scholarly journals Evaluation of an in-vehicle monitoring system (IVMS) to reduce risky driving behaviors in commercial drivers: Comparison of in-cab warning lights and supervisory coaching with videos of driving behavior

2017 ◽  
Vol 60 ◽  
pp. 125-136 ◽  
Author(s):  
Jennifer L. Bell ◽  
Matthew A. Taylor ◽  
Guang-Xiang Chen ◽  
Rachel D. Kirk ◽  
Erin R. Leatherman
Keyword(s):  
Monitoring System ◽  
Driving Behavior ◽  
Risky Driving ◽  
Vehicle Monitoring ◽  
Driving Behaviors ◽  
Commercial Drivers ◽  
Risky Driving Behaviors ◽  
Warning Lights

scholarly journals Understanding Traffic Accidents among Young Drivers in Qatar

2022 ◽  
Vol 19 (1) ◽  
pp. 514
Author(s):  
Faris Tarlochan ◽  
Mohamed Izham Mohamed Ibrahim ◽  
Batool Gaben
Keyword(s):  
Traffic Accidents ◽  
Corrective Feedback ◽  
Risky Behaviors ◽  
Driving Behavior ◽  
Self Report ◽  
Measurement Scales ◽  
Risky Driving ◽  
Driving Behaviors ◽  
Young Drivers ◽  
Risky Driving Behaviors

Young drivers are generally associated with risky driving behaviors that can lead to crash involvement. Many self-report measurement scales are used to assess such risky behaviors. This study is aimed to understand the risky driving behaviors of young adults in Qatar and how such behaviors are associated with crash involvement. This was achieved through the usage of validated self-report measurement scales adopted for the Arabic context. A nationwide cross-sectional and exploratory study was conducted in Qatar from January to April 2021. Due to the Covid-19 pandemic, the survey was conducted online. Therefore, respondents were selected conveniently. Hence, the study adopted a non-probability sampling method in which convenience and snowball sampling were used. A total of 253 completed questionnaires were received, of which 57.3% were female, and 42.7% were male. Approximately 55.8% of these young drivers were involved in traffic accidents after obtaining their driving license. On average, most young drivers do have some risky driving behavior accompanied by a low tendency to violate traffic laws, and their driving style is not significantly controlled by their personality on the road. The older young drivers are more involved in traffic accidents than the younger drivers, i.e., around 1.5 times more likely. Moreover, a young male driver is 3.2 times less likely to be involved in traffic accidents than a female driver. In addition, males are only 0.309 times as likely as females to be involved in an accident and have approximately a 70% lower likelihood of having an accident versus females. The analysis is complemented with the association between young drivers’ demographic background and psychosocial-behavioral parameters (linking risky driving behavior, personality, and obligation effects on crash involvement). Some interventions are required to improve driving behavior, such as driving apps that are able to monitor and provide corrective feedback.

scholarly journals Implementing Surrogate Safety Measures in Driving Simulator and Evaluating the Safety Effects of Simulator-Based Training on Risky Driving Behaviors

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Eunhan Ka ◽  
Do-Gyeong Kim ◽  
Jooneui Hong ◽  
Chungwon Lee
Keyword(s):  
Driving Simulator ◽  
Driver Education ◽  
Risky Driving ◽  
Safety Measures ◽  
Novice Drivers ◽  
Elderly Drivers ◽  
Driving Behaviors ◽  
Commercial Drivers ◽  
Surrogate Safety Measures ◽  
Risky Driving Behaviors

Human errors cause approximately 90 percent of traffic accidents, and drivers with risky driving behaviors are involved in about 52 percent of severe traffic crashes. Driver education using driving simulators has been used extensively to obtain a quantitative evaluation of driving behaviors without causing drivers to be at risk for physical injuries. However, since many driver education programs that use simulators have limits on realistic interactions with surrounding vehicles, they are limited in reducing risky driving behaviors associated with surrounding vehicles. This study introduces surrogate safety measures (SSMs) into simulator-based training in order to evaluate the potential for crashes and to reduce risky driving behaviors in driving situations that include surrounding vehicles. A preliminary experiment was conducted with 31 drivers to analyze whether the SSMs could identify risky driving behaviors. The results showed that 15 SSMs were statistically significant measures to capture risky driving behaviors. This study used simulator-based training with 21 novice drivers, 16 elderly drivers, and 21 commercial drivers to determine whether a simulator-based training program using the SSMs is effective in reducing risky driving behaviors. The risky driving behaviors by novice drivers were reduced significantly with the exception of erratic lane-changing. In the case of elderly drivers, speeding was the only risky driving behavior that was reduced; the others were not reduced because of their difficulty with manipulating the pedals in the driving simulator and their defensive driving. Risky driving behaviors by commercial drivers were reduced overall. The results of this study indicated that the SSMs can be used to enhance drivers’ safety, to evaluate the safety of traffic management strategies as well as to reduce risky driving behaviors in simulator-based training.

