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Found 14 papers, 2 papers with code
Traffic State Estimation and Uncertainty Quantification at Signalized Intersections with Low Penetration Rate Vehicle Trajectory Data
This paper studies the traffic state estimation problem at signalized intersections with low penetration rate vehicle trajectory data.
Evaluating Roadside Perception for Autonomous Vehicles: Insights from Field Testing
This paper introduces a comprehensive evaluation methodology specifically designed to assess the performance of roadside perception systems.
MSight: An Edge-Cloud Infrastructure-based Perception System for Connected Automated Vehicles
As vehicular communication and networking technologies continue to advance, infrastructure-based roadside perception emerges as a pivotal tool for connected automated vehicle (CAV) applications.
Robust Roadside Perception: an Automated Data Synthesis Pipeline Minimizing Human Annotation
Our approach was rigorously tested at two key intersections in Michigan, USA: the Mcity intersection and the State St./Ellsworth Rd roundabout.
ROCO: A Roundabout Traffic Conflict Dataset
With the traffic conflict data collected, we discover that failure to yield to circulating vehicles when entering the roundabout is the largest contributing reason for traffic conflicts.
Adaptive Safety Evaluation for Connected and Automated Vehicles with Sparse Control Variates
One prevailing way is to design testing scenarios using prior knowledge of CAVs, test CAVs in these scenarios, and then evaluate their safety performances.
Adaptive Testing for Connected and Automated Vehicles with Sparse Control Variates in Overtaking Scenarios
To validate the proposed method, the high-dimensional overtaking scenarios are investigated, and the results demonstrate that our approach can further accelerate the evaluation process by about 30 times.
Real-time Full-stack Traffic Scene Perception for Autonomous Driving with Roadside Cameras
We propose a novel and pragmatic framework for traffic scene perception with roadside cameras.
A probabilistic model for missing traffic volume reconstruction based on data fusion
Moreover, for the low coverage problem, which cannot be handled by most existing methods, the proposed model can also achieve high accuracy.
Corner Case Generation and Analysis for Safety Assessment of Autonomous Vehicles
In this paper, a unified framework is proposed to generate corner cases for the decision-making systems.
A Learning-based Stochastic Driving Model for Autonomous Vehicle Testing
However, pre-determined BV trajectories can not react to the AV's maneuvers, and deterministic models are different from real human drivers due to the lack of stochastic components and errors.
Distributionally Consistent Simulation of Naturalistic Driving Environment for Autonomous Vehicle Testing
Microscopic traffic simulation provides a controllable, repeatable, and efficient testing environment for autonomous vehicles (AVs).
Testing Scenario Library Generation for Connected and Automated Vehicles: An Adaptive Framework
A customized testing scenario library for a specific CAV model is generated through an adaptive process.
Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studies
In Part I of this study, a general methodology for TSLG is proposed, and theoretical properties are investigated regarding the accuracy and efficiency of CAV evaluation.
