Gotowe bibliografie tematyczne / Risky Driving

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Gotowa bibliografia na temat „Risky Driving”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 20 lutego 2023

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Artykuły w czasopismach na temat "Risky Driving"

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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Rozprawy doktorskie na temat "Risky Driving"

Harbeck, Emma. "Young novice drivers' perceived risk, risky driving engagement and hazard perception." Thesis, Griffith University, 2017. http://hdl.handle.net/10072/375754.

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Internationally, young novice drivers (aged 17-25 years) are often overrepresented in road-related crash injury and fatality statistics. Compared with older, more experienced drivers, prominent contributors to young driver crash-risk is their lower perceived risk, higher engagement in risky driving behaviours (e.g., speeding), and poorer hazard perception skills. This thesis describes seven studies conducted to address three research aims. The first aim was to model and examine three psychological theories of personality, social–cognitive, and social-learning, to propose a new conceptual frame

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Laude, Jennifer R. "COGNITIVE AND BEHAVIORAL MECHANISMS UNDERLYING ALCOHOL-INDUCED RISKY DRIVING." UKnowledge, 2016. http://uknowledge.uky.edu/psychology_etds/88.

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Alcohol intoxication represents one situation an individual might increase their amount of risk taking when driving. This dissertation is comprised of three studies that investigate the mechanisms by which alcohol increases driver risk-taking. Study 1 examined the effect of alcohol on driver risk-taking using a proxemics approach. The study also tested whether alcohol-induced increases in risky driving co-occurred with pronounced impairment in the driver’s skill. The study also examined whether the most disinhibited drivers were also the riskiest. Indeed, alcohol increased driver risk-taking a

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Aavik, Julie Jensen. "Drunk - Driving, Relapse Pattern and Risky Driving Behavior Among Participants in a DWI Prevention Programme." Thesis, Norges teknisk-naturvitenskapelige universitet, Fakultet for samfunnsvitenskap og teknologiledelse, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11705.

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The overall aim of the study was to examine relapse among participants in the DWI Prevention Programme and those who get prison sentence after driving when influenced by alcohol and to examine the participants’ attitudes towards drunk – driving, risk behavior and traffic safety. A direct evaluation of the sentence and penal accomplishment is also examined. The sample of the survey study (see article 1) was 44 from the DWI – sample and 44 from the prison – sample that completed a questionnaire answering about their attitudes towards drunk – driving, risk behavior and traffic safety. The results

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Dula, Chris S. "Validity and Reliability Assessment of a Dangerous Driving Self-Report Measure." Diss., Virginia Tech, 2003. http://hdl.handle.net/10919/26606.

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The Dula Dangerous Driving Index (DDDI) was created to measure drivers' self-reported propensity to drive dangerously (Dula & Ballard, in press). In the early stages of development, the DDDI and each of its subscales (Dangerous Driving Total, Aggressive Driving, Negative Emotional Driving, and Risky Driving) were found to have strong internal reliability (alphas from .83 to .92), and there was evidence of construct validity. In Study One, the alpha coefficient of .91 for the DDDI Total scale indicated excellent internal reliability for the measure and good internal reliability was demonstrate

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Fernandes, Ralston Psychology Faculty of Science UNSW. "A systematic investigation of relevant predictors, moderations and mediations for intention to speed, drink-drive, drive while fatigued, and not wear a seat belt, amongst young NSW drivers." Publisher:University of New South Wales. Psychology, 2007. http://handle.unsw.edu.au/1959.4/42933.

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Road trauma is recognized as a major public health problem worldwide (particularly for younger drivers), and risky driving has been identified as an important contributor to road crashes. It is often assumed that similar factors influence all risky driving behaviours, although direct and systematic examination of the differences between risky driving behaviours in terms of precipitating factors is lacking. The present thesis sought to undertake a systematic investigation of relevant factors in the prediction of four key risky driving behaviours (speeding, drink-driving, driving while fatigued,

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Ribak, Judith H. "Characteristics of Older and Oldest Adult Drivers: Understanding Risky Driving." University of Cincinnati / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1211932852.

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Ford, Emily E., Kathryn L. Duvall, David L. Wood, and Kiana R. Johnson. "Taking the Risk: Insufficient Communication Concerning Risky Driving Behaviors Among Young Drivers in Central Appalachia." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/asrf/2018/schedule/91.