scholarly journals The Role of Impulsivity, Attentional bias and Decision-Making Styles in Risky Driving Behaviors

2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Fatemeh Barati ◽  
Abbas Pourshahbaz ◽  
Masoud Nosratabadi ◽  
Zahra Mohammadi
Keyword(s):  
Decision Making ◽  
Attentional Bias ◽  
Pearson Correlation ◽  
Driving Behavior ◽  
Pearson Correlation Coefficient ◽  
Road Accidents ◽  
Risky Driving ◽  
Driving Behaviors ◽  
Decision Making Styles ◽  
Risky Driving Behaviors

Background: Road accidents are a major cause of deaths, injuries, and financial losses globally, especially in developing countries. Iran is one of the countries with a high rate of road accidents causing considerable damage in different domains. Therefore, in order to tackle this problem, we need to examine its causes. Objectives: The aim of the present study was to examine the association of risky driving behavior with impulsiveness, attentional bias, and decision-making styles. Patients and Methods: This was a descriptive-correlational study. The sample included 117 male drivers, aged 20 - 34 years, attending car insurance agencies in Tehran. The participants were selected using the convenience sampling method. The data were gathered using the Manchester Driver Behavior Questionnaire (DBQ), the Barratt Impulsiveness Scale (BIS), the Decision-Making Style Scale (DMS), and the Dot Probe Task to assess attentional bias. All data analysis was conducted using Pearson correlation coefficient and multiple regression analysis, by using SPSS, version 22. Results: According to the results of the Pearson correlation coefficient, risky driving behavior was significantly correlated with impulsiveness subscales (P < 0.01) and attentional bias (P < 0.05). In addition, significant relationships were observed between risky driving behaviors and three decision-making styles, including rational (P < 0.05), spontaneous (P < 0.01), and avoidant (P < 0.01). Conclusions: Based on the study results, impulsivity, decision-making styles, and attentional bias as factors influencing drivers’ cognitive skills related to driving, could explain the increase in the frequency of risky driving behavior.

Using Real-Time and Post Hoc Feedback to Improve Driving Safety for Novice Drivers

2016 ◽  
Vol 60 (1) ◽  
pp. 1936-1940 ◽  
Author(s):  
Sheila G. Klauer ◽  
Tina B. Sayer ◽  
Peter Baynes ◽  
Gayatri Ankem
Keyword(s):  
Real Time ◽  
Motor Vehicle ◽  
Driving Behavior ◽  
Driving Safety ◽  
Risky Driving ◽  
Novice Drivers ◽  
Safe Driving ◽  
Driving Behaviors ◽  
Post Hoc ◽  
Risky Driving Behaviors

Introduction. Motor vehicle crashes remain the leading cause of fatalities among teens in the U.S. (National Center for Injury Prevention and Control, 2013). Prior research suggests that real-time and post hoc feedback can improve teen driver behavior. The Driver Coach Study (DCS) aimed to improve teens’ safe driving habits by providing them real-time feedback and post hoc feedback to a broader range of risky driving behaviors that have never been used in previous studies. Exposure data were also collected so that rates of risky driving behaviors over time could be assessed. Post hoc feedback, which included an electronic report card of risky driving behavior as well as video clips, was provided to both teens and parents via email and secure website link. Method. Ninety-two teen/parent dyads were recruited in southwest Virginia to have a data acquisition system (DAS) installed in their vehicles within two weeks of receiving their learner’s permit. Data were collected through the nine-month (minimum) learner’s permit phase plus seven months of provisional licensure. Feedback was only provided for the first six months of post licensure, then turned off to assess whether teenagers returned to unsafe driving behavior. Trained data coders reviewed 15 seconds of video surrounding each risky driving maneuver, and recorded driver errors such as poor vehicle control, poor speed selection, drowsiness, etc., for each event. Results. In this paper, the relationship between driver coaching and driver errors will be examined across the six-month feedback phase and also compared to the seventh month when feedback was turned off. Conclusions. This study has implications for the design of future monitoring and feedback systems, as it is currently unknown whether these devices can improve novice drivers’ crash rates.

