Female Drivers Research Articles

Effects of personality traits on bus drivers' prosocial and aggressive behaviours: The moderated mediating role of risk perception and gender.

The present study aimed to examine the effects of personality traits on bus drivers' self-reported prosocial and aggressive driving behaviours as well as the mediating role of risk perception and the moderating role of gender in this relationship. Three hundred and ten bus drivers who were 24-57 years old agreed to participate in this study. The measures utilized included personality scales, a risk perception scale and a prosocial and aggressive driving behaviour scale. A moderated mediation model was established. The effects of normlessness/anger on prosocial driving behaviour are mediated by risk perception. Risk perception has a stronger promoting effect on the prosocial driving behaviour of male drivers (b = 0.358, p < 0.01) than it does on that of female drivers (b = 0.072, p > 0.05). The effects of normlessness/anger on the aggressive driving behaviour of both male and female drivers are also mediated by risk perception. Moreover, gender plays a moderating role in the influences of personality and risk perception on aggressive driving behaviour. Drivers with higher risk perception and less anger exhibit less aggressive driving behaviour, and this effect is clearer among male drivers than it is among female drivers. The present study revealed the relationship between personality traits and the prosocial and aggressive driving behaviours of bus drivers through a moderated mediation model. These findings highlight the importance of taking risk perception and gender into consideration when examining the effects of personality on bus drivers' driving behaviours.

Driving in a man's world: examining gender disparity in the trucking industry

PurposeRecent supply chain disruptions have highlighted the global shortage of truck drivers. Because it is a quintessential “masculine” profession, the proportion of women truck drivers is small, although efforts are underway to recruit and retain women. This research offers a comprehensive and theoretically-driven empirical analysis of women in the US trucking industry.Design/methodology/approachThe research utilizes a detailed longitudinal database of 20 million driver inspections from 2010 to 2019. It is paired with US Social Security Administration data to infer the gender of the driver for each inspection. Descriptive evidence is provided, and a logit model is used to test the hypotheses.FindingsThe research finds that female truck drivers make up 3.2% of the inspection sample, but their representation has grown by 23.1% over the last decade. Women are vastly overrepresented in the jobs that are the easiest to get and underrepresented in jobs that offer better pay, more regular hours and more time at home. However, the proportion of women in more desirable truck driving jobs has grown from 2010 to 2019, offering positive news for the industry.Practical implicationsThe research offers a more credible and realistic statistic for the proportion of women in the industry, contradicting previous industry figures. The research also highlights policy implications for industry stakeholders.Social implicationsThe truck driving industry is vital for a nation's economic sustainability. Truck driving jobs offer better wages and more opportunity than many non-professional female-dominant jobs. The research emphasizes the path to move into jobs that are better suited for women with domestic or family responsibilities.Originality/valueThe authors document hitherto unknown facts about women in the US trucking industry. Using theoretically driven research in organizational science, this study highlights the interplay of supply-side and demand-side factors that help to explain a nuanced perspective of the workforce composition and discusses potential policies to increase the number of female drivers.

Knowledge and Adherence to Traffic Regulations and Their Impact Among Female Drivers in Saudi Arabia

Knowledge and Adherence to Traffic Regulations and Their Impact Among Female Drivers in Saudi Arabia

Impact of Driver's Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach.

The purpose of this research is (1) to investigate the relationship between crash severity and the age and gender of the at-fault driver, the socio-economic characteristics of the surrounding environment, and road conditions, and (2) to explain the probability of a bodily injury crash, including fatality, with the alternative being a property damage only crash. In contrast to earlier research that has focused on young and old drivers, age is considered here on its lifetime continuum. A logit model is adopted and the gender and age of the at-fault drivers are part of the independent explanatory variables. The unit of analysis is the individual crash. Since age is a continuous variable, this analysis shows more precisely how age impacts accident severity and identifies when age has little effect. According to the results, the type of vehicle, timing of the crash, type of road and intersection, road condition, regional and locational factors, and socio-economic characteristic have a significant impact on crashes. Regarding the effect of age, when an accident occurs the probability of bodily injury or fatality is 0.703 for female drivers, and 0.718 for male drivers at 15 years of age. These probabilities decline very slightly to 0.696 and 0.711, respectively, around 33 years of age, then very slightly increase to 0.697 and 0.712, respectively, around 47.5 years of age. The results show that age affects crash severity following a polynomial curve. While the overall pattern is one of a downward trend with age, this trend is weak until the senior years. The policy implications of the results are discussed.

