Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study

11/11/2018

∙

Five car-following models were calibrated, validated and cross-compared. The intelligent driver model performed best among the evaluated models. Considerable behavioral differences between different drivers were found. Calibrated model parameters may not be numerically equivalent with observed ones.

READ FULL TEXT

Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study

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

Driver Identification through Stochastic Multi-State Car-Following Modeling

Strengthening the Case for a Bayesian Approach to Car-following Model Calibration and Validation using Probabilistic Programming

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

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

Formulation and validation of a car-following model based on deep reinforcement learning

Bicycle Longitudinal Motion Modeling

Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study

Related Research

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

Driver Identification through Stochastic Multi-State Car-Following Modeling

Strengthening the Case for a Bayesian Approach to Car-following Model Calibration and Validation using Probabilistic Programming

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

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

Formulation and validation of a car-following model based on deep reinforcement learning

Bicycle Longitudinal Motion Modeling