Determinants behind young motorcyclists’ risky riding behavior

Young motorcyclists have traditionally been considered a high-risk population. Given the critical influence of riders’ behaviors on traffic safety, identifying what riders think can help clarify the nature of accidents. Although psychological studies have explored the relationships among personality traits, attitudes and risky driving behavior, the primary difference this study makes from past studies is incorporating both positive and negative effects in a refined causal framework. This study adopts structural equation modeling to analyze data collected from 683 young motorcyclists aged between 18 and 28. The results conclude three primary personality traits of young motorcyclists, namely sensation seeking, amiability and impatience. While amiable riders represent a group of relatively mature and safe riders, the sensation-seeking riders are extremely self-confident, comfortable with unsafe riding and interested in the utility gained from it. Meanwhile, the sensation-seeking ones also are highly aware of traffic conditions, which may lower the chances of getting into an accident, but the accident could be extremely severe if it ever occurs. Impatient riders, having low riding confidence and traffic awareness deficiency, also seek utility from certain risky riding behaviors. However, their fear of an accident leads them to fail to observe surrounding traffic conditions. The result indicates various mental compromise mechanisms for young motorcyclists in conducting riding behaviors. Thus, corresponding countermeasures, including licensure system and ITS roadway development, should consider the heterogeneous characteristics of young riders.     

Exploring the safety implications of young drivers’ behavior,attitudes and perceptions

The present study aims at identifying and quantifying significant factors (i.e., demographic, aberrant driving behavior) associated with young drivers’ involvement in at-fault crashes or traffic citations at the ages of 16–17 (while having the Operational License) and 18–24 years old (while having the Full License). A second objective was to investigate the main reason(s) for involvement in risky driving behavior by young drivers.     

Taxi drivers' views on risky driving behavior in Tehran: a qualitative study using a social marketing approach

The use of the social marketing approach for public health issues is increasing. This approach uses marketing concepts borrowed from the principles of commercial marketing to promote beneficial health behaviors. In this qualitative study, four focus groups involving 42 participants were used in consumer research to explore taxi drivers’ views on the driving situation and the determinants of risky driving behaviors in Tehran, as well as to gather their ideas for developing a social marketing program to reduce risky driving behaviors among taxi drivers in Tehran, Iran.Participants were asked to respond to questions that would guide the development of a marketing mix, or four Ps (product, price, place and promotion). The discussions determined that the program product should involve avoiding risky driving behaviors through increased attention to driving. They pointed out that developing and communicating with a well-designed persuasive message meant to draw their attention to driving could affect their driving behaviors. In addition, participants identified price, place and promotion strategies. They offered suggestions for marketing nonrisky driving to the target audience.The focus group discussions generated important insights into the values and the motivations that affect consumers’ decisions to adopt the product. The focus group guided the development of a social marketing program to reduce risky driving behaviors in taxi drivers in Tehran, Iran.     

Factors affecting stability and change in risky driving from late adolescence to the late twenties

The risky driving tendencies of young drivers has been extensively researched, but much less is known about across-time patterns of risky driving behavior and the factors which influence these. This study identified factors associated with stable, increasing and decreasing risky driving trajectories among 751 Australian drivers participating in an ongoing longitudinal study. Five groups were formed on the basis of participants’ patterns of risky driving from 19–20 to 27–28 years (i.e., stable low-risk, stable speeding, stable high-risk, increasing and decreasing). Very few participants exhibited a stable high-risk pattern. Characteristics that differentiated the different across-time groups were identified using Multinomial Logistic Regression. The most consistent correlates of risky driving patterns were antisocial behavior, binge drinking and relationship status. Sex, school completion, temperament, civic engagement, and antisocial peer friendships were also correlated with different across-time patterns. The implications of these findings for road safety are discussed.     

How reinforcement sensitivity and perceived risk influence young drivers’ reported engagement in risky driving behaviors

Gray's reinforcement sensitivity theory (RST), implementing Carver and White's behavior inhibition system (BIS) and behavior approach system (BAS) scales, was used to predict reported engagement in 10 risky driving behaviors: speeding (2 levels), driving under the influence of alcohol, racing other vehicles, cell phone use (hand-held and hands free), tailgating, unsafe overtaking, driving while fatigued, and not wearing a seatbelt. Participants were 165 young male and female (n = 101) drivers aged 17–25 years who held a valid Australian driver's license. Effects of the explanatory variables and specific risk perceptions upon engagement in the reported risky driving behaviors were examined using SEM analyses. Also of interest was whether perceived risk mediated the relationship between the personality variables and reported engagement in risky driving behaviors. RST variables, negative reactivity, reward responsiveness and fun seeking, accounted for unique variance in young drivers’ perceived risk. Reward responsiveness and perceived risk accounted for unique variance in young drivers’ reported engagement in risky driving behaviors. Negative reactivity was completely mediated by perceived risk in its negative relationship with reported engagement. To better understand driving related risk decision making, future research could usefully incorporate drivers’ motivation systems. This has the potential to lead to more tailored approaches to identifying risk-prone drivers and provide information for the development and implementation of media campaigns and educational programs.     

Driving under the influence of distraction: Examining dissociations between risk perception and engagement in distracted driving

Driving while distracted is a critical and unwavering problem in the United States leading to numerous injuries and fatalities each year. While increasing legislation and developing technological interventions strive to ensure we only focus on driving, individuals still drive distracted. We surveyed college-aged adults to examine the factors that influence both their risk perception of driving while distracted and how often they engage in distracting activities and situations while driving. We found a disassociation between individuals’ perception of driving distraction risk and their engagement with the distraction. Exposure, perceived knowledge of risks, fairness beliefs, and ratings of perceived visual and cognitive demands was associated with risk perception. Conversely, risk-seeking traits, how voluntary the task was perceived, and previous exposure to a distraction influenced engagement. Overall, we recommend additional research focusing on factors that predict engagement in driver distraction rather than perceived risk alone.     

Interrupted versus uninterrupted flow: A safety propensity index for driver behavior

The objective of this paper is to develop a quantitative safety propensity index (SPI) that captures the overall propensity of a given surrounding environment to cause unsafe driving. The study is conducted in two different flow conditions: interrupted and uninterrupted. Using structural modeling techniques, the index can be estimated from observed geometric, weather-related, vehicular, driver-related, and traffic-related characteristics. To illustrate the adopted approach, extensive effort was conducted to “sync” data from different sources including the Virginia Department of Transportation and the FARS/GES crash data libraries. The Virginia Department of Transportation provided traffic data for 10 freeway sections with interrupted flow and 9 highway sections with interrupted flow in the Northern Virginia area, USA. Two different structural equations models were found allowing insights to the safety impact of different surrounding elements/dimensions. The SPI provides (a) a basis for quantifying the effects of the aforementioned characteristics on safety, (b) a basis for comparing the differences between the factors affecting safety in different flow scenarios and (c) ranking the corresponding roadway sections/locations for improved safety performance. The framework and methodology used to develop this index have the potential to support safety policy analysis and decision making.