Driving behavior: traffic risk perception and intentions to commit driving violations in Iran

2014 ◽  
Author(s):  
Zahra Tabibi ◽  
◽  
Hoda Hashemi Chahnoeei ◽  
Keyword(s):  
Risk Perception ◽  
Driving Behavior

scholarly journals Driving Behavior Theory and Computer Simulation System of Driver's Risk Perception based on 3D

2013 ◽  
Vol 96 ◽  
pp. 1686-1695 ◽  
Author(s):  
Zhao Jian-you ◽  
Shi Xiao-fen ◽  
Zhao Liang ◽  
Zhao Shuang-xi ◽  
Niu Xi-yang
Keyword(s):  
Computer Simulation ◽  
Risk Perception ◽  
Driving Behavior ◽  
Simulation System ◽  
Behavior Theory

scholarly journals Social Norms and Risk Perception: Predictors of Distracted Driving Behavior Among Novice Adolescent Drivers

2014 ◽  
Vol 54 (5) ◽  
pp. S32-S41 ◽  
Author(s):  
Patrick M. Carter ◽  
C. Raymond Bingham ◽  
Jennifer S. Zakrajsek ◽  
Jean T. Shope ◽  
Tina B. Sayer
Keyword(s):  
Risk Perception ◽  
Social Norms ◽  
Driving Behavior ◽  
Distracted Driving ◽  
Adolescent Drivers

Effects of Occupational Drivers’ Traffic Accident History on Risk Perception, Work Attitudes, and Unstable Driving

2021 ◽  
pp. 036119812110126
Author(s):  
Eun Kyoung Chung ◽  
So Young Park ◽  
Young Woo Sohn
Keyword(s):  
Job Satisfaction ◽  
Risk Perception ◽  
Job Stress ◽  
Traffic Accident ◽  
Work Attitudes ◽  
Driving Behavior ◽  
Safe Driving ◽  
Professional Pride ◽  
The Relationship ◽  
Occupational Drivers

In previous studies the risk perception of future accidents was the main variable likely to affect safe driving. However, findings on the relationship between traffic accident history and risk perception of future accidents have been inconsistent. Moreover, in the case of occupational drivers, work attitudes could be the main factor affecting safe driving. However, no research has been conducted on the direct relationship between traffic accident history and work attitudes. Therefore, present study examined the effect of occupational drivers’ traffic accident history on their risk perception, work attitudes, and unstable driving. Data analysis was based on a self-reported survey of Korean occupational drivers (n = 388) and their official traffic accident records. Results show that traffic accident history was associated significantly with professional pride, job satisfaction, and aggressive driving but not with risk perception of future accidents or job stress. Moreover, all variables measuring unstable driving behavior were significantly related to professional pride, job satisfaction, and job stress. Furthermore, professional pride turned out to mediate the relationship between traffic accident history and current unstable driving. The major finding is that there is no significant relationship between traffic accident history and risk perception of future accidents. Furthermore, traffic accident history has a significant effect on positive variables such as professional pride and job satisfaction but not on negative variables such as job stress. In addition, the significant mediator in the relationship between traffic accident history and current unstable driving behavior was only professional pride.

1315 Examination of Risk Perception Ability of Mobility Scooter Users and Their Unsafe Driving Behavior in Daily Life

2014 ◽  
Vol 2014.23 (0) ◽  
pp. 221-224
Author(s):  
Motoki Shino ◽  
Hideyuki Shimomura ◽  
Motoaki Matsuyama ◽  
Kunihiro Hayashi ◽  
Minoru Kamata
Keyword(s):  
Risk Perception ◽  
Daily Life ◽  
Driving Behavior

scholarly journals Predicting Compliance with Speed Limits using Speed Limit Credibility Perception and Risk Perception Data

2020 ◽  
Vol 2674 (9) ◽  
pp. 450-461
Author(s):  
Yao Yao ◽  
Oliver Carsten ◽  
Daryl Hibberd
Keyword(s):  
Risk Perception ◽  
Driving Simulator ◽  
Learning Algorithm ◽  
Warning System ◽  
Personal Characteristics ◽  
Driving Behavior ◽  
Speed Limit ◽  
Speed Limits ◽  
The Road ◽  
Boosted Decision Tree

The link between attitudes and behavior shows that driving behavior can be predicted by personal characteristics and individual attitudes, as has been shown in previous research. This study aimed to predict the level of compliance with speed limits by individual drivers by using attitudes data including speed limit credibility perception and risk perception on eight rural single carriageway layouts. This study investigated how the road layout and roadside environment affect speed limit credibility perception and risk perception, and investigated which machine learning algorithm can be used to predict driving behavior based on experimental evidence. This study was carried out in a well-controlled experimental design by using a questionnaire and a driving simulator. The simulated road environment only considered rural single carriageway which has higher risk factors than other road types. The results show that a boosted decision tree algorithm can establish a driving behavior model based on drivers’ credibility perception and risk perception. This result can be used to predict driving behavior in advance for in-vehicle warning system design.

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