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Artykuły w czasopismach na temat „Risky Driving”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 20 lutego 2023

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1

Leal, Nerida, Barry Watson, and Kerry Armstrong. "Risky Driving or Risky Drivers?" Transportation Research Record: Journal of the Transportation Research Board 2182, no. 1 (January 2010): 16–23. http://dx.doi.org/10.3141/2182-03.

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Chen, Shengdi, Qingwen Xue, Xiaochen Zhao, Yingying Xing, and Jian John Lu. "Risky Driving Behavior Recognition Based on Vehicle Trajectory." International Journal of Environmental Research and Public Health 18, no. 23 (November 24, 2021): 12373. http://dx.doi.org/10.3390/ijerph182312373.

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This paper proposes a measurement of risk (MOR) method to recognize risky driving behavior based on the trajectory data extracted from surveillance videos. Three types of risky driving behavior are studied in this paper, i.e., speed-unstable driving, serpentine driving, and risky car-following driving. The risky driving behavior recognition model contains an MOR-based risk evaluation model and an MOR threshold selection method. An MOR-based risk evaluation model is established for three types of risky driving behavior based on driving features to quantify collision risk. Then, we propose two m

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Măirean, Cornelia, Grigore M. Havârneanu, Danijela Barić, and Corneliu Havârneanu. "Cognitive Biases, Risk Perception, and Risky Driving Behaviour." Sustainability 14, no. 1 (December 22, 2021): 77. http://dx.doi.org/10.3390/su14010077.

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This study evaluated the relationship between drivers’ cognitive biases (i.e., optimism bias, illusion of control) and risky driving behaviour. It also investigated the mediational role of risk perception in the relationship between cognitive biases and self-reported risky driving. The sample included 366 drivers (Mage = 39.13, SD = 13.63 years) who completed scales measuring optimism bias, illusion of control, risk perception, and risky driving behaviour, as well as demographic information. The results showed that risky driving behaviour was negatively predicted by optimism bias and positivel

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Bao, Qiong, Hanrun Tang, and Yongjun Shen. "Driving Behavior Based Relative Risk Evaluation Using a Nonparametric Optimization Method." International Journal of Environmental Research and Public Health 18, no. 23 (November 26, 2021): 12452. http://dx.doi.org/10.3390/ijerph182312452.

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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

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Lazuras, Lambros, Richard Rowe, Antonia Ypsilanti, Isabelle Smythe, Damian Poulter, and John Reidy. "Driving self-regulation and risky driving outcomes." Transportation Research Part F: Traffic Psychology and Behaviour 91 (November 2022): 461–71. http://dx.doi.org/10.1016/j.trf.2022.10.027.

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Iversen, Hilde. "Risk-taking attitudes and risky driving behaviour." Transportation Research Part F: Traffic Psychology and Behaviour 7, no. 3 (May 2004): 135–50. http://dx.doi.org/10.1016/j.trf.2003.11.003.

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Li, Zhenming, Siu Shing Man, Alan Hoi Shou Chan, and Jianfang Zhu. "Integration of Theory of Planned Behavior, Sensation Seeking, and Risk Perception to Explain the Risky Driving Behavior of Truck Drivers." Sustainability 13, no. 9 (May 7, 2021): 5214. http://dx.doi.org/10.3390/su13095214.

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Truck-related accidents account for a substantial portion of traffic accidents. Risky driving behavior is a main cause of traffic accidents. Understanding the risky driving behavior of truck drivers is therefore important in reducing truck-related accidents. This study aimed to propose and validate a research model that integrated a theory of planned behavior, sensation seeking, and risk perception to explain the risky driving behavior of truck drivers. A total of 471 valid data were collected from Chinese truck drivers in this study. Structural equation modeling and mediation analysis were us

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Huh, Jason, and Julian Reif. "Teenage Driving, Mortality, and Risky Behaviors." American Economic Review: Insights 3, no. 4 (December 1, 2021): 523–39. http://dx.doi.org/10.1257/aeri.20200653.

