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

TL;DR

This study evaluates five car-following models using naturalistic driving data from Shanghai, finding the intelligent driver model most effective and highlighting significant behavioral differences among drivers.

Contribution

It provides a comprehensive calibration and validation of multiple models on real-world data, revealing behavioral variability and calibration limitations.

Findings

Intelligent driver model outperformed others.

Significant behavioral differences among drivers.

Calibrated parameters may not match observed data.

Abstract

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.