Risky Driving Research Articles

Influence of Risky Driving Behavior and Road Section Type on Urban Expressway Driving Safety

The causes of traffic crashes are complex and uncertain, among which the risky driving behaviors of drivers and the types of road sections in high-crash areas are all critical influencing factors. We used ArcGIS software to draw traffic heat maps under different thresholds to prevent the occurrence of traffic crashes accurately and effectively according to the vehicle GPS data of urban expressways in Jinan City, Shandong Province. This paper studied the relationship between risky driving behaviors (rapid acceleration, rapid deceleration, and overspeed) and road types with traffic crashes. The traffic safety evaluation model of urban expressways based on ordered logistic was established to predict the safety level of the urban expressway. The model’s accuracy was 85.71%, and the applicability was good. The research results showed that rapid deceleration was the most significant influencing factor of crashes on urban expressways. When the vehicle deceleration was less than or equal to −4 m/s2, the probability of a crash was 22.737 times greater than when the vehicle deceleration was at −2 to −2.5 m/s2; when the vehicle acceleration was greater than or equal to 3 m/s2, the probability of a crash was 19.453 times greater than when the vehicle acceleration was at 1 to 1.5 m/s2. The likelihood of a crash at a road section with a ramp opening was 8.723 times greater than that of a crash at a non-ramp opening; the crash probability of a speeding vehicle was 7.925 times greater than that of a non-speeding vehicle; the likelihood of a crash on a curve was 6.147 times greater than that on a straight. The research results can provide adequate technical support for identifying high-risk sections of expressways and active early warning of traffic crashes.

Exploration of road closure time characteristics of tunnel traffic accidents: A case study in Pennsylvania, USA

With the increase of roadway tunnels, tunnel traffic accidents are also increasing. Compared with open roadways, road closures caused by traffic accidents in the tunnel have greater influences on traffic operations, as tunnels are often the key junctions of the roadway network. With the traffic accident data of Pennsylvania from 1997 to 2020, this study is designed to identify the features and trends of road closure time due to tunnel traffic accidents. First, features of tunnel and non-tunnel traffic accidents are compared from the perspectives of accident consequences, environmental factors, risky driver behavior, and vehicle features. The data confirms that tunnel traffic accidents are more likely to lead to road closures than non-tunnel ones. Besides, tunnel traffic accidents are mainly consisted of rear-end and hit-fixed-object collisions with many speeding cases. Then, a Negative Binomial model is built to statistically identify the factors significantly influencing the road closure time, which is recorded as non-negative integer in the data. The estimation results indicate that collision type, accident severity, road type, driving under the influence, the involvement of heavy trucks, and the number of involved vehicles could significantly influence the road closure time, whereas lighting, road condition, speeding, and area are insignificant. Finally, based on the research findings, some countermeasures are proposed to reduce the road closure time caused by tunnel traffic accidents.

Predicting Risky Driving in a Connected Vehicle Environment

In this paper we propose an unsupervised learning framework to predict risky driving at intersections in a connected vehicle environment. The proposed framework uses time series k-means to categorize multi-dimensional time series trajectories into several context-aware driving patterns. Dynamic time warping (DTW) is implemented within the time series k-means algorithm for measuring the similarity between trajectories. DTW is adopted to make the framework robust to temporal distortions and missing data points. We train an isolation forest (iForest) model on the trajectory dataset to identify anomalous trajectories, and apply this model to clusters to provide Risky Driving Prediction (RDP) scores for each driving pattern. We provide a real-time online assessment approach to predict the risk score of driving trajectories that travel toward a signalized intersection. We use real-world connected vehicle trajectories collected by a road-side unit (RSU) in Ann Arbor, Michigan to implement our framework. We use several quantitative measures as well as illustrations to validate our model. We further discuss how the RDP framework can be used to develop network-level and individual vehicle-level insurance and safety focused applications.

