected and Automated Vehicles (CAVs) from a single Control Zone (CZ) around a traffic conflict area to an entire network.
Feasibility Guaranteed Traffic Merging Control Using Control Barrier Functions
We consider the merging control problem for Connected and Automated Vehicles (CAVs) aiming to jointly minimize travel time and energy consumption while providing speed-dependent safety guarantees and satisfying velocity and acceleration constraints.
Decentralized Time and Energy-Optimal Control of Connected and Automated Vehicles in a Roundabout
The paper considers the problem of controlling Connected and Automated Vehicles (CAVs) traveling through a three-entry roundabout so as to jointly minimize both the travel time and the energy consumption while providing speed-dependent safety guarantees, as well as satisfying velocity and acceleration constraints.
Adaptive Adversarial Logits Pairing
Specifically, AALP consists of an adaptive feature optimization module with Guided Dropout to systematically pursue fewer high-contribution features, and an adaptive sample weighting module by setting sample-specific training weights to balance between logits pairing loss and classification loss.
Butterfly Detection and Classification Based on Integrated YOLO Algorithm
Insects are abundant species on the earth, and the task of identification and identification of insects is complex and arduous.
blessing in disguise: Designing Robust Turing Test by Employing Algorithm Unrobustness
Turing test was originally proposed to examine whether machine's behavior is indistinguishable from a human.
Attention, Please! Adversarial Defense via Activation Rectification and Preservation
This study provides a new understanding of the adversarial attack problem by examining the correlation between adversarial attack and visual attention change.
Deep neural network based i-vector mapping for speaker verification using short utterances
Experimental results using the NIST SRE 2010 dataset show that both methods provide significant improvement and result in a max of 28. 43% relative improvement in Equal Error Rates from a baseline system, when using deep encoder with residual blocks and adding an additional phoneme vector.
