activity
20182022
most citedEvaluation of the Gradient Boosting of Regression Trees Method on Estimating the Car Following Behavior

29 citations · 39 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2022

An Assessment of Safety-Based Driver Behavior Modeling in Microscopic Simulation Utilizing Real-Time Vehicle Trajectories

Awad Abdelhalim, Montasir Abbas

Accurate representation of observed driving behavior is critical for effectively evaluating safety and performance interventions in simulation modeling. In this study, we implement…

cs.CV2021

A Framework for Real-time Traffic Trajectory Tracking, Speed Estimation, and Driver Behavior Calibration at Urban Intersections Using Virtual Traffic Lanes

Awad Abdelhalim, Montasir Abbas, Bhavi Bharat Kotha +1

In a previous study, we presented VT-Lane, a three-step framework for real-time vehicle detection, tracking, and turn movement classification at urban intersections. In this study,…

cs.CY2020★ 2 cited

Vehicle Class, Speed, and Roadway Geometry Based Driver Behavior Identification and Classification

Awad Abdelhalim, Montasir Abbas

This paper focuses on the study of the impact that the class of the vehicle, leading heavy vehicles in particular, causes on the following vehicle's behavior, specifically in terms…

stat.AP2018★ 8 cited

Introducing a Cost-Effective Approach for Improving the Arterial Traffic Performance Operating Under the Semi-Actuated Coordinated Signal Control

Sina Dabiri, Kianoush Kompany, Montasir Abbas

The semi-actuated coordinated operation mode is a type of signal control where minor approaches are placed with detectors to develop actuated phasing while major movements are coor…

stat.AP2018★ 29 cited

Evaluation of the Gradient Boosting of Regression Trees Method on Estimating the Car Following Behavior

Sina Dabiri, Montasir Abbas

Car-following models, as the essential part of traffic microscopic simulations, have been utilized to analyze and estimate longitudinal drivers' behavior since sixty years ago. The…