The effects of co-presence on risk perception and intention to engage in risky behaviors

Cristea, Mioara; Delhomme, Patricia

doi:10.1016/j.jsr.2015.12.006

Cited by 10 publications

(6 citation statements)

References 36 publications

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“…To understand the differences in driver responses to TPB variables under the CV and non-CV environments, we took a conflict point at an unsignalized intersection as the test scenario [19,20,37]. As an intersection is a point where numerous vehicles, pedestrians, and bicycles meet from different directions.…”

Section: A Questionnaire Designmentioning

confidence: 99%

“…Risk perceptions (RP). Four items adapted from previous works were used to measure each risk perception aspect [15,19]. "RP1: I think being concerned about myself being injured in a crash if I accelerate through such an unsignalized intersection.…”

Section: A Questionnaire Designmentioning

confidence: 99%

“…However, there is a shortage of researches in analyzing risky driving intentions for receiving real-time information under the CV environment. Because unsignalized intersections have been considered as one of the most dangerous facilities on highways [18][19][20], the intentions to risk-taking behaviors under the two different environments are tested at unsignalized intersections.…”

Section: Introductionmentioning

confidence: 99%

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Intention of Risk-Taking Behavior at Unsignalized Intersections Under the Connected Vehicle Environment

et al. 2021

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With the rapid emergence of connected vehicle (CV) technologies, there is a shortage of research to understand CV technology's effect on drivers' risk-taking behavioral intentions. This paper aims to analyze driver responses to the real-time information by comparing their reactions to driving intentions between the CV and non-CV environments. A multi-group structural equation model (SEM) is employed to explore the heterogeneity in the relationships between behavioral intentions, attitudes, subjective norms, perceived behavioral control, and risk perceptions under the two different environments. This study reveals two key findings: 1) regarding driver responses to the theory of planned behavior (TPB) model, there are significant differences in attitudes and risk perceptions between the CV and non-CV environments; 2) irrespective of driving environments, risk-taking behavioral intentions are directly related to perceived behavioral control and risk perceptions. While intentions are directly related to attitudes but not associated with subjective norms under the non-CV environment. In contrast, intentions are directly related to subjective norms but not associated with attitude under the CV environment. The findings provide a theoretical basis for using TPB to evaluate CV technology's effects and understanding the differences between the CV and non-CV environments. INDEX TERMS Connected vehicles, Risky driving intentions, Structural equation model, Theory of planned behavior, Unsignalized intersections.

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Section: A Questionnaire Designmentioning

confidence: 99%

Section: A Questionnaire Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Intention of Risk-Taking Behavior at Unsignalized Intersections Under the Connected Vehicle Environment

et al. 2021

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“…This can be explained by the fact that most accidents caused by drivers who are not aware of the potential hazards and break the traffic rules and make an incorrect decision (Rakha et al, 2007;Takemoto et al, 2008).Awareness of risky situations, as a main factor related to accident occurrence, cannot be directly measured but can be reflected by their driving intentions and behaviors in a specific environment (Ma et al, 2010;Şimşekoğlu et al, 2013;Mohamed and Bromfield, 2017;Cox et al, 2017;Steinbakk et al, 2019). Also, the theory of planned behavior (TPB) and its extension has been usually employed to reflect their awareness of risky situation by explaining and predicting driving intentions and behaviors (Zhou et al, 2009;Ma et al, 2010;Cristea and Delhomme, 2016;Atombo et al, 2016;Cristea and Gheorghiu, 2016;Rowe and Andrews, 2016).…”

Section: Introductionmentioning

confidence: 99%

The extended theory of planned behavior considering heterogeneity under a connected vehicle environment: A case of uncontrolled non-signalized intersections

Zhao

Quddus

Huang

et al. 2021

Accident Analysis & Prevention

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“…A large number of empirical studies have confirmed that traffic psychology factors are effective predictors of violation behaviors, and in-depth study of the cause-and-effect relationship between psychological factors and violation behaviors can provide a theoretical foundation for the design of interventions. [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Using the Theory of Planned Behavior to Understand Traffic Violation Behaviors in E-Bike Couriers in China

Qian

Deng

2021

Journal of Advanced Transportation

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This paper identifies salient beliefs that influence e-bike couriers’ traffic violation behavior based on the theory of planned behavior (TPB). Two surveys were conducted in Nanjing, China, in 2018. The first survey extracted the key psychological beliefs, which were used to design a questionnaire. The second survey assessed TPB components and reported e-bike couriers’ traffic violation behavior. A structural equation model was adopted to analyze the data. The results revealed that attitudes, descriptive norms, and perceived behavioral control explained 55.7% of the variance in intention to perform traffic violation behavior, and intentions together with perceived behavior control accounted for 28.5% of the variance in self-reported violation riding behavior. All of the belief composites had strong direct impacts on their respective TPB constructs. Salient beliefs were applied to develop effective intervention strategies. Age, education level, whether one possessed a driver’s license, and past traffic violation behaviors had significant effects on belief composites and behavior. The quantitative analysis results obtained in the study can provide theoretical support for designing more effective interventions for reducing the traffic violation rate of e-bike couriers.

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The effects of co-presence on risk perception and intention to engage in risky behaviors

Cited by 10 publications

References 36 publications

Intention of Risk-Taking Behavior at Unsignalized Intersections Under the Connected Vehicle Environment

Intention of Risk-Taking Behavior at Unsignalized Intersections Under the Connected Vehicle Environment

The extended theory of planned behavior considering heterogeneity under a connected vehicle environment: A case of uncontrolled non-signalized intersections

Using the Theory of Planned Behavior to Understand Traffic Violation Behaviors in E-Bike Couriers in China

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