scholarly journals Drivers’ Risk Perception and Risky Driving Behavior under Low Illumination Conditions: Modified Driver Behavior Questionnaire (DBQ) and Driver Skill Inventory (DSI)

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jing Liu ◽  
Cheng Wang ◽  
Zhipeng Liu ◽  
Zhongxiang Feng ◽  
N. N. Sze
Keyword(s):  
Risk Perception ◽  
Driver Behavior ◽  
Positive Influence ◽  
Driving Behavior ◽  
Risky Driving ◽  
Driving Experience ◽  
Driving Behaviors ◽  
Driving Skills ◽  
Low Illumination ◽  
Risky Driving Behaviors

Most road crashes are caused by human factors. Risky behaviors and lack of driving skills are two human factors that contribute to crashes. Considering the existing evidence, risky driving behaviors and driving skills have been regarded as potential decisive factors explaining and preventing crashes. Nighttime accidents are relatively frequent and serious compared with daytime accidents. Therefore, it is important to focus on driving behaviors and skills to reduce traffic accidents and enhance safe driving in low illumination conditions. In this paper, we examined the relation between drivers’ risk perception and propensity for risky driving behavior and conducted a comparative analysis of the associations between risk perception, propensity for risky driving behavior, and other factors in the presence and absence of streetlights. Participants in Hefei city, China, were asked to complete a demographic questionnaire, the Driver Behavior Questionnaire (DBQ), and the Driver Skill Inventory (DSI). Multiple linear regression analyses identified some predictors of driver behavior. The results indicated that both the DBQ and DSI are valuable instruments in traffic safety analysis in low illumination conditions and indicated that errors, lapses, and risk perception were significantly different between with and without streetlight conditions. Pearson’s correlation test found that elderly and experienced drivers had a lower likelihood of risky driving behaviors when driving in low illumination conditions, and crash involvement was positively related to risky driving behaviors. Regarding the relationship between study variables and driving skills, the research suggested that age, driving experience, and annual distance were positively associated with driving skills, while myopia, penalty points, and driving self-assessment were negatively related to driving skills. Furthermore, the differences across age groups in errors, lapses, violations, and risk perception in the presence of streetlights were remarkable, and the driving performance of drivers aged 45–55 years was superior to that of drivers in other age groups. Finally, multiple linear regression analyses showed that education background and crash involvement had a positive influence on error, whereas risk perception had a negative effect on errors; crash involvement had a positive influence, while risk perception had a negative effect on lapse; driving experience and crash involvement had a positive influence on violation; and age had a negative influence on it.

scholarly journals Driving Behavior Based Relative Risk Evaluation Using a Nonparametric Optimization Method

2021 ◽  
Vol 18 (23) ◽  
pp. 12452
Author(s):  
Qiong Bao ◽  
Hanrun Tang ◽  
Yongjun Shen
Keyword(s):  
Relative Risk ◽  
Risk Evaluation ◽  
Absolute Risk ◽  
Evaluation Model ◽  
Optimization Method ◽  
Driving Behavior ◽  
Risky Driving ◽  
Driving Behaviors ◽  
Proposed Model ◽  
Risky Driving Behaviors

Evaluating risks when driving is a valuable method by which to make people better understand their driving behavior, and also provides the basis for improving driving performance. In many existing risk evaluation studies, however, most of the time only the occurrence frequency of risky driving events is considered in the time dimension and fixed weights allocation is adopted when constructing a risk evaluation model. In this study, we develop a driving behavior-based relative risk evaluation model using a nonparametric optimization method, in which both the frequency and the severity level of different risky driving behaviors are taken into account, and the concept of relative risk instead of absolute risk is proposed. In the case study, based on the data from a naturalistic driving experiment, various risky driving behaviors are identified, and the proposed model is applied to assess the overall risk related to the distance travelled by an individual driver during a specific driving segment, relative to other drivers on other segments, and it is further compared with an absolute risk evaluation. The results show that the proposed model is superior in avoiding the absolute risk quantification of all kinds of risky driving behaviors, and meanwhile, a prior knowledge on the contribution of different risky driving behaviors to the overall risk is not required. Such a model has a wide range of application scenarios, and is valuable for feedback research relating to safe driving, for a personalized insurance assessment based on drivers’ behavior, and for the safety evaluation of professional drivers such as ride-hailing drivers.

