Citation

Qi G, Guan W. Accid. Anal. Prev. 2019; 123: 282-290.

Affiliation

MOE Key Laboratory of Urban, Transportation Complex System Theory and Technology, Beijing Jiaotong University, Beijing 100044, PR China. Electronic address: weig@bjtu.edu.cn.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.aap.2018.12.006

PMID

30554060

Abstract

Situational discomfort awareness plays an important role in decision making among drivers and has rarely been discussed in detail in previous research. An instrumented vehicle was used to collect car-following data from multiple drivers, thereby quantitatively examining situational discomfort grading patterns using a new discomfort grading method and the latent Dirichlet allocation model. In this process, the gas pedal data and speed difference data are particularly involved in the computation for providing broader meaning to discomfort and building more comprehensive situations. The results show that individual discomfort awareness varies between drivers. More importantly, the potential patterns of situational discomfort grading are extracted, which provides knowledge for characterizing drivers in the context of discomfort awareness. The knowledge achieved can be further applied to distinguish drivers and identify the typical comfort and discomfort zones. This study has great value for promoting investigations on traffic psychology and developing more effective and customized driver assistant systems.

Copyright © 2018 Elsevier Ltd. All rights reserved.

Language: en

Keywords

Car-following; Driving behaviour; Latent Dirichlet allocation; Situational discomfort