Micro-Mobility Sharing System Accident Case Analysis by Statistical Machine Learning Algorithms

This study aims to analyze the variables that affect the accidents experienced by e-scooter users and to estimate the probability of an accident during travel with an e-scooter vehicle. The data of e-scooter drivers, offered for use via rental application in 15 different cities of Turkey, were run in this study. The methodology of this study consists of testing the effects of the input parameters with the statistical analysis of the data, estimating the probability of an e-scooter accident with machine learning, and calculating the optimum values of the input parameters to minimize e-scooter accidents. By running SVM, RF, AB, kNN, and NN algorithms, four statuses (completed, injured, material damage, and nonapplicable) likely to be encountered by shared e-scooter drivers during the journey are estimated in this study. The F1 score values of the SVM, RF, kNN, AB, and NN algorithms were calculated as 0.821, 0.907, 0.839, 0.928, and 0.821, respectively. The AB algorithm showed the best performance with high accuracy. In addition, the highest consistency ratio in the ML algorithms belongs to the AB algorithm, which has a mean value of 0.930 and a standard deviation value of 0.178. As a result, the rental experience, distance, driving time, and driving speed for a female driver were calculated as 100, 10.44 km, 48.33 min, and 13.38 km/h, respectively, so that shared e-scooter drivers can complete their journey without any problems. The optimum values of the independent variables of the rental experience, distance, driving time, and driving speed for male drivers were computed as 120, 11.49 km, 52.20 min, and 17.28 km/h, respectively. Finally, this study generally provides a guide to authorized institutions so that customers who use shared and rentable micro-mobility e-scooter vehicles do not have problems during the travel process.

Using confidence interval-based estimation of relevance to determine women’s emotions and perceptions of the Malaysian road environment during COVID-19

The road environment is one of the factors that contribute to road accidents. Extensive research has been conducted on the diversity of road users, conditions, and environments; however, it tends to be general in focus. In Malaysia, the road environment is an important element of the Critical National Information Infrastructure (CNII) agenda. As women play a greater role in a country’s population growth, they are considered to hold greater responsibility for the nation’s sustainability. This paper examines the road environment in Malaysia, centering on women’s perceptions and using emotions as a predictor. The study data were collected via an online Google form that was specifically targeted at female drivers. A total of 93 respondents participated in the survey. The results include an R2 value equal to 0.27 with a 99% confidence interval. The results indicate that emotions played a moderate role in determining women’s perceptions of the on-road environment. Meanwhile, respondents with negative emotions were able to separate their cognitive processes without affecting their perception. Current research indicates that the confidence interval-based estimation of relevance (CIBER) technique is efficient at predicting behavior and is useful for behavior modification in the future, which has significant implications for policy revision and recommendations. Limitations of this research include its focus on women and reliance on data collected during the pandemic, which may be different from other events or situations. Finally, this research suggests that it would be appropriate to establish future behavior interventions among road users at the national level.

Positive and Negative Politeness in Nonverbal Communication Contexts: An Examination into Driving Behaviors in Europe

This study examines politeness as a nonverbal politic behavior in 29 European countries and territories using Brown and Levinson’s (1987) politeness theory. The examination looked into the nonverbal acts of ‘following road signs and speed limit’ and ‘giving signals before changing lanes’ as they reflect (1) negative politeness in the form of avoiding imposition and reducing face-threatening-acts and (2) positive politeness in the form of noticing and appreciating other drivers’ wants and interests to drive without imposition respectively. The examination looked into four variables that are the gender of drivers, age of drivers, level of education of drivers and their country of origin. The study found that European drivers are generally polite and they tend to use the positive politeness act (giving signals) of noticing and appreciating other drivers more often than the negative politeness act (following sigs and speed limits) of reducing imposition and avoiding face-threatening acts. The study also found that the level of education did not play a significant role in the adherence to the driving politic behavior. However, this study found a positive coloration between the age of drivers and their adherence to the driving politic behavior as older drivers follow the driving politic behavior more often than young drivers. This study also found that female drivers in Europe are more polite than male drivers as they notice and appreciate other drivers (positive politeness). This study also revealed that Danish (female), British (male and female), Irish (male), Finish (male), Dutch (male and female), Belgium (female), Austrian (female), Greek (female) and Spanish (male) drivers have the highest frequency of adherence to the driving politic behavior. The study also found that Portuguese male and female, Croatian male and female, Macedonian male and female, Scottish male and female, Albanian male, Norwegian male, Czech male, Austrian female, Romanian male and Swedish female drivers have the lowest frequency of adherence to the driving politic behavior in Europe. The study also found that Cypriot (male), Catalonian (female), French (male and female), German (male and female), Hungarian (male and female), Italian (male and female), Polish (male and female), Russian (male and female), Serbian (male and female), Slovakian (male and female), and Turkish (male and female) drivers’ adherence to driving politic behavior is relatively moderate to high.