Perceived Self-Efficacy and Risky Driving Behaviors

2010 ◽  
Vol 69 (4) ◽  
pp. 233-238 ◽  
Author(s):  
Nolwenn Morisset ◽  
Florence Terrade ◽  
Alain Somat
Keyword(s):  
Self Efficacy ◽  
Risky Driving ◽  
Driving Behaviors ◽  
Conduite Automobile ◽  
Risky Driving Behaviors

Les recherches dans le domaine de la santé, et notamment en matière de conduite automobile, attestent que le jugement subjectif du risque (comparatif et absolu) et l’auto-efficacité perçue sont impliqués dans les comportements à risque. Cette étude avait pour objectif d’étudier l’influence de l’auto-efficacité perçue sur le jugement subjectif du risque, évalué au moyen d’une mesure indirecte, et de tester le rôle médiateur de ce facteur entre l’auto-efficacité perçue et les comportements auto-déclarés. Les participants, 90 hommes, lisaient deux scénarii décrivant les deux comportements les plus impliqués dans l’accidentologie: la vitesse et l’alcool au volant. Les résultats ne montrent pas de lien significatif entre l’auto-efficacité perçue et le score de jugement comparatif mais une relation significative avec les deux évaluations absolues du risque (autrui et soi). De plus, le jugement absolu du risque pour soi médiatise partiellement la relation entre auto-efficacité perçue et comportements auto-déclarés relatifs aux deux risques routiers étudiés.

scholarly journals Examining Risky Driving Behavior Among Older Drivers Using Self-Reported and Objective Data

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 465-465
Author(s):  
Jennifer Zakrajsek ◽  
Lisa Molnar ◽  
David Eby ◽  
David LeBlanc ◽  
Lidia Kostyniuk ◽  
...  
Keyword(s):  
Motor Vehicle ◽  
Seat Belt ◽  
Driving Behavior ◽  
Video Data ◽  
Older Drivers ◽  
Driving Frequency ◽  
Middle Aged ◽  
Risky Driving ◽  
Driving Behaviors ◽  
Study Results

Abstract Motor vehicle crashes represent a significant public health problem. Efforts to improve driving safety are multifaceted, focusing on vehicles, roadways, and drivers with risky driving behaviors playing integral roles in each area. As part of a study to create guidelines for developing risky driving countermeasures, 480 drivers (118 young/18-25, 183 middle-aged/35-55, 179 older/65 and older) completed online surveys measuring driving history, risky driving (frequency of engaging in distracted [using cell phone, texting, eating/drinking, grooming, reaching/interacting] and reckless/aggressive [speeding, tailgating, failing to yield right-of-way, maneuvering unsafely, rolling stops] driving behaviors), and psychosocial characteristics. A cluster analysis using frequency of the risky behaviors and seat belt use identified five risky behavior-clusters: 1) rarely/never distracted-rarely/never reckless/aggressive (n=392); 2) sometimes distracted-rarely/never reckless/aggressive (n=33); 3) sometimes distracted-sometimes reckless/aggressive (n=40); 4) often/always distracted-often/always reckless/aggressive (n=11); 5) no pattern (n=4). Older drivers were more likely in the first/lowest cluster (93.8% of older versus 84.2% of middle-aged and 59.3% of young drivers; p&lt;.0001). Fifteen older drivers participated in a follow-up study in which their vehicles were equipped with a data acquisition system that collected objective driving and video data of all trips for three weeks. Analysis of video data from 145 older driver trips indicated that older drivers engaged in at least one distracted behavior in 115 (79.3%) trips. While preliminary, this suggests considerably more frequent engagement in distracted driving than self-reported and that older drivers should not be excluded from consideration when developing risky driving behavior countermeasures. Full study results and implications will be presented.

scholarly journals Risky driving behaviors for road traffic accident among drivers in Mekele city, Northern Ethiopia

2011 ◽  
Vol 4 (1) ◽  
pp. 535 ◽  
Author(s):  
Abrahim Hassen ◽  
Ameyu Godesso ◽  
Lakew Abebe ◽  
Eshetu Girma
Keyword(s):  
Road Traffic Accident ◽  
Traffic Accident ◽  
Road Traffic ◽  
Northern Ethiopia ◽  
Risky Driving ◽  
Driving Behaviors ◽  
Risky Driving Behaviors
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