Statistical Properties of Car Following: Theory and Driving Simulator Experiments

TL;DR

This paper uses a driving simulator to analyze human car-following behavior, revealing that human control actions are intermittent with noise-driven activation, and proposing a new model incorporating jerk and acceleration as key phase variables.

Contribution

It introduces a novel car-following model based on simulator experiments, emphasizing the role of jerk and acceleration as essential for capturing human driving dynamics.

Findings

Human driving actions are best described as generalized intermittent control.

Car jerk and acceleration are crucial phase variables in modeling driver behavior.

The proposed model aligns well with experimental data and real traffic flow observations.

Abstract

A fair simple car driving simulator was created based on the open source engine TORCS and used in car-following experiments aimed at studying the basic features of human behavior in car driving. Four subjects with different skill in driving real cars participated in these experiments. The subjects were instructed to drive a car without overtaking and losing sight of a lead car driven by computer at a fixed speed. Based on the collected data the distributions of the headway distance, the car velocity, acceleration, and jerk are constructed and compared with the available experimental data for the real traffic flow. A new model for the car-following is proposed to capture the found properties. As the main result, we draw a conclusion that human actions in car driving should be categorized as generalized intermittent control with noise-driven activation. Besides, we hypothesize that the car jerk together with the car acceleration are additional phase variables required for describing the dynamics of car motion governed by human drivers.