Citation

Ivanco A. J. Saf. Res. 2017; 63: 145-148.

Affiliation

Department of Automotive Engineering, Clemson University, Greenville 29607, SC, USA. Electronic address: aivanco@clemson.edu.

Copyright

(Copyright © 2017, U.S. National Safety Council, Publisher Elsevier Publishing)

DOI

10.1016/j.jsr.2017.10.009

PMID

29203012

Abstract

INTRODUCTION: Modern automobiles are going through a paradigm shift, where the driver may no longer be needed to drive the vehicle. As the self-driving vehicles are making their way to public roads the automakers have to ensure the naturalistic driving feel to gain drivers' confidence and accelerate adoption rates.

METHOD: This paper filters and analyzes a subset of radar data collected from SHRP2 with focus on characterizing the naturalistic headway distance with respect to the vehicle speed.

RESULTS: The paper identifies naturalistic headway distance and compares it with the previous findings from the literature.

CONCLUSION: A clear relation between time headway and speed was confirmed and quantified. A significant difference exists among individual drivers which supports a need to further refine the analysis. PRACTICAL APPLICATIONS: By understanding the relationship between human driving and their surroundings, the naturalistic driving behavior can be quantified and used to increase the adoption rates of autonomous driving. Dangerous and safety-compromising driving can be identified as well in order to avoid its replication in the control algorithms.

Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

Language: en

Keywords

Autonomous; Headway distance; Naturalistic driving; Radar data; SHRP2