Seemingly irrational driving behavior model: The effect of habit strength and anticipated affective reactions

Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior

Low-speed driving is an underestimated dangerous behavior that may cause safety issues, such as speed dispersion and traffic flow bottlenecks. To investigate the influence mechanism of low-speed driving behavior, this study constructed the low-speed specific model (LSSM) by extending theory of planned behavior (TPB). The LSSM incorporated two factors, namely, risk perception and behavior habit, into the standard TPB components (attitude, subjective norm, perceived behavioral control, and behavior intention). Web-based questionnaires were used to collect data from a valid sample of 374, of which males accounted for 50%. The participants were aged from 18 to 65 years (M = 35.40, SD = 0.88). The structural equation model was applied to calculate and validate the interrelationships among the components of LSSM. Results showed that the LSSM could explain the variance in low-speed driving behavior and behavior intention by 46% and 76%, respectively. Meanwhile, attitude (β = 0.52, p < 0.001) and behavior habit (β = 0.48, p < 0.001) had the strongest positive influence and prediction power over low-speed driving behavior, respectively, whereas subjective norm (β = 0.05, p > 0.01) and perceived behavioral control (β = -0.12, p > 0.01) showed few significant in influencing the intention. LSSM also showed that people who were sensitive to driving risk perception would avoid low-speed driving behaviors and attitudes. Our findings may provide theoretical support for interventions on low-speed driving behavior.

Do nutrition knowledge, food preferences, and habit strength moderate the association between preference for intuition and deliberation in eating decision-making and dietary intake?

An intuitive style in eating decision-making, for example, basing decisions on one's gut feeling, has been related to a less healthy diet, whereas deliberately deciding what to eat, such as making plans about eating behavior, has been related to a healthier diet. The present study investigated whether nutrition knowledge, food preferences, and habit strength for healthy and unhealthy eating moderate these relationships. In total, 1245 participants took part in a preregistered cross-sectional online survey. Results revealed that neither nutrition knowledge, nor liking of healthy or unhealthy foods, nor habit strength for healthy or unhealthy eating interacted with the preference for intuition or deliberation in eating decision-making in affecting dietary intake (βs ≤ |.06|; ts ≤ |2.11|; ps ≥ .035). Instead, including the potential moderating variables in analyses rendered the effect of a preference for intuition largely non-significant. In contrast, the positive effect of a preference for deliberation was largely stable even when including the potential moderating variables. Thus, the present study confirms the general health-promoting effect of a preference for deliberation in eating decision-making. In contrast, results speak in favor of a generally minor role of a preference for intuition for healthy or unhealthy eating.

Understanding the Sociocognitive Process of Construction Workers' Unsafe Behaviors: An Agent-Based Modeling Approach

Previous literature has recognized that workers’ unsafe behavior is the combined result of both isolated individual cognitive processes and their interaction with others. Based on the consideration of both individual cognitive factors and social organizational factors, this paper aims to develop an Agent-Based Modeling (ABM) approach to explore construction workers’ sociocognitive processes under the interaction with managers, coworkers, and foremen. The developed model is applied to explore the causes of cognitive failure of construction workers and the influence of social groups and social organizational factors on the workers’ unsafe behavior. The results indicate that (1) workers’ unsafe behaviors are gradually reduced with the interaction with managers, foremen, and workers; (2) the foreman is most influential in reducing workers’ unsafe behaviors, and their demonstration role can hardly be ignored; (3) the failure of sociocognitive process of construction workers is affected by many factors, and cognitive process errors could be corrected under social norms; and (4) among various social organizational factors, social identity has the most obvious effect on reducing workers’ unsafe behaviors, and preventive measures are more effective than reactive measures in reducing workers’ unsafe behaviors.

Research on Risky Driving Behavior of Novice Drivers

Novice drivers have become the main group responsible for traffic accidents because of their lack of experience and relatively weak driving skills. Therefore, it is of great value and significance to study the related problems of the risky driving behavior of novice drivers. In this paper, we analyzed and quantified key factors leading to risky driving behavior of novice drivers on the basis of the planned behavior theory and the protection motivation theory. We integrated the theory of planned behavior (TPB) and the theory of planned behavior (PMT) to extensively discuss the formation mechanism of the dangerous driving behavior of novice drivers. The theoretical analysis showed that novice drivers engage in three main risky behaviors: easily changing their attitudes, overestimating their driving skills, and underestimating illegal driving. On the basis of the aforementioned results, we then proposed some specific suggestions such as traffic safety education and training, social supervision, and law construction for novice drivers to reduce their risky behavior.

How to quantitatively evaluate safety of driver behavior upon accident? A biomechanical methodology

How to evaluate driver spontaneous reactions in various collision patterns in a quantitative way is one of the most important topics in vehicle safety. Firstly, this paper constructs representative numerical crash scenarios described by impact velocity, impact angle and contact position based on finite element (FE) computation platform. Secondly, a driver cabin model is extracted and described in the well validated multi-rigid body (MB) model to compute the value of weighted injury criterion to quantitatively assess drivers’ overall injury under certain circumstances. Furthermore, based on the coupling of FE and MB, parametric studies on various crash scenarios are conducted. It is revealed that the WIC (Weighted Injury Criteria) value variation law under high impact velocities is quite distinct comparing with the one in low impact velocities. In addition, the coupling effect can be elucidated by the fact that the difference of WIC value among three impact velocities under smaller impact angles tends to be distinctly higher than that under larger impact angles. Meanwhile, high impact velocity also increases the sensitivity of WIC under different collision positions and impact angles. Results may provide a new methodology to quantitatively evaluate driving behaviors and serve as a significant guiding step towards collision avoidance for autonomous driving vehicles.

An examination of the construct and predictive validity of the self-reported speeding behavior model

The present study deals with the problem of speeding behavior on rural roads. The purpose of the paper is to examine the construct validity and the internal consistency and reliability of a questionnaire that measures the determinants of speeding behavior. In addition, it aimed to test the predictive validity of a modified theoretical framework of a theory of planned behavior (TPB) in relation to speeding behavior. A total of 546 car drivers from five local communities in the Republic of Srpska successfully completed the questionnaire after reading the scenario. The principal component analysis revealed seven components interpreted as: personal norm, perceived behavioral control, affective attitude toward speeding, subjective norm, habit, descriptive norm, and cognitive attitude toward speeding. A speeding behavior model was developed by structural equation modeling. Personal norm, subjective norm, and affective attitudes were shown to be important variables within the modified TPB in understanding speeding behavior. Overall, the present findings provide significant support for the concept of the modified theoretical framework of TPB in relation to speeding behavior on rural roads. Implications for a speeding behavior model and interventions are discussed.