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We investigate the effect of teenage driving on mortality and risky behaviors in the United States using a regression discontinuity design. We estimate that total mortality rises by 5.84 deaths per 100,000 (15 percent) at the minimum legal driving age cutoff, driven by an increase in motor vehicle fatalities of 4.92 deaths per 100,000 (44 percent). We also find that poisoning deaths, which are caused primarily by drug overdoses, rise by 0.31 deaths per 100,000 (29 percent) at the cutoff and that this effect is concentrated among females. Our findings show that teenage driving contributes to se

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Mas-Cuesta, Laura, Sabina Baltruschat, Antonio Cándido, and Andrés Catena. "Relationships between Personality Traits and Brain Gray Matter Are Different in Risky and Non-risky Drivers." Behavioural Neurology 2022 (April 5, 2022): 1–15. http://dx.doi.org/10.1155/2022/1775777.

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Personality traits such as impulsivity or sensitivity to rewards and punishments have been associated with risky driving behavior, but it is still unclear how brain anatomy is related to these traits as a function of risky driving. In the present study, we explore the neuroanatomical basis of risky driving behavior and how the level of risk-taking influences the relationship between the traits of impulsivity and sensitivity to rewards and punishments and brain gray matter volume. One hundred forty-four participants with different risk-taking tendencies assessed by real-life driving situations

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Ka, Eunhan, Do-Gyeong Kim, Jooneui Hong, and Chungwon Lee. "Implementing Surrogate Safety Measures in Driving Simulator and Evaluating the Safety Effects of Simulator-Based Training on Risky Driving Behaviors." Journal of Advanced Transportation 2020 (June 19, 2020): 1–12. http://dx.doi.org/10.1155/2020/7525721.

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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 sur

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Bonnett, Laura. "Driving is a risky business." Significance 18, no. 4 (July 28, 2021): 12–15. http://dx.doi.org/10.1111/1740-9713.01546.

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Jonah, Brian A. "Age differences in risky driving." Health Education Research 5, no. 2 (1990): 139–49. http://dx.doi.org/10.1093/her/5.2.139.

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Steinberg, Laurence. "Adolescents' Risky Driving in Context." Journal of Adolescent Health 49, no. 6 (December 2011): 557–58. http://dx.doi.org/10.1016/j.jadohealth.2011.10.001.

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Simons-Morton, Bruce G., Kaigang Li, Johnathon Ehsani, Marie Claude Ouimet, Jessamyn Perlus, and Sheila G. Klauer. "Are Perceptions About Driving Risk and Driving Skill Prospectively Associated with Risky Driving Among Teenagers?" Transportation Research Record: Journal of the Transportation Research Board 2584, no. 1 (January 2016): 39–44. http://dx.doi.org/10.3141/2584-06.

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Liu, Jing, Cheng Wang, Zhipeng Liu, Zhongxiang Feng, and N. N. Sze. "Drivers’ Risk Perception and Risky Driving Behavior under Low Illumination Conditions: Modified Driver Behavior Questionnaire (DBQ) and Driver Skill Inventory (DSI)." Journal of Advanced Transportation 2021 (November 19, 2021): 1–13. http://dx.doi.org/10.1155/2021/5568240.

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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’

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Ventsislavova, Petya, David Crundall, Pedro Garcia-Fernandez, and Candida Castro. "Assessing Willingness to Engage in Risky Driving Behaviour Using Naturalistic Driving Footage: The Role of Age and Gender." International Journal of Environmental Research and Public Health 18, no. 19 (September 28, 2021): 10227. http://dx.doi.org/10.3390/ijerph181910227.

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Young novice drivers are more prone than older drivers to get involved in a risky driving situation. Some young drivers underestimate risk while overestimating their driving abilities, increasing the likelihood of engaging in risky behaviour. Age and inexperience both influence risk estimation, though it is not clear which of these variables is more important. Can drivers’ willingness to engage in risky behaviour be assessed in a similar way to hazard perception skill using video-based risky situations? The aim of the current study was to assess whether a video-based tool could measure the wil

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17

Karlsson, G. "HOSPITALIZATION AND MORTALITY SUCCEEDING DRUNK DRIVING AND RISKY DRIVING." Alcohol and Alcoholism 38, no. 3 (May 1, 2003): 281–86. http://dx.doi.org/10.1093/alcalc/agg068.

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Kochetova, T. V., and G. Meinhard. "The Method for Evaluation of Driver’s Risky Traffic Behaviour: Validation in the Russian Sample." Social Psychology and Society 11, no. 3 (2020): 196–210. http://dx.doi.org/10.17759/sps.2020110313.

