# Model based string stability of adaptive cruise control systems using field data

## TL;DR

This study empirically evaluates the string stability of commercial adaptive cruise control systems using real vehicle data, revealing that these systems are generally string unstable and may contribute to traffic disturbances.

## Contribution

It provides the first empirical calibration and analysis of string stability for real-world ACC systems based on field data.

## Key findings

- Calibrated models show ACC systems are string unstable.
- String instability can lead to traffic disturbances and phantom jams.
- Moderate-sized ACC platoons can dampen some lead vehicle disturbances.

## Abstract

This article is motivated by the lack of empirical data on the performance of commercially available Society of Automotive Engineers level one automated driving systems. To address this, a set of car following experiments are conducted to collect data from a 2015 luxury electric vehicle equipped with a commercial adaptive cruise control (ACC) system. Velocity, relative velocity, and spacing data collected during the experiments are used to calibrate an optimal velocity relative velocity car following model for both the minimum and maximum following settings. The string stability of both calibrated models is assessed, and it is determined that the best-fit models are string unstable, indicating they are not able to prevent all traffic disturbances from amplifying into phantom jams. Based on the calibrated models, we identify the consequences of the string unstable ACC system on synthetic and empirical lead vehicle disturbances, highlighting that some disturbances can be dampened even with string unstable commercial ACC platoons of moderate size.