Development of Steering Control System for Autonomous Vehicle

Automation can help us to reduce the number of crashes on our roads. Through research it is identified that 94 percent of the accidents that occur are because of driver behavior or error as a factor and self-driving vehicles can help reduce driver error. High levels of automation have the potential to reduce risky and dangerous driver behavior and prevent accidents. The main aim is to convert the manual operated steering of the vehicle into fully autonomous steering. The objective of Steering Control System is to control the vehicle’s steering while the vehicle is in motion and also to take accurate decisions while making a turn from the given inputs. The main purpose to develop a steering system for the autonomous vehicle is to replace the manual steering of the vehicle into driverless steering. The steering control is responsible for the vehicle’s steering i.e., at what desired angle the vehicle need to turn. A PID (Proportional Integral Derivative) controller and an encoder is basically used to control the system based on the necessary conditions and requirement’s. For the vehicle’s steering the encoder is used to generate pulses when the steering wheel is turned so that those pulse values can be sent to the DC Motor which is attached to the front axle which is responsible for the vehicle to turn. This autonomous vehicle is a Level-4 automation system and the benefit of this automation is that the vehicle can be even operated in manual mode whenever it’s necessary.

Development and Validation of Psychological Fitness to Drive Scale for Filipinos

AbstractRoad transportation for Filipinos is a daily task that subjects an individual to risks and dangers, leading to damages and deaths annually, this leads to developing and validating a Psychological Fitness to Drive Scale for Filipinos (PFDSF) to assess Filipino drivers’ mental readiness and save lives. Via test development, 154 items were generated after a rigorous process of conceptualization and item generation from pre-survey, interviews, and related literature with English and Filipino test booklets as delivered to 102 participants for pilot testing. Online field testing was delivered due to the COVID-19 pandemic. About 463 samples went through a series of factor analyses to determine the existing factors and retain highly relevant items, resulting in two factors namely, Risky Driving Behavior (RDB) with 50 items (α=0.968), and Responsible and Safe Mobility (RSM) having 22 items (α=0.915), for a total of 72 items. PFDSF was found to be psychometrically sound with validity in its content, construct, factors, and high reliability (α=0.967). Future researchers are invited to use the scale and explore other areas for utility with specific population, age, gender, exploration of a social desirability factor, further strengthening of its criterion, convergent and divergent validity considering computer-assisted online version its localization to different major dialects.Keywords: Psychological fitness to drive, test development and validation, Filipino drivers, road safety and traffic psychology

The Prevalence of Several Risky Driving Behaviors and Associated Crash Risk in Adolescent: A Population-Based Study of Tuscany Region.

Objectives: To evaluate the prevalence of numerous risky driving behaviors (RDBs) and the associated risk of road traffic accidents (RTA) in a population-based sample of adolescent drivers (14–19 years) of Tuscany, Italy. Methods: The frequency of participation -by age and sex- often RDBs were investigated: Multivariable analyses were performed to evaluate the association between RDBs and the risk of RTA and severe RTA. Results: 2,737 adolescents were included in the study. Talking to passenger(s), listening to loud music, speeding, and texting showed the highest weekly participation rates. For all the considered RDBs, the frequency of participation significantly increased with age. Males reported a significantly higher participation in speeding, DUI of alcohol or drugs; while females reported listening to loud music and talking to passenger(s) more frequently. All the considered RDBs were significantly associated with the risk of RTA and severe RTA. Conclusion: The prevalence of RDBs and the associated risk of RTA largely varied in adolescents. Findings provide evidence for tailoring prevention interventions and suggest the need to include common- but traditionally overlooked- RDBs in road safety campaigns.

Difficulties in Emotion Regulation and Optimistic Bias in Young Drivers’ Risky Driving Behaviors

Risky driving behavior is the most dominant human error among young novice drivers. This research's objective was to find the correlation between difficulties in emotion regulation and optimistic bias towards risky driving behavior of teenagers. Sample was Senior High School students from grade 10 to 11 S who drove private vehicles on a daily basis (N=160). Instruments used were modified Behavior of Young Novice Drivers' Scale (BYNDS), modified Difficulties in Emotion Regulation Scale (DERS) and optimistic bias scale. Hypotheses were tested using multiple regression analysis. Results showed that there was a positive and significant correlation between difficulties in emotion regulation and optimistic bias towards risky driving behavior (F (2, 157) = 47.846; p < .01). Bigger contribution was found on difficulties in emotion regulation, indicating that teenagers while driving, relied more on their emotion regulation abilities than their awareness of driving risks.