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Objectives. The purpose of the article is approbation the method for evaluation of drivers’ risky traffic behaviour, its structure and main patterns. Background. Psychological research of risky traffic behaviour of drivers is especially acute. It is a very important to measure and identify the features of the traffic behaviour of drivers as high-risk behaviour. In this context, the study of risky traffic behaviour is of particular interest. Study design. The structure and patterns of risky traffic behavior of three groups of Russian drivers with different driving experience were studied. It wa

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Kim, Jae Sung, Jong Bin Bae, Kyuhee Han, Jong Woo Hong, Ji Hyun Han, Tae Hui Kim, Kyung Phil Kwak, et al. "Driving-Related Adverse Events in the Elderly Men: A Population-Based Prospective Cohort Study." Psychiatry Investigation 17, no. 8 (August 25, 2020): 744–50. http://dx.doi.org/10.30773/pi.2019.0219.

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Objective This study estimated the incidence of driving-related adverse events and examined the association of cognitive function with the risk of future driving-related adverse events in the elderly Korean male population.Methods We analyzed 1,172 male drivers aged 60 years or older in the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD). Using the data from Korean National Police Agency, we classified the participants into three groups: safe driving (drove for 2 years after baseline without a traffic accident or repeated violations), driving cessation (stopped driving), an

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오주택 and 이상용. "Analysis of Risky Driving Pattern and Warning Effect by Risk Driving Judgment Device." Journal of Transport Research 17, no. 2 (June 2010): 139–41. http://dx.doi.org/10.34143/jtr.2010.17.2.139.

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Morgenroth, Thekla, Cordelia Fine, Michelle K. Ryan, and Anna E. Genat. "Sex, Drugs, and Reckless Driving." Social Psychological and Personality Science 9, no. 6 (September 19, 2017): 744–53. http://dx.doi.org/10.1177/1948550617722833.

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We investigated whether risk-taking measures inadvertently focus on behaviors that are more normative for men, resulting in the overestimation of gender differences. Using a popular measure of risk-taking (Domain-Specific Risk-Taking) in Study 1 ( N = 99), we found that conventionally used behaviors were more normative for men, while, overall, newly developed behaviors were not. In Studies 2 ( N = 114) and 3 ( N = 124), we demonstrate that differences in normativity are reflected in gender differences in self-reported risk-taking, which are dependent on the specific items used. Study 3 further

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Marks, Charles, Arash Jahangiri, and Sahar Ghanipoor Machiani. "Identifying and Labeling Potentially Risky Driving: A Multistage Process Using Real-World Driving Data." Journal of Advanced Transportation 2021 (February 13, 2021): 1–11. http://dx.doi.org/10.1155/2021/8819094.

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Every year, over 50 million people are injured and 1.35 million die in traffic accidents. Risky driving behaviors are responsible for over half of all fatal vehicle accidents. Identifying risky driving behaviors within real-world driving (RWD) datasets is a promising avenue to reduce the mortality burden associated with these unsafe behaviors, but numerous technical hurdles must be overcome to do so. Herein, we describe the implementation of a multistage process for classifying unlabeled RWD data as potentially risky or not. In the first stage, data are reformatted and reduced in preparation f

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Puspa Nirmala, Happy Virgina, and Bhina Patria. "Peran Regulasi Diri dan Konformitas terhadap Perilaku Berkendara Berisiko pada Remaja." Gadjah Mada Journal of Psychology (GamaJoP) 2, no. 2 (February 6, 2018): 113. http://dx.doi.org/10.22146/gamajop.33095.

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There are a number factors that contribute to the traffic accident at adolescents. One of them is the implementation of risky driving behaviour. The psychological factros that can be the predictors of risky driving behaviour are self-regulation and conformity. The aim of this research is to identify the factors’ role of risky driving behaviour at young novice drivers. The study involved adolescents aged 16 to 18 who were eligible subjects of the study. This study uses an adaptation of the Driving Behaviour Quetionnaire (DBQ) and The Czech Self-Regulation Quetionnaire (SRQ-Cz). Hypotheses of th

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Shams, Mohsen, and Vafa Rahimi-Movaghar. "Risky Driving Behaviors in Tehran, Iran." Traffic Injury Prevention 10, no. 1 (February 27, 2009): 91–94. http://dx.doi.org/10.1080/15389580802492280.