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Introduction: This study moves to examine the prevalence of risky driving behaviors and deficiency of communication pertinent to topics related to safe driving among adolescents in central Appalachia. Even though plenty of research displays the consequences associated with driving, drivers continue to take part in risky behaviors such as texting while driving, riding in a vehicle without wearing a seatbelt, and riding in a vehicle with someone who has been drinking. Methods: Participants of the study included three high schools in Southwest Virginia consisting of 385 11th and 12th grade studen

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Herrero-Fernández, David, Sara Fonseca-Baeza, and Sara Pla-Sancho. "Factorial structure of Driving Log in a Spanish sample." Pontificia Universidad Católica del Perú, 2014. http://repositorio.pucp.edu.pe/index/handle/123456789/101153.

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The present study aimed the adaptation of the Driving Log, a questionnaire that assesses aggressive and risky driving behaviors in a day by day basis, with 395 Spanish participants. Confirmatory factor analysis showed that the questionnaire fitted properly in two correlated factors, labeled as Risky Driving and Aggressive Driving. Subsequent analyses showed that the number of drives is significantly associated to Risky Driving, while the number of occasions in which anger is experimented correlated with Risky Driving as well as Aggressive Driving. Other findings suggest that men behave in a mo

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Missikpode, Celestin. "Modeling the dynamics of teen risky driving for evaluating prevention strategies." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6216.

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Despite the tremendous efforts made in recent years towards improving overall health status of adolescents, road traffic crashes remain a global problem worldwide among teen drivers. It is well established that the first few months of independent driving are the most dangerous. Indeed, crash risk among adolescent drivers is particularly high during the early months of independent driving, after which it starts to rapidly decrease over a period of over a period of years. Hypotheses for this decline have focused on Some researchers have hypothesized accumulation of driving experience, maturation

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Scott-Parker, Bridie Jean. "A comprehensive investigation of the risky driving behaviour of young novice drivers." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/59638/1/Bridie_Scott-Parker_Thesis.pdf.

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Young novice drivers - that is, drivers aged 16-25 years who are relatively inexperienced in driving on the road and have a novice (Learner, Provisional) driver's licence - have been overrepresented in car crash, injury and fatality statistics around the world for decades. There are numerous persistent characteristics evident in young novice driver crashes, fatalities and offences, including variables relating to the young driver themselves, broader social influences which include their passengers, the car they drive, and when and how they drive, and their risky driving behaviour in particular

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Książki na temat "Risky Driving"

Bauer, Thomas, Jürgen Großmann, Fredrik Seehusen, Ketil Stølen, and Marc-Florian Wendland, eds. Risk Assessment and Risk-Driven Testing. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14114-5.

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Seehusen, Fredrik, Michael Felderer, Jürgen Großmann, and Marc-Florian Wendland, eds. Risk Assessment and Risk-Driven Testing. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26416-5.

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Marowitz, Leonard A. The relationship between drug arrests and driving risk. [Sacramento]: California Dept. of Motor Vehicles, [Research and Development Section, 1994.

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Lund, Mass Soldal, Bjørnar Solhaug, and Ketil Stølen. Model-Driven Risk Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-12323-8.

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The psychology of driving. Mahwah, NJ: Lawrence Erlbaum Associates, 2006.

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Großmann, Jürgen, Michael Felderer, and Fredrik Seehusen, eds. Risk Assessment and Risk-Driven Quality Assurance. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57858-3.

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Hennessy, David F. Clearing a road to driving fitness by better assessing driving wellness: Development of California's propective three-tier driving-centered assessment system : summary report. [Sacramento, CA]: California Dept. of Motor Vehicles, Research and Development Section, 2005.

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Rothe, John Peter. The trucker's world: Risk, safety, and mobility. New Brunswick, U.S.A: Transaction Publishers, 1991.

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Roine, Matti. Accident risks of car drivers in wintertime traffic. Espoo [Finland]: Technical Research Centre of Finland, 1999.

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Części książek na temat "Risky Driving"

McKnight, A. James. "Risky Driving by Youth." In Automobile Insurance: Road Safety, New Drivers, Risks, Insurance Fraud and Regulation, 243–51. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4058-8_17.

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Jessor, Richard, Mark S. Turbin, and Frances M. Costa. "Developmental Change in Risky Driving." In Advancing Responsible Adolescent Development, 423–46. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51349-2_21.

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Wang, Junxiu. "Research on Risky Driving Behavior." In Research Series on the Chinese Dream and China’s Development Path, 211–32. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2270-9_10.

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Zuckerman, Marvin. "Sensation Seeking and Risky Driving, Sports, and Vocations." In Sensation seeking and risky behavior., 73–106. Washington: American Psychological Association, 2007. http://dx.doi.org/10.1037/11555-003.

