40 citations · 107 across the 15 of their papers we have counts for
16 papers
Using Collision Momentum in Deep Reinforcement Learning Based Adversarial Pedestrian Modeling
Dianwei Chen, Ekim Yurtsever, Keith Redmill +1
Recent research in pedestrian simulation often aims to develop realistic behaviors in various situations, but it is challenging for existing algorithms to generate behaviors that i…
A Formal Safety Characterization of Advanced Driver Assist Systems in the Car-Following Regime with Scenario-Sampling
Bowen Weng, Minghao Zhu, Keith Redmill
The capability to follow a lead-vehicle and avoid rear-end collisions is one of the most important functionalities for human drivers and various Advanced Driver Assist Systems (ADA…
A Finite-Sampling, Operational Domain Specific, and Provably Unbiased Connected and Automated Vehicle Safety Metric
Bowen Weng, Linda Capito, Umit Ozguner +1
A connected and automated vehicle safety metric determines the performance of a subject vehicle (SV) by analyzing the data involving the interactions among the SV and other dynamic…
A Formal Characterization of Black-Box System Safety Performance with Scenario Sampling
Bowen Weng, Linda Capito, Umit Ozguner +1
A typical scenario-based evaluation framework seeks to characterize a black-box system's safety performance (e.g., failure rate) through repeatedly sampling initialization configur…
Pedestrian Emergence Estimation and Occlusion-Aware Risk Assessment for Urban Autonomous Driving
Mert Koc, Ekim Yurtsever, Keith Redmill +1
Avoiding unseen or partially occluded vulnerable road users (VRUs) is a major challenge for fully autonomous driving in urban scenes. However, occlusion-aware risk assessment syste…
Towards Guaranteed Safety Assurance of Automated Driving Systems with Scenario Sampling: An Invariant Set Perspective (Extended Version)
Bowen Weng, Linda Capito, Umit Ozguner +1
How many scenarios are sufficient to validate the safe Operational Design Domain (ODD) of an Automated Driving System (ADS) equipped vehicle? Is a more significant number of sample…