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Yuan, Yiran, Feng Du, Weina Qu, Wenguo Zhao, and Kan Zhang. "Identifying risky drivers with simulated driving." Traffic Injury Prevention 17, no. 1 (April 2, 2015): 44–50. http://dx.doi.org/10.1080/15389588.2015.1033056.

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Bina, Manuela, Federica Graziano, and Silvia Bonino. "Risky driving and lifestyles in adolescence." Accident Analysis & Prevention 38, no. 3 (May 2006): 472–81. http://dx.doi.org/10.1016/j.aap.2005.11.003.

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Yilmaz, Veysel, and H. Eray Çelik. "A MODEL FOR RISKY DRIVING ATTITUDES IN TURKEY." Social Behavior and Personality: an international journal 32, no. 8 (January 1, 2004): 791–96. http://dx.doi.org/10.2224/sbp.2004.32.8.791.

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Different research traditions have attempted to explain individual differences in risky driving behavior and traffic accident involvement. This study was designed to improve a model for risky driving attitudes (RDA) and to understand the mechanisms underlying drivers' risk-taking behavior in traffic. The questionnaire used in this study was composed of “the driver's behavior” questionnaire, improved by Reason, Manstead, Stradling, Baxter, and Campbell, (1990), and “the scales measuring attitudes and behavior” questionnaire, improved by Ulleberg and Rundmo (2003). The questionnaire survey was c

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Corte, Colleen M., and Marilyn S. Sommers. "Alcohol and Risky Behaviors." Annual Review of Nursing Research 23, no. 1 (January 2005): 327–60. http://dx.doi.org/10.1891/0739-6686.23.1.327.

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The purpose of this chapter is to review and critique the literature on risky drinking, driving, and sexual behaviors. To complete this review, electronic searches using databases from the disciplines of nursing, medicine, and psychology were used with keywords alcohol and risky behavior, risky drinking, risky driving, risky sex, and sexual aggression, as well as other relevant terms.The basic tenets of contemporary theoretical models of risky behaviors are used as a framework for reviewing the literature. Most relevant to the discussion are the relationships among the behaviors, risk and prot

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Craig, Curtis M., and Samuel J. Levulis. "The relationship between global and information processing factors and self-perceived risky driving among older adults." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1447–51. http://dx.doi.org/10.1177/1541931213601847.

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Drivers typically calibrate their driving behavior with their perceived risk of the current driving situation. However, the degree of risky behavior that drivers find acceptable may be affected by individual difference factors, such as gender, cognitive ability, and personality traits. Using a publicly available dataset examining cognitive and personality variables in a sample of older American adults (CogUSA; McArdle, Rodgers, & Willis, 2015), the present study assessed the relationships between global and information processing factors and self-perceived risky driving behavior (after con

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Gershon, Pnina, Johnathon P. Ehsani, Chunming Zhu, Kellienne R. Sita, Sheila Klauer, Tom Dingus, and Bruce Simons-Morton. "Crash Risk and Risky Driving Behavior Among Adolescents During Learner and Independent Driving Periods." Journal of Adolescent Health 63, no. 5 (November 2018): 568–74. http://dx.doi.org/10.1016/j.jadohealth.2018.04.012.

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Gershon, Pnina, and Bruce Simons-Morton. "Crash Risk and Risky Driving Behavior Among Adolescents During Learner and Independent Driving Periods." Journal of Adolescent Health 64, no. 5 (May 2019): 671–72. http://dx.doi.org/10.1016/j.jadohealth.2019.02.005.

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Rachmatunnisa, Firdha, and Sunu Bagaskara. "Peran Locus of Control dan Sikap Pro Risiko terhadap Perilaku Mengemudi Berisiko." Jurnal Penelitian Transportasi Darat 23, no. 2 (December 27, 2021): 135–41. http://dx.doi.org/10.25104/jptd.v23i2.1799.

