Citation

Suzdaleva E, Nagy I. Transp. Res. B Methodol. 2019; 128: 254-270.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.trb.2019.08.009

PMID

unavailable

Abstract

This paper deals with the task of modeling the driving style depending on the driving environment. The model of the driving style is represented as a two-layer mixture of normal components describing data with two pointers: outer and inner. The inner pointer indicates the actual driving environment categorized as "urban", "rural" and "highway". The outer pointer through the determined environment estimates the active driving style from a fuel economy point of view as "low consumption", "middle consumption" and "high consumption". All of these driving styles are assumed to exist within each driving environment due to the two-layer model. Parameters of the model and the driving style are estimated online, i.e., while driving using a recursive algorithm under the Bayesian methodology. The main contributions of the presented approach are: (i) the driving style recognition within each of urban, rural and highway environments as well as in the case of switching among them; (ii) the two-layer pointer, which allows us to incorporate the information from continuous data into the model; (iii) the potential use of the data-based model for other measurements using corresponding distributions. The approach was tested using real data.

Language: en

Keywords

Driving environment; Driving style; Fuel consumption; Mixture-based clustering; Recursive mixture estimation; Two-layer pointer