Born to Be a Risky Driver? The Relationship Between Cloninger's Temperament and Character Traits and Risky Driving.

Temperament refers to basic, largely inherited, relatively stable personality traits which have been present since early childhood. Considering the very fundamental role of temperament in human development and behaviour, it is reasonable to assume that temperament is also related to risky driving and drivers’ view of themselves as drivers. The aim of the present study was to investigate the relationships between Cloninger’s temperament dimensions, risky driving and drivers’ view of their perceptual motor and safety skills. The sample consisted of 335 Turkish drivers (aged 19–57; 53.7% men) who completed an Internet-based survey including Temperament and Character Inventory (TCI), Driver Behaviour Questionnaire (DBQ) and Driver Skill Inventory (DSI). Correlation analyses showed that TCI scale Cooperativeness correlated negatively with all DBQ scales indicating risky driving and positively with safety skills. In regression analyses after controlling age, gender and lifetime mileage, cooperativeness still was significantly related to all DBQ scales and safety skills. Persistence correlated negatively with ordinary violations, lapses and errors and positively with perceptual motor skills. In regression analyses, persistence was related to errors and lapses. Reward dependence was positively related to lapses and harm avoidance negatively to perceptual motor skills. The results of the present study indicate that largely innate temperament character traits may influence an individual’s predisposition to risky driving. Future studies about temperament and risky driving with larger samples allowing sub-group analyses are needed.

Organisational Safety Climate, Professional Driver Behaviours, and Crashes Among a Mixed Group of Professional Drivers

The current study compared different driver groups and investigated the relationship between safety climate, driver behaviours, and crashes in a mixed group of professional drivers in Turkey. Two hundred and sixty drivers completed the scales developed explicitly for professional drivers, Transportation Companies’ Climate Scale and Occupational Driver Behaviour Questionnaire, along with the demographic form. Freight drivers scored higher on risky driver behaviours than passenger vehicle drivers. Organisational safety climate predicted driver behaviours. When the organisations are more sensitive regarding work and time pressure issues (low level of pressure), drivers are less likely to speed, violate the rules, and get tired. Additionally, risky driver behaviours were related to more crashes. Specifically, driving while tired positively predicted crashes after controlling for the effects of age and annual mileage. Altogether, a favourable safety climate predicted safer driving behaviours, which was found to be related to fewer crashes. The results were discussed in detail.

Peer pressure and risky driving: Development of a new scale

Introduction: Peer pressure is a main factor influencing risky driving behavior in young people. Most empirical studies have focused either on direct or indirect peer pressure, and comprehensive measures assessing both are currently lacking. The present study aimed at developing and validating a scale to examine the influence of different types of peer pressure on risky driving in young drivers: the Peer Pressure on Risky Driving Scale (PPRDS). Method: Scale construction and assessment of its psychometric properties involved four phases: item development, assessment of content validity by expert reviewers, pre-testing of the scale and evaluation of psychometric properties of the final version in a sample of 773 young drivers aged 18–29. Results: Confirmatory factor analysis supported a three-factor structure that reflected the multifaceted definition of peer pressure on risky driving in the immediate driving context: risk-encouraging direct peer pressure; risk-discouraging direct peer pressure, and indirect pressure. The three factor scales showed good internal consistency and construct reliability, and correlated as expected with self-reported risky driving. Younger drivers (18–24) reported more direct and indirect peer pressure to engage in risky driving. Males indicated more direct peer pressure towards risky driving. Finally, interaction effects between age and sex were observed. Young male drivers reported the greatest direct peer pressure and adult female drivers the lowest direct peer pressure. Conclusions: The 23-item PPRDS scale has good psychometric properties and provides a useful tool for assessing different forms of peer pressure on risky driving. Practical Applications: The PPRDS can be used for evaluating the impact of peer-based education and road safety programs. The scale also provides valuable information for the design of evidence-based intervention.