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ABSTRACTThe Locus of Control’s Role and Pro Risk Attitude in Risky Driving Behavior: This study aims to determine whether the role of locus of control and pro-risk attitudes towards risky driving behavior. Using accidental sampling, this study involved 88 participants who were car drivers and motorcycle riders, and were male aged 18-25 years. The results of multiple linear regression analysis showed that the Traffic-Locus of Control scores of self dimensions and pro-risk attitudes together explain 35.2% variance of risky driving behavior. This finding indicates that road users who have a high

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Adira, Nesya, Machmuroch Machmuroch, and Pratista Arya Satwika. "Difficulties in Emotion Regulation and Optimistic Bias in Young Drivers’ Risky Driving Behaviors." Gadjah Mada Journal of Psychology (GamaJoP) 8, no. 1 (May 23, 2022): 95. http://dx.doi.org/10.22146/gamajop.72115.

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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 th

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Zakrajsek, Jennifer, Lisa Molnar, David Eby, Lidia Kostyniuk, Nicole Zanier, David J. LeBlanc, and Tina B. Sayer. "GUIDELINES FOR DEVELOPING EVIDENCE-BASED RISKY DRIVING COUNTERMEASURES THAT INCLUDE OLDER DRIVERS." Innovation in Aging 6, Supplement_1 (November 1, 2022): 164. http://dx.doi.org/10.1093/geroni/igac059.655.

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Abstract Driver behavior will continue to play a critical role in driving safety for the foreseeable future. Utilizing behavior change theory appropriately presents opportunities to improve the effectiveness of risky driving countermeasures that have been under-utilized to date. Older drivers should not be excluded from consideration of risky behaviors. Forty-six drivers (33% age 65+) completed surveys, then drove for three weeks with data collection during all trips. The Theory of Planned Behavior guided a two-phased regression analysis approach: 1) behavioral intentions were predicted using

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VLAICU, Claudia, and Felicia HAIDU. "THE PROFILE OF THE ROMANIAN AGGRESSIVE DRIVER." Pro Edu. International Journal of Educational Sciences 3, no. 5 (June 27, 2021): 81–95. http://dx.doi.org/10.26520/peijes.2021.5.3.81-95.

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Various studies have documented that aggressive driving is indeed a real problem. In each country there are various aspects of dangerous driving of empirical and practical concern and there are also individual differences to be explored. The present study aims at profiling the Romanian aggressive driver and questioning whether there are differences according to demographic variables such as: gender, age, area of living, marital status, religion, socio-economic status and level of instruction. An educational purpose may be nevertheless included. If psychologist may be provided with the profile

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Kidd, Pamela, and Sandra Huddleston. "Psychometric properties of the driving practices questionnaire: Assessment of risky driving." Research in Nursing & Health 17, no. 1 (February 1994): 51–58. http://dx.doi.org/10.1002/nur.4770170108.

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Venkatesh, Nandini, and Sumit Kumar. "Risky driving behaviour among the motorized two-wheeler novice riders in Davanagere city, Karnataka- Cross-sectional study." Indian Journal of Community Health 32, no. 1 (March 31, 2020): 133–36. http://dx.doi.org/10.47203/ijch.2020.v32i01.027.

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Introduction-Road traffic accidents (RTA) account for more significant mortality and morbidity rates worldwide, resulting in considerable global burden. In Indi, motor vehicle accidents are one of the common reasons for mortality among young riders. The present study provides insight into different aspects of risky driving behavior from individual attitudes, and psychological factors like anger, mood, and emotions. Methodology- A cross-sectional study was conducted among college students; findings from this study say young males are more involved in risky driving behavior. Results- Number of m

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Yang, Longhai, Xiqiao Zhang, Xiaoyan Zhu, Yule Luo, and Yi Luo. "Research on Risky Driving Behavior of Novice Drivers." Sustainability 11, no. 20 (October 9, 2019): 5556. http://dx.doi.org/10.3390/su11205556.

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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 mechani

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Murugan, N., C. Sagong, A. S. Cuamatzi Castelan, K. Moss, T. Roth, C. L. Drake, and P. Cheng. "0203 To and From the Night Shift: Risky On-the-Road Driving in Night Shift Workers." Sleep 43, Supplement_1 (April 2020): A79—A80. http://dx.doi.org/10.1093/sleep/zsaa056.201.

