2019
DOI: 10.1109/access.2019.2926494
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Driving Style Classification Based on Driving Operational Pictures

Abstract: Accurately describing and classifying driving style is crucial for driving safety intervention strategies in the design of advanced driver assistance systems (ADASs). This paper presents a novel driving style classification method based on constructed driving operational pictures (DOPs) which map sequential data from naturalistic driving into 2-D pictures. By using the nested time window method, 798/1683/1153 DOPs sized 42 (features) × 60 (seconds) were generated for three different driving styles (low-risk, m… Show more

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Cited by 32 publications
(12 citation statements)
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“…(2) The taxiing style of a pilot can be estimated using the examined scanning measures. The scanning behavior of widely accepted safe and experienced pilots can be used as the standard scanning pattern [31], [32]. The safety level of other pilots' scanning behavior can be compared and evaluated for skills training or pilot selection.…”
Section: Discussionmentioning
confidence: 99%
“…(2) The taxiing style of a pilot can be estimated using the examined scanning measures. The scanning behavior of widely accepted safe and experienced pilots can be used as the standard scanning pattern [31], [32]. The safety level of other pilots' scanning behavior can be compared and evaluated for skills training or pilot selection.…”
Section: Discussionmentioning
confidence: 99%
“…T and G • U calculated from (5); notice that this equation, in the special case of N c = 1 reduces to a scalar and it delivers the explicit solution of the first step in the flowchart given in Fig. 1.…”
Section: A Basic Mpc Input-output Data Formulationmentioning
confidence: 93%
“…On the other hand, driving behaviors are closely related to fuel efficiency. The difference in fuel consumption between normal and aggressive driving is estimated to be as high as 40% [4], [5]. As for challenges and opportunities, a key driver is the necessity of a multidisciplinary and an interdisciplinary approach to resolve such complex CPS.…”
Section: Introductionmentioning
confidence: 99%
“…The framework of clustering-based was shown in Fig 1 . The research method based on classification was a more in-depth study based on clustering method, the framework of it was shown in Fig 2 . In this framework, the results of cluster analysis were used to train and test the classification algorithm. The main classification methods include various neural networks [14][15][16][17][18], decision tree [19], random forest (RF) [20], extreme gradient boosting (XGB) [21], support vector machine (SVM) [22,23], Bayes classifier [24,25], AdaBoost [26], and Dempster-Shafer (D-S) evidence theory [27]. Driving style classification could be realized by conventional methods, but there were still many limitations: (1) The clustering-based methods have a problem of re-cluster analysis for newly added data, as new data were generated, it needed to re-analyze the whole data set.…”
Section: Introductionmentioning
confidence: 99%