Identifying the Factors Contributing to Freeway Crash Severity Based on Discrete Choice Models

The freeway’s operation safety has attracted wide attention. In order to mitigate the losses brought on by traffic accidents on freeways, discrete choice models were constructed based on the statistical analysis method to quantitatively analyze the significance and magnitude of the impact of multiple dimensional factors on crash severity. Based on 1154 accidents that occurred on Zhejiang Province’s Hang-Jin-Qu Fressway from 2013 to 2018, the distribution characteristics of crash severity were analyzed. The dependent variable was the crash injury severity, which was categorized into property damage only (PDO), injury, and fatal. As independent variables, 15 candidate variables representing four aspects, including driver, vehicle, road, and environmental conditions, were chosen. Considering the ordered characteristics of the variables, the models developed included the ordered logit, the generalized ordered logit, and the partial proportional odds models. The Brant test found that the previous two models had difficulty dealing with the problem of partial variables that did not fit the parallel-lines assumption, and the conclusions were finally discussed through the partial proportional odds model results. The findings indicate that 11 factors have significant consequences. Five variables, namely “mountainous”, “female”, “driving experience 2- years”, “large vehicle responsible”, and “vehicle not going straight”, violated the parallel-lines assumption. Female drivers and drivers aged 55+ years were more likely to suffer injuries and fatalities in collisions with guardrails and other objects. Large vehicles being involved and vehicles not going straight enhanced the likelihood of injury and fatal outcomes when drivers had 2- years of experience. Wet-skid road conditions enhanced the likelihood of injury accidents, and driving at nighttime without lighting increased the likelihood of fatal accidents. Departments responsible for traffic management can take full account of these variations and develop focused proposals for improvement.

A case and framework for expanding the use of model‐free evidence

A case and framework for expanding the use of model‐free evidence

The Vehicle Safety Standard Bias: How Male-Based Crash Testing Leaves Female Drivers in the Backseat

What do crash test dummies and gender bias have to do with one another? A lot more than you might think. This article explains how today's vehicular safety standards can put women at risk.

KNOWLEDGE, ATTITUDE AND PRACTICE ABOUT CAR SEATBELT AMONG DRIVING WOMEN IN SAUDI ARABIA 2019

Background: The purpose of this study is to conduct an assessment of knowledge, attitude and practice of car seatbelt among driving women in Saudi Arabia since women now are allowed to obtain a driving license in Saudi Arabia. The lack of this kind of study which assesses diving women in Saudi we were motivated to conduct this study. We want to know the KAP of female drivers in Saudi Arabia and also the association between the sociodemographic and the KAP regarding car seatbelt. General objective: To assess Saudi women drivers knowledge, attitude and practice of using seatbelt while driving. Methods: A cross sectional study targeting all driving women who will respond self-administered online questionnaire, will be distributed through social media in Saudi Arabia from 12, Jan to 20, Jan ,2019. Conclusion: The perception of participants about using safety seat belt was 97%, the percentage of using seat belt during driving in city 65% while 81% using seat belt during driving in highway They represent 58% and the second most common restriction of movement represent 29.8most common barrier among driver women is forgetting using seat belt.

Studying Driver’s Perception Arousal and Takeover Performance in Autonomous Driving

The driver’s perception level and takeover performance are two major factors that result in accidents in autonomous vehicles. This study’s goal is to analyze the change in drivers’ perception level and its influence on takeover performance during autonomous driving. A takeover behavior test platform is implemented based on a high-fidelity driving simulator. The fog zone is selected as the takeover scenario. Thus, a 2 (takeover request time: 5 s, 10 s) by 2 (non-driving-related task: work task, entertainment task) takeover experiment was conducted. A generalized linear mixed model is developed to explore the influence of the perception level on takeover performance. The study finds out that, after the takeover request is triggered, the driver’s gaze duration is shortened and the pupil area is enlarged, which is helpful for the driver to extract and understand the road information faster. Male drivers have greater perception levels than female drivers, and they prioritize leisure tasks more than professional ones. The drivers’ perception level decreases when age increases. The shorter the gaze duration is, and the larger the pupil area is, the shorter the takeover response time will be. In addition, drivers’ perception level has a positive effect on takeover performance. Finally, this study provides a reference for revealing the changing rules of drivers’ perception level in autonomous driving, and the study can provide support for the diagnosis of takeover risks of autonomous vehicles from the perspective of human factors.

