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(1 - 13 of 13)
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How predictable are macroscopic traffic states: a perspective of uncertainty quantification
Evaluating the safety and efficiency impacts of forced lane change with negative gaps based on empirical vehicle trajectories
How Far Ahead Should Autonomous Vehicles Start Resolving Predicted Conflicts? Exploring Uncertainty-Based Safety-Efficiency Trade-Off
Unravelling uncertainty in trajectory prediction using a non-parametric approach
Modeling the impact of lane-changing's anticipation on car-following behavior
Analysis of Stochasticity and Heterogeneity of Car-Following Behavior Based on Data-Driven Modeling
Large Car-following Data Based on Lyft level-5 Open Dataset: Following Autonomous Vehicles vs. Human-driven Vehicles
How Gaps are Created during Anticipation of Lane Changes
Estimate the limit of predictability in short-term traffic forecasting: An entropy-based approach
Multistep traffic forecasting by dynamic graph convolution: Interpretations of real-time spatial correlations
Dynamic Graph Filters Networks: A Gray-box Model for Multistep Traffic Forecasting
Discretionary lane-changing behavior: empirical validation for one realistic rule-based model
Macroscopic travel time reliability diagrams for freeway networks
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