Self-Assessed Driving Skills and Risky Driver Behaviour Among Young Drivers: A Cross-Sectional Study.

The first few years of driving is a critical period when driving skills develop and the driving style is established. While the actual driving skills improve during the first few years of driving, a novice driver’s view of himself/herself as a safe and/or skilful driver also develops rapidly. The aim of this study was to investigate self-evaluated driver safety and perceptual-motor skills among different age groups of young drivers, along with the relationships between self-evaluated skills and driving behaviour. The sample consisted of a stratified random sample of 18–25-year-old drivers from the Finnish driving licence register. The questionnaires, which included the Driver Skill Inventory (DSI), Driver Behaviour Questionnaire (DBQ) and background information, were completed and returned by a total of 1,058 participants. While female drivers assessed their safety skills to be higher than their perceptual-motor skills, the opposite was true for males. In both sexes, perceptual-motor skills increased, and safety skills decreased with experience. Perceptual-motor skills correlated negatively with safety skills, lapses and errors, but positively with aggressive and ordinary violations. Safety skills correlated negatively with all DBQ variables. Safety orientation seems to be most clearly reflected in deliberate aberrant driving behaviours. Sex differences were observed in the development of behaviours and skills, perceptual-motor skills only increased with age among males, while safety skills decreased through experience among both men and women. Results showed that driving experience was strongly related to both driving style (violations, errors) and the drivers’ view of their skills (safety orientation), highlighting the importance of the first few years of driving.

Differences in the Assessment of Safe and Risky Driving Behaviors: Pedestrians Versus Drivers

Interactions between pedestrians and drivers are an important traffic safety issue. Psycho-social factors such as thoughts, perceptions and attitudes toward other people can be reliable predictors of riskier or safer behaviors among road users. The aim of this study was to assess how frequently participants perceive that drivers perform safe and risky road behaviors through drivers’ self-reported behavior and pedestrians and other drivers’ external perceptions. The results show that pedestrians assess the road behaviors of drivers in a seriously negative way. Meanwhile, drivers perceive their own behaviors as more appropriate than those performed by the rest of drivers. Women attribute more favorable assessments to other users’ road behavior. Similarly, older drivers do the same, and consider themselves “safer” users. On the contrary, younger drivers report a higher frequency of self-rated unsafe behaviors. The study highlights the importance of working on the awareness of self-rated road behaviors. Road safety interventions and programs in Spain must consider the differences related to gender and age.

The Effects of Personality and Attitude on Risky Driving Behavior Among Public van Drivers: Hierarchical Modeling

BackgroundTraffic injuries have become a significant public health problem in low- and middle-income countries. Several studies have examined the role of personality and attitude toward traffic safety in predicting driving behaviors in diverse types of drivers. Few studies have investigated risky behavior among public passenger van drivers. This study aims to identify the predictors of self-reported risky driving behavior among public van drivers. MethodA total of 410 public van drivers were interviewed at terminal stations in Bangkok. Hierarchical regression models were applied to determine the effects of demographics, personality traits, and attitude on self-reported risky driving behaviors. ResultsThe results indicated that drivers with a high education level, more working days, and high scores for normlessness and anger were more likely to report risky driving behaviors (p < 0.05). ConclusionThe personality traits and attitude toward speeding account for aberrant self-reported risky driving behavior in passenger van drivers. This could be another empirical basis for evidence-based road safety interventions in the context of public transport.

Multistate Pilot Study Evaluating the Short-Term Efficacy of a Smartphone-Based Older Driver Support System on Modifying Risky Driving Behaviors

