Formation Mechanisms and Clustering Differences in Risky Riding Behaviors of Electric Bike Riders

Individual differences between various riders cause risky riding behaviors such as violations, taking the lead, negligence and error, and pushing the limits, resulting in a high incidence and high number of road accidents for the vulnerable road use group of electric bike riders. Therefore, the subc...

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Main Authors: Tao Wang, Yuzhi Chen, Jin Yu, Sihong Xie
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
SEM
Online Access:https://ieeexplore.ieee.org/document/9523560/
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spelling doaj-a383718f879a4ed186646c05a2f3ce082021-09-02T23:00:20ZengIEEEIEEE Access2169-35362021-01-01911971211972110.1109/ACCESS.2021.31080399523560Formation Mechanisms and Clustering Differences in Risky Riding Behaviors of Electric Bike RidersTao Wang0https://orcid.org/0000-0002-1386-9587Yuzhi Chen1https://orcid.org/0000-0003-2321-993XJin Yu2Sihong Xie3School of Architecture and Transportation, Guilin University of Electronic Technology, Guilin, ChinaSchool of Architecture and Transportation, Guilin University of Electronic Technology, Guilin, ChinaSchool of Architecture and Transportation, Guilin University of Electronic Technology, Guilin, ChinaSchool of Architecture and Transportation, Guilin University of Electronic Technology, Guilin, ChinaIndividual differences between various riders cause risky riding behaviors such as violations, taking the lead, negligence and error, and pushing the limits, resulting in a high incidence and high number of road accidents for the vulnerable road use group of electric bike riders. Therefore, the subcluster differential characteristics among riders were analyzed in terms of their riding confidence, risk perception, safety attitude, and basic attributes. The influences and formation mechanisms of risky riding behaviors among the subclusters of riders were also explored. First, the 573 riders were clustered into 4 types, action type, anxiety type, introversion type, and negative type, based on the E-bike Risky Riding Behavior Questionnaire (E-RBQ), factor analysis method, and K-means clustering. Second, a structural equation model of e-bike risky riding behavior (E-SEM) was established to explore the main influencing factors for the risky riding behavior of the 4 types of riders and the differences among them. Finally, risky riding behavior avoidance strategies for various types of riders were proposed. The findings showed that negligence and error (0.48) and take the lead behavior (0.44) of action types were significantly and positively influenced by judgment ability; violation behavior (−0.52) and take the lead behavior (−0.41) of anxiety types were significantly and negatively influenced by traffic rules; pushing the limits (−0.29) and take the lead behaviors (−0.31) of introversion types were significantly and negatively influenced by probability evaluation; and negligence and error (−0.43) and violation (0.37) of negative types were negatively and positively influenced by herd mentality. In particular, the overconfidence of the action and anxiety types in their own techniques and judgment ability may cause misjudgment of the surrounding area; the worry degree of the introversion type must be balanced effectively; and the negative type must control the degree of confidence in their judgment ability.https://ieeexplore.ieee.org/document/9523560/Risky riding behaviore-bikeSEMK-means clusteringtraffic safety
collection DOAJ
language English
format Article
sources DOAJ
author Tao Wang
Yuzhi Chen
Jin Yu
Sihong Xie
spellingShingle Tao Wang
Yuzhi Chen
Jin Yu
Sihong Xie
Formation Mechanisms and Clustering Differences in Risky Riding Behaviors of Electric Bike Riders
IEEE Access
Risky riding behavior
e-bike
SEM
K-means clustering
traffic safety
author_facet Tao Wang
Yuzhi Chen
Jin Yu
Sihong Xie
author_sort Tao Wang
title Formation Mechanisms and Clustering Differences in Risky Riding Behaviors of Electric Bike Riders
title_short Formation Mechanisms and Clustering Differences in Risky Riding Behaviors of Electric Bike Riders
title_full Formation Mechanisms and Clustering Differences in Risky Riding Behaviors of Electric Bike Riders
title_fullStr Formation Mechanisms and Clustering Differences in Risky Riding Behaviors of Electric Bike Riders
title_full_unstemmed Formation Mechanisms and Clustering Differences in Risky Riding Behaviors of Electric Bike Riders
title_sort formation mechanisms and clustering differences in risky riding behaviors of electric bike riders
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2021-01-01
description Individual differences between various riders cause risky riding behaviors such as violations, taking the lead, negligence and error, and pushing the limits, resulting in a high incidence and high number of road accidents for the vulnerable road use group of electric bike riders. Therefore, the subcluster differential characteristics among riders were analyzed in terms of their riding confidence, risk perception, safety attitude, and basic attributes. The influences and formation mechanisms of risky riding behaviors among the subclusters of riders were also explored. First, the 573 riders were clustered into 4 types, action type, anxiety type, introversion type, and negative type, based on the E-bike Risky Riding Behavior Questionnaire (E-RBQ), factor analysis method, and K-means clustering. Second, a structural equation model of e-bike risky riding behavior (E-SEM) was established to explore the main influencing factors for the risky riding behavior of the 4 types of riders and the differences among them. Finally, risky riding behavior avoidance strategies for various types of riders were proposed. The findings showed that negligence and error (0.48) and take the lead behavior (0.44) of action types were significantly and positively influenced by judgment ability; violation behavior (−0.52) and take the lead behavior (−0.41) of anxiety types were significantly and negatively influenced by traffic rules; pushing the limits (−0.29) and take the lead behaviors (−0.31) of introversion types were significantly and negatively influenced by probability evaluation; and negligence and error (−0.43) and violation (0.37) of negative types were negatively and positively influenced by herd mentality. In particular, the overconfidence of the action and anxiety types in their own techniques and judgment ability may cause misjudgment of the surrounding area; the worry degree of the introversion type must be balanced effectively; and the negative type must control the degree of confidence in their judgment ability.
topic Risky riding behavior
e-bike
SEM
K-means clustering
traffic safety
url https://ieeexplore.ieee.org/document/9523560/
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