Search Results for author:
Found 8 papers, 4 papers with code
Enhancing Visual Perception in Novel Environments via Incremental Data Augmentation Based on Style Transfer
The deployment of autonomous agents in real-world scenarios is challenged by "unknown unknowns", i. e. novel unexpected environments not encountered during training, such as degraded signs.
Designing an Optimized Electric Vehicle Charging Station Infrastructure for Urban Area: A Case study from Indonesia
The rapid development of electric vehicle (EV) technologies promises cleaner air and more efficient transportation systems, especially for polluted and congested urban areas.
Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling
In this work, we present Deep Importance Sampling (Deep IS) framework that utilizes a deep neural network to obtain an efficient IS that is on par with the state-of-the-art, capable of reducing the required sample size 43 times smaller than the naive sampling method to achieve 10% relative error and while producing an estimate that is much less conservative.
Certifiable Deep Importance Sampling for Rare-Event Simulation of Black-Box Systems
Rare-event simulation techniques, such as importance sampling (IS), constitute powerful tools to speed up challenging estimation of rare catastrophic events.
Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems
Evaluating the reliability of intelligent physical systems against rare safety-critical events poses a huge testing burden for real-world applications.
Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field
We then use this model to reproduce the high-dimensional driving scenarios in a finitely tractable form.
Evaluation Uncertainty in Data-Driven Self-Driving Testing
These Monte Carlo samples are generated from stochastic input models constructed based on real-world data.
An Accelerated Approach to Safely and Efficiently Test Pre-Production Autonomous Vehicles on Public Streets
Various automobile and mobility companies, for instance Ford, Uber and Waymo, are currently testing their pre-produced autonomous vehicle (AV) fleets on the public roads.