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Pei, Yulong, Weiwei Qi, and Chuanyun Fu. "Characteristics of Risky Merging Driving Behavior on Urban Expressway." In Advances in Computer Science, Environment, Ecoinformatics, and Education, 284–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23324-1_46.

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Parameswaran, Swathy, Aswin Ramesh, and Venkatesh Balasubramanian. "Mediating Role of Driving Stress in the Relation Between Reaction Time and Risky Driving." In Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021), 784–91. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74608-7_96.

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Cruz, Luis C., Adrián Macías, Manuel Domitsu, Luis A. Castro, and Luis-Felipe Rodríguez. "Risky Driving Detection through Urban Mobility Traces: A Preliminary Approach." In Ubiquitous Computing and Ambient Intelligence. Context-Awareness and Context-Driven Interaction, 382–85. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03176-7_51.

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Jessor, Richard, John E. Donovan, and Frances Costa. "Adolescent and Young Adult Risky Driving: The Role of Problem Drinking." In Advancing Responsible Adolescent Development, 413–22. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51349-2_20.

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Pei, Yulong, Weiwei Qi, Xupeng Zhang, and Mo Song. "Comprehensive Analysis of Risky Driving Behaviors Based on Fuzzy Evaluation Model." In Advances in Intelligent and Soft Computing, 507–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29390-0_81.

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Park, Se Jin, Murali Subramaniyam, Seoung Eun Kim, Seunghee Hong, Joo Hyeong Lee, and Chan Min Jo. "Older Driver’s Physiological Response Under Risky Driving Conditions—Overtaking, Unprotected Left Turn." In Advances in Intelligent Systems and Computing, 107–14. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41627-4_11.

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Streszczenia konferencji na temat "Risky Driving"

Pradhan, Anuj, Alexander Pollatsek, and Donald L. Fisher. "Comparison of Trained and Untrained Novice Drivers’ Gaze Behavior in Risky and Non-Risky Scenarios." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2007. http://dx.doi.org/10.17077/drivingassessment.1257.

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Simmons-Morton, Bruce G., Kaigang Li, Ashley Brooks-Russell, Johnathon Ehsani, Anuj Pradhan, Marie Claude Ouimet, and Sheila Klauer. "Validity of the C-RDS Self-Reported Risky Driving Measure." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2013. http://dx.doi.org/10.17077/drivingassessment.1462.

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Senserrick, Teresa M., Timothy Brown, Dawn Marshall, D. Alex Quistberg, Ben Dow, and Flaura K. Winston. "Risky Driving by Recently Licensed Teens: Self-Reports and Simulated Performance." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2007. http://dx.doi.org/10.17077/drivingassessment.1289.

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Sümer, Nebi. "Cognitive and Psychomotor Correlates of Hazard Perception Ability and Risky Driving." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2011. http://dx.doi.org/10.17077/drivingassessment.1399.

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Hsu, Chih-Chung, Wen-Hai Tseng, and Hao-Ting Yang. "Learning to Predict Risky Driving Behaviors for Autonomous Driving." In 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan). IEEE, 2020. http://dx.doi.org/10.1109/icce-taiwan49838.2020.9258163.

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Jongen, Ellen, Kris Brijs, Marcell Komlos, Tom Brijs, and Geert Wets. "Inhibitory Control and Reward Predict Risky Driving in Young Novice Drivers: A Simulator Study." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2011. http://dx.doi.org/10.17077/drivingassessment.1444.

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Sun, Zhengwei, Xin Pei, Pengju Wang, Haowei Liu, Dajun Wang, and Zuo Zhang. "Longitudinal Risky Driving Behavior Recognition Based on Naturalistic Driving Study." In 17th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2018. http://dx.doi.org/10.1061/9780784480915.487.

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Langevin, Sabine, Aurèlie Dommes, Viola Cavallo, Jennifer Oxley, and Fabrice Vienne. "Cognitive, Perceptual and Motor Decline as Predictors of Risky Street-Crossing Decisions in Older Pedestrians." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2011. http://dx.doi.org/10.17077/drivingassessment.1426.

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Jongen, Ellen M. M., Kris Brijs, Tom Brijs, and Geert Wets. "Inhibitory Control and Peer Passengers Predict Risky Driving in Young Novice Drivers - A Simulator Study." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2013. http://dx.doi.org/10.17077/drivingassessment.1483.