The effectiveness of prosocial policies: Gender differences arising from social norms.

We study policies aimed at discouraging behavior that produces negative externalities, and their differential gender impact. Using driving as an application, we carry out an experiment where slowest vehicles are the safest choice, whereas faster driving speeds lead to higher potential payoffs but higher probabilities of accidents. Faster speeds have a personal benefit but create a negative externality. We consider four experimental policy conditions: a baseline situation, a framing condition in which drivers are suggested that driving fast violates a social norm, and two punishment conditions, one exogenous and one endogenous. We find that the most effective policies use different framing and endogenously determined punishment mechanisms (to fast drivers by other drivers). These policies are only effective for female drivers which leads to substantial gender payoff differences. Our data suggest that these results arise from differences in social norms across genders, thus opening the way to designing more effective policies.

Impact of an exclusive narrow automated vehicle lane on adjacent lane driver behavior

This study contributes to understanding the behavioral impacts of infrastructure adaptation to Automated Vehicles (AVs) on non-AV drivers. It attempts to answer the question of how a narrow (9 ft) lane dedicated to AVs would affect the behavior of drivers in terms of safety measures who are driving in the adjacent lane to the right. To this end, a custom designed driving simulator world was designed mimicking the Interstate 15 smart corridor in San Diego. A group of participants were assigned to drive next to the simulated 9 ft narrow lane while a control group were assigned to drive next to a regular 12 ft AV lane. Behavior of drivers was analyzed by measuring the mean lane position, mean speed, and the mental effort. In addition to AV lane width, AV headway, gender, and right lane traffic were taken into consideration in the experimental design to investigate interaction effects. The results showed no significant differences in speed and mental effort of drivers while indicating significant differences in lane positioning. Although the overall effect of AV lane width was not significant, there were some significant interaction effects between lane width and other factors (i.e., driver gender and presence of traffic on the next regular lane to the right). In all the significant interactions, there was no case in which those factors stayed constant while AV lane width changed between the groups indicating that the significant difference might be stemmed from the other factors rather than the lane width. However, the trend observed was that drivers driving next to the 12 ft lane had better lane centering compared to the 9 ft lane. The analysis also showed that while in general female drivers tended to drive further away from the 9 ft lane and performed worse in terms of lane centering, they performed better than male drivers when right lane traffic was present.

Road traffic accident prediction for mixed traffic flow using artificial neural network

Transport scenariosin developingcountries arefundamentally different fromthose indevelopedcountries. The latterconsists primarilyof passenger cars and can beadequately describedas“homogeneous” traffic,butthe formerconsistsof vehicle types withdifferentstatic and dynamiccharacteristics thatoccupy the same right ofway. Vehiclemovementis asynchronous. Fewstudies have attempted tounderstand the characteristics of mixed traffic. Thisarticleexplores the sharing attributes and influencing causes of traffic accidents inamixed trafficarea. A predictability model isemployed todescribethe connection between highwaydisastersand appropriate constraints such astraffic capacity, road provisions,and atmosphereissues. In this paper,the comparison has been done between the Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) predictive models. The study has been conducted at Pimpri Chinchwad Muncipal Corporation (PCMC) region of Pune, Maharashtra, India. For this work, nine years data has been used ranging from the year 2011 to 2019. Results revels that, maximum numbers of accidents were occurred in clear weather condition. Distinctive accidents were occurred due to overloaded vehicle conditions. Also it has been found that the less number of female drivers are responsible for accident. Forecasting model using ANN presents outstanding precision. In this study, additional prominence has been givento the real constraints which are accountable for accident cause in heterogeneous traffic flow.

Application of Unsupervised Machine Learning Classification for the Analysis of Driver Behavior in Work Zones in the State of Qatar

Work zone areas are commonly known as crash-prone areas. Thus, they usually receive high priority by road operators as drivers and workers have higher chances of being involved in road crashes. The paper aims to investigate driving behavior in work zones using unsupervised machine learning and vehicle kinematic data. A dataset of 67 participants was gathered through an experiment using a driving simulator located at the Qatar Transportation and Traffic Safety Center (QTTSC). The study considered two different work zone scenarios where the leftmost lane was closed for maintenance. In the first scenario, drivers drove on the leftmost lane (Drive 1), while in the second, they drove on the second leftmost lane (Drive 2). The results show that the number of aggressive and conservative drivers was surprisingly more than normal drivers, as most participants either cautiously drove through or failed to drive without being aggressive. The results also show that drivers acted more aggressively in the leftmost lane rather than in the second leftmost lane. We also found that female drivers and drivers with relatively little driving experience were more likely to be aggressive as they drove through a work zone. The framework was found to be promising and can help policymakers take optimal safety countermeasures in work zones during construction.

