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06/13/2023
Using Collision Momentum in Deep Reinforcement Learning Based Adversarial Pedestrian Modeling
Recent research in pedestrian simulation often aims to develop realistic...
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02/17/2022
A Formal Safety Characterization of Advanced Driver Assist Systems in the Car-Following Regime with Scenario-Sampling
The capability to follow a lead-vehicle and avoid rear-end collisions is...
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11/15/2021
A Finite-Sampling, Operational Domain Specific, and Provably Unbiased Connected and Automated Vehicle Safety Metric
A connected and automated vehicle safety metric determines the performan...
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10/05/2021
A Formal Characterization of Black-Box System Safety Performance with Scenario Sampling
A typical scenario-based evaluation framework seeks to characterize a bl...
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07/06/2021
Pedestrian Emergence Estimation and Occlusion-Aware Risk Assessment for Urban Autonomous Driving
Avoiding unseen or partially occluded vulnerable road users (VRUs) is a ...
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04/19/2021
Towards Guaranteed Safety Assurance of Automated Driving Systems with Scenario Sampling: An Invariant Set Perspective (Extended Version)
How many scenarios are sufficient to validate the safe Operational Desig...
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04/12/2021
Predicting Pedestrian Crossing Intention with Feature Fusion and Spatio-Temporal Attention
Predicting vulnerable road user behavior is an essential prerequisite fo...
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09/25/2020
A Modeled Approach for Online Adversarial Test of Operational Vehicle Safety
The scenario-based testing of operational vehicle safety presents a set ...
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05/30/2020
Optical Flow based Visual Potential Field for Autonomous Driving
Monocular vision-based navigation for automated driving is a challenging...
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05/15/2020
A Multi-State Social Force Based Framework for Vehicle-Pedestrian Interaction in Uncontrolled Pedestrian Crossing Scenarios
Vehicle-pedestrian interaction (VPI) is one of the most challenging task...
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02/02/2020
Integrating Deep Reinforcement Learning with Model-based Path Planners for Automated Driving
Automated driving in urban settings is challenging chiefly due to the in...
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02/01/2019
