Search Results for author:
Found 8 papers, 0 papers with code
Vehicle-group-based Crash Risk Formation and Propagation Analysis for Expressways
Several key factors contributing to crash risks were identified, including past high-risk vehicle-group states, complex vehicle behaviors, high percentage of large vehicles, frequent lane changes within a vehicle group, and specific road geometries.
Evaluation of Infrastructure-based Warning System on Driving Behaviors-A Roundabout Study
A real-world roundabout in Ann Arbor, Michigan was built in the co-simulation platform as the study area, and the merging scenarios were investigated.
An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems
Navigating automated driving systems (ADSs) through complex driving environments is difficult.
Improving Autonomous Vehicle Mapping and Navigation in Work Zones Using Crowdsourcing Vehicle Trajectories
Navigating CAVs in such areas heavily relies on how the vehicle defines drivable areas based on perception information.
IDM-Follower: A Model-Informed Deep Learning Method for Long-Sequence Car-Following Trajectory Prediction
Model-based and learning-based methods are two major types of methodologies to model car following behaviors.
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.
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.
