In line with European developments, a Dutch second phase coaching program, referred to as the DX- （Driver Xperience） program, was developed for young novice drivers to counteract their high accident risk. More speci...In line with European developments, a Dutch second phase coaching program, referred to as the DX- （Driver Xperience） program, was developed for young novice drivers to counteract their high accident risk. More specifically, the aim of the DX-program was to enable young drivers to make responsible decisions and develop positive attitudes regarding four levels of the driving task： combining life style and driving, planning and navigation, participating in different traffic situations and handling the vehicle. In this paper, the design principles of the program are described. The empirical study focused on the entry characteristics of the participating young drivers （n = 3,117） as compared to a reference group of young drivers （n = 345）. Results show that the DX-program attracted young drivers that, in some respects, showed a more risky profile than average young drivers in terms of speed violations, anger and the number of fines. In addition, four groups of participants with sharply differing driving styles could be distinguished. Implications for educational design and follow-up research are discussed within the theoretical framework of self-regulated learning.展开更多
Motor vehicle crashes are the leading cause of the death of teenagers in the United States.Young drivers have shown a higher propensity to get involved in crashes due to using a cellphone while driving,breaking the sp...Motor vehicle crashes are the leading cause of the death of teenagers in the United States.Young drivers have shown a higher propensity to get involved in crashes due to using a cellphone while driving,breaking the speed limit,and reckless driving.This study analyzed motor vehicle crashes involving young drivers using New Jersey crash data.Specifically,four years of crash data(2016-2019)were gathered and analyzed.Different machine learning(ML)methods,such as Random Forest,Light GBM,Catboost,and XGBoost,were used to predict the injury severity.The performance of the models was evaluated using accuracy,precision,and recall scores.In addition,interpretable ML techniques like sensitivity analysis and Shapley values were conducted to assess the most influential factors’impacts on young driver-related crashes.The results revealed that XGBoost performed better than Random Forest,CatBoost,and LightGBM models in crash severity prediction.Results from the sensitivity analysis showed that multi-vehicle crashes,angular crashes,crashes at intersections,and dark-not-lit conditions had increased crash severity.A partial dependence plot of SHAP values revealed that speeding in clear weather had a higher likelihood of injury crashes,and multi-vehicle crashes at the intersection had more injury crashes.We expect that the results obtained from this study will help policymakers and practitioners take appropriate countermeasures to improve the safety of young drivers in New Jersey.展开更多
In Australia,and around the world,there is a continuous debate about the ways of delivering a message,instruction,or feedback effectively to improve students’learning and performance.Contemporary cognitive skills tra...In Australia,and around the world,there is a continuous debate about the ways of delivering a message,instruction,or feedback effectively to improve students’learning and performance.Contemporary cognitive skills training approaches have emerged as a result of further development of effective cognitive skills training in different contexts,such as education,aviation,and driving.One of the effective cognitive-based training is feedback.Feedback is an important component in learning,including the development of safe driving for novice drivers.Research shows that feedback can reduce the number of speeding occurrences,and the likelihood of speeding-related incidents and accidents,but it is not clear how to provide effective feedback to young learners.This paper reviews the literature and examines various aspects of feedback as a training intervention for young drivers and provides recommendation for effective use for young learners.The results explored the characteristics