Older drivers are most at risk of serious and fatal injury in crashes per vehicle mile driven compared with other age groups owing to a combination of cognitive decline and increased fragility. A smartphone coaching application targeting risky driving behaviors (e.g., speeding, hard braking), was iteratively designed to ensure older driver acceptance and usability. A 12-week field operational test examined driving performance of 28 drivers aged 65 to 78 from Kansas and Minnesota using the RoadCoach app and an ABA reversal design. Participants’ baseline driving behaviors were recorded for 3 weeks, followed by a 6-week experimental phase of real-time app coaching, and concluded with a 3-week baseline phase with no feedback provided. Compared with the pretreatment phase, there was a significant reduction in the rates of hard braking and stop sign violations associated with system use. A protection effect was observed through the posttreatment phase. Excessive speeding violations were not significantly different across the phases; however, there were modest declines in the proportion of miles traveled 15 mph above the speed limit in the posttreatment phase compared with the prior two phases. No significant effect was found for excessive acceleration and aggressive turning measures posttreatment, despite an observed increase in both rates during the treatment phase compared with pretreatment. Overall, the results indicate that the RoachCoach app may be an effective intervention to reduce several risky driving behaviors while in use and may result in prolonged behavior changes (i.e., reduced hard braking and stop sign violations) after treatment cessation.

Analysis of Risky Driving Behavior of Urban Electric Bicycle Drivers for Improving Safety

In this work, to clarify the impact of electric bicycle drivers’ risky driving behavior on driving safety, we used multiple regression analysis methods combined with a questionnaire survey of residents of the city of Guilin, China. We studied the impact of the two dimensions of safety knowledge and safety attitude on risky driving behavior, and identified the differences in the impact of these two dimensions from the perspective of personal characteristics. Through modeling analysis, we found that “responsible attitude” and “group behavior attitude” explain 62.4% of the variation in aggressive behavior; 48.5% of the variation in negligent behavior is caused by “age”, “safety knowledge” and “responsible attitude”; and 52% of the variation in violations is caused by “age”, “violation attitude” and “group behavior attitude”. The results show that “group behavior attitude” affects the occurrence of aggression; that safety knowledge has a significant negative impact on unintentional negligence but has no significant effect on deliberate violations and aggression; and that the difference in risky driving behavior is mainly manifested in “age”, “gender”, “violation” and “accident experience”.

Association Between Suicidality and Risky Driving Among US Adolescents—Results From the 2019 Youth Risk Behavior Survey

Association Between Suicidality and Risky Driving Among US Adolescents—Results From the 2019 Youth Risk Behavior Survey

Identification of Factors Causing Risky Driving Behavior on High-speed Multi-lane Highways in India Through Principal Component Analysis

In developing countries like India, Multilane high-speed National Highways (NHs) are victims of high accident rates. The Indian National Highway network comprises only 2% of the Indian road network, but transports 40% of traffic, resulting in traffic accidents on National Highways. As observed from past studies, drivers are the main responsible factors for accident causation due to their risky behavior. Hence, to determine significant factors causing the risky behavior of drivers on multi-lane high-speed highways, the personal interview survey through questionnaire was conducted for the road users of NH-47 comprising of the responses to the drivers' demographics, attitude towards vehicle condition and maintenance, traffic regulations/ enforcement following attitude characteristics, and roadway environment characteristics. Principal component analysis (PCA) was applied to the questionnaire variables, and significant category-wise variables for risky driving were identified. Fifteen important variables contributed to risky driving behavior from the questionnaire database by PCA. They are Roadway environment characteristics like improper signals, roadside accident prevention infrastructure, improper pavement, and no safe crossing points; Driver's age and experience; Using mirrors while overtaking, using lights and dipper during night-time, and using hand signals during daytime; Using helmets and seatbelts while driving and having a valid vehicle insurance policy; age of the vehicles, vehicle service frequency, and lane preference in their decreasing significance based on the questionnaire database. The authorities can take suitable measures to control the significant variables causing risky driving behavior on high speed multi-lane highways and reduce the accidents scenarios on the multilane highways.

The Predictive Role of Gender, Age, and Personality Organization in Risky Driving

The Predictive Role of Gender, Age, and Personality Organization in Risky Driving

Personalised Driving Safety: Using Telematics to Reduce Risky Driving Behaviour Among Young Drivers

Personalised Driving Safety: Using Telematics to Reduce Risky Driving Behaviour Among Young Drivers

Driving Self-Regulation and Risky Driving Outcomes

Driving Self-Regulation and Risky Driving Outcomes