2022 – Page 2 – Smart Transport Safety Research Lab

Transferability of multivariate extreme value models for safety assessment by applying artificial intelligence-based video analytics.

A comprehensive analysis on the effects of signal strategies, intersection geometry, and traffic operation factors on right-turn crashes at signalised intersections : An application of hierarchical crash frequency model.

STATER : Slit-Based Trajectory Reconstruction for Dense Urban Network With Overlapping Bluetooth Scanning Zones.

A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environment.

Influence of segmentation approaches on the before-after evaluation of engineering treatments : A hypothetical treatment approach.

Analyzing factors and interaction terms affecting urban fatal crash types based on a hybrid framework of econometric model and machine learning approaches.

Bi-level clustering of vehicle trajectories for path choice set and its nested structure identification.

Predicting and explaining lane-changing behaviour using machine learning : A comparative study.

Modeling endogeneity between motorcyclist injury severity and at-fault status by applying a Bayesian simultaneous random-parameters model with a recursive structure.

A hybrid modelling framework of machine learning and extreme value theory for crash risk estimation using traffic conflicts.

1
2
3