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Danno, Mikio, and Akio Wakabayashi. "Neuropsychological approach to identifying risky driving behaviors." In 2010 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2010. http://dx.doi.org/10.1109/ivs.2010.5548141.

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Raporty organizacyjne na temat "Risky Driving"

Huh, Jason, and Julian Reif. Teenage Driving, Mortality, and Risky Behaviors. Cambridge, MA: National Bureau of Economic Research, October 2020. http://dx.doi.org/10.3386/w27933.

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Xing, Xiaoyuan. Reproduction of 'Teenage Driving, Mortality, and Risky Behaviors'. Social Science Reproduction Platform, March 2022. http://dx.doi.org/10.48152/ssrp-rbfz-ey24.

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Chen, Meixuan. Reproduction of 'Teenage Driving, Mortality, and Risky Behaviors'. Social Science Reproduction Platform, March 2022. http://dx.doi.org/10.48152/ssrp-0vkv-7636.

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Wang, Shenlong, and David Forsyth. Safely Test Autonomous Vehicles with Augmented Reality. Illinois Center for Transportation, August 2022. http://dx.doi.org/10.36501/0197-9191/22-015.

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This work exploits augmented reality to safely train and validate autonomous vehicles’ performance in the real world under safety-critical scenarios. Toward this goal, we first develop algorithms that create virtual traffic participants with risky behaviors and seamlessly insert the virtual events into real images perceived from the physical world. The resulting composed images are photorealistic and physically grounded. The manipulated images are fed into the autonomous vehicle during testing, allowing the self-driving vehicle to react to such virtual events within either a photorealistic sim

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Cavallo, Eduardo A., and Eduardo Fernández-Arias. The Risk of External Financial Crisis. Inter-American Development Bank, December 2022. http://dx.doi.org/10.18235/0004579.

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This paper explores the empirical determinants of external crises on a world panel dataset of 62 countries over the fifty-year period 1970-2019 and estimates their risk trade-offs with the aim of informing macrofinancial prudential policies. The determinants include countries external balance sheets, macroeconomic imbalances, and structural and global factors. It finds that information on the composition of gross positions in countries external financial portfolios is required to gauge the risk of external crisis: debt liabilities are the riskiest component, FDI liabilities are half as risky,

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Wheatley, Paul. A risk driven approach to Bitstream Preservation. DPC, December 2022. http://dx.doi.org/10.7207/twgn22-02.

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Beiker, Sven. Unsettled Issues in Remote Operation for On-road Driving Automation. SAE International, December 2021. http://dx.doi.org/10.4271/epr2021028.

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On-road vehicles equipped with driving automation features—where a human might not be needed for operation on-board—are entering the mainstream public space. However, questions like “How safe is safe enough?” and “What to do if the system fails?” persist. This is where remote operation comes in, which is an additional layer to the automated driving system where a human remotely assists the so-called “driverless” vehicle in certain situations. Such remote-operation solutions introduce additional challenges and potential risks as the entire vehicle-network-human now needs to work together safely

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McBeth, Michael S. Risk Driven Outcome-Based Command and Control (C2) Assessment. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada458928.

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Everest, Grace, Louise Marshall, Caroline Fraser, and Adam Briggs. Addressing the leading risk factors for ill health. The Health Foundation, February 2022. http://dx.doi.org/10.37829/hf-2022-p10.

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Smoking, poor diet, physical inactivity and harmful alcohol use are leading risk factors driving the UK’s high burden of preventable ill health and premature mortality. All are socioeconomically patterned and contribute significantly to widening health inequalities. This Health Foundation report summarises recent trends for each of these risk factors and looks at national-level policies for England, introduced or proposed by the UK government between 2016 and 2021. The report reviews the government’s approach and finds a heavy reliance on policies aimed at changing individual behaviour and an

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Kennedy, Alan, Jonathon Brame, Taylor Rycroft, Matthew Wood, Valerie Zemba, Charles Weiss, Matthew Hull, Cary Hill, Charles Geraci, and Igor Linkov. A definition and categorization system for advanced materials : the foundation for risk-informed environmental health and safety testing. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41803.

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Novel materials with unique or enhanced properties relative to conventional materials are being developed at an increasing rate. These materials are often referred to as advanced materials (AdMs) and they enable technological innovations that can benefit society. Despite their benefits, however, the unique characteristics of many AdMs, including many nanomaterials, are poorly understood and may pose environmental safety and occupational health (ESOH) risks that are not readily determined by traditional risk assessment methods. To assess these risks while keeping up with the pace of development

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