Cognitive Preference Performance of In-Vehicle Human–Machine Interface Icons under Female New Energy Vehicles

With the advent of the “her economy” era, the new energy automobile market has also ushered in the “her era”, and female consumers have gradually become the main force of domestic and foreign vehicle consumption, thus contributing to the sustainable and rapid development of many female new energy automobile market segments. In this context, this study explores the icon cognitive preferences of female drivers based on gender differences in icon cognition by taking the human–machine interface icons in new energy automobiles as a case study. Firstly, we conducted behavioral response experiments and facial electromyography experiments on 20 male and female participants to analyze their cognitive preferences for icons by combining the four dimensions of “semantic dimension, conceptual dimension, contextual dimension and pragmatic dimension”. The results showed that the four−dimensional graphic deconstruction format had a significant effect on the improvement of icon recognition performance. At the same time, we designed 10 formats of icons as experimental stimulus materials and combined them with subjective scales to jointly explore the reasons for the bias of different gender participants towards icons. The results show that there are significant gender differences in icon perception on a four−dimensional basis, with males more likely to be disturbed by icon constituent elements (semantic dimension), while females are more likely to be disturbed by icon metaphors (semantic dimension) and usage environment and interface context (contextual dimension). This study helps to explore the best balance between studying women’s driving experiences in new energy vehicles and the sustainable product life cycle, and then improve the accuracy of women drivers’ decision−making behavior in new energy vehicles to ensure driving safety.

Understanding the drowsy driving crash patterns from correspondence regression analysis

Abstract: Drowsy driving-related crashes have been a key concern in transportation safety. In Louisiana, 14% (1,758 out of 12,512) of police-reported drowsy driving-related crashes during 2015–2019 resulted in injury (fatal, severe, or moderate). Amid the calls for action against drowsy driving by national agencies, it is of paramount importance to explore the key reportable attributes of drowsy driving behaviors and their potential association with crash severity. Method: This study used 5-years (2015–2019) of crash data and utilized the correspondence regression analysis method to identify the key collective associations of attributes in drowsy driving-related crashes and interpretable patterns based on injury levels. Results: Several drowsy driving-related crash patterns were identified through crash clusters – afternoon fatigue crashes by middle-aged female drivers on urban multilane curves, crossover crashes by young drivers on low-speed roadways, crashes by male drivers during dark rainy conditions, pickup truck crashes in manufacturing/industrial areas, late-night crashes in business and residential districts, and heavy truck crashes on elevated curves. Several attributes – scattered residential areas indicating rural areas, multiple passengers, and older drivers (aged more than 65 years) – showed a strong association with fatal and severe injury crashes. Practical Applications: The findings of this study are expected to help researchers, planners, and policymakers in understanding and developing strategic mitigation measures to prevent drowsy driving.

3D Simulation Test and Development of Interchangeable Heel Shoes for Female Drivers

3D Simulation Test and Development of Interchangeable Heel Shoes for Female Drivers

The Role of Sex in Evaluating Other Male and Female Drivers’ Driving Skills and Behavior

Countries with wider gender gap might host sex-based stereotypical evaluations, which might be present from the early ages and persist. It might also hinder the stereotyped groups’ performance on the stereotyped field, such as driving (Granié and Papafava, 2011; Moè, Cadinu, &amp; Maass, 2015; Steele &amp; Aronson, 1995). Although the effect of sex and gender roles in self-evaluated driving skills and behaviors are studied, the possible effect of sex in evaluating other male and female drivers in their driving skills and behaviors was not a topic of interest in road safety studies. Thus, the aim of the current study was to investigate whether sex of the participants was a significant factor in evaluating other male and female drivers’ driving skills and behavior. 92 Female and 70 male drivers participated in the study. Participants were asked to fill forms of Driver Skill Inventory (DSI) and Driver Behavior Questionnaire (DBQ) to assess driving skills and behaviors of other male and female drivers. The results indicated significant differences between male and female participants in evaluations of other female drivers’ perceptual-motor skills, safety skills, and driving errors. In line with the literature, female drivers were endorsed for their safety skills, and male participants were endorsed for their perceptual motor skills. Similarly, female drivers received higher mean values for lapses and male drivers received higher mean values for errors, aggressive violations, and ordinary violations. Results are important in raising awareness regarding sex-based stereotypical evaluations of drivers, especially towards female drivers, in Turkey.