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Abstract Introduction Drowsy driving is a common occupational hazard for night shift workers (NSWs). While sleep loss is commonly identified as the primary culprit of drowsy driving, another critical factor to consider is circadian phase. However, the role of circadian phase in driving safety has not been well characterized in NSWs. This study examined if dim light melatonin offset (DLMOff, i.e. the cessation of melatonin secretion) is also a relevant phase marker of susceptibility to four different subtypes of risky on-the-road driving behaviors. Methods On-the-road driving was monitored over

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Farooq, Danish. "Statistical Evaluation of Risky Driver Behavior Factors that Influence Road Safety based on Drivers Age and Driving Experience in Budapest and Islamabad." European Transport/Trasporti Europei 80, ET.2020 (December 2020): 1–18. http://dx.doi.org/10.48295/et.2020.80.2.

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Driver behavior is considered as one of the most influential factors on road safety. Most of the drivers on road involve in risky driving attitudes which cause fatal and seriously injured road accidents. This study aims to evaluate and compare the risky driver behavior factors that influence road safety based on drivers age and driving experience for Budapest and Islamabad. To achieve this, the study utilized the well-proved driver behavior questionnaire (DBQ) designed on a three-point scale to analyse statistically the driver behavior responses on perceived road safety issues. The study overa

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Zhang, Fangda, Meng Wang, Jah’inaya Parker, and Shannon C. Roberts. "The Effect of Driving Style on Responses to Unexpected Vehicle Cyberattacks." Safety 9, no. 1 (January 31, 2023): 5. http://dx.doi.org/10.3390/safety9010005.

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Vehicle cybersecurity is a serious concern, as modern vehicles are vulnerable to cyberattacks. How drivers respond to situations induced by vehicle cyberattacks is safety critical. This paper sought to understand the effect of human drivers’ risky driving style on response behavior to unexpected vehicle cyberattacks. A driving simulator study was conducted wherein 32 participants experienced a series of simulated drives in which unexpected events caused by vehicle cyberattacks were presented. Participants’ response behavior was assessed by their change in velocity after the cybersecurity event

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Kalyoncuoglu, S. F., and M. Tigdemir. "Modelling of personality, attitudes and risky driving." Proceedings of the Institution of Civil Engineers - Transport 161, no. 1 (February 2008): 37–43. http://dx.doi.org/10.1680/tran.2008.161.1.37.

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Orlowske, Lori L., and Paul D. Luyben. "Risky Behavior: Cell Phone Use While Driving." Journal of Prevention & Intervention in the Community 37, no. 3 (June 30, 2009): 221–29. http://dx.doi.org/10.1080/10852350902976106.

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Morisset, Nolwenn, Florence Terrade, and Alain Somat. "Perceived Self-Efficacy and Risky Driving Behaviors." Swiss Journal of Psychology 69, no. 4 (January 2010): 233–38. http://dx.doi.org/10.1024/1421-0185/a000027.

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Streszczenie:

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 plu

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Vinceti, M., M. Bergomi, R. Vivoli, S. Rovesti, P. Bussetti, and G. Vivoli. "Personality Traits as Predictors of Risky Driving." Epidemiology 18, Suppl (September 2007): S207—S208. http://dx.doi.org/10.1097/01.ede.0000289058.58519.a1.

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Harré, Niki, Theo Brandt, and Martin Dawe. "The Development of Risky Driving in Adolescence." Journal of Safety Research 31, no. 4 (December 2000): 185–94. http://dx.doi.org/10.1016/s0022-4375(00)00035-9.

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Jonah, Brian A., Rachel Thiessen, and Elaine Au-Yeung. "Sensation seeking, risky driving and behavioral adaptation." Accident Analysis & Prevention 33, no. 5 (September 2001): 679–84. http://dx.doi.org/10.1016/s0001-4575(00)00085-3.

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Otto, Jay, Nicholas Ward, Steven Swinford, and Jeffrey Linkenbach. "Engaging worksite bystanders to reduce risky driving." Transportation Research Part F: Traffic Psychology and Behaviour 26 (September 2014): 370–78. http://dx.doi.org/10.1016/j.trf.2014.02.006.

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BATES, BETSY. "Women Closing Gap in Risky Drinking, Driving." Clinical Psychiatry News 33, no. 10 (October 2005): 50. http://dx.doi.org/10.1016/s0270-6644(05)70891-2.

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Danno, Mikio, and Akio Wakabayashi. "Neuropsychological Approach to Identifying Risky Driving Behaviors." IEEE Intelligent Systems 25, no. 5 (September 2010): 91–96. http://dx.doi.org/10.1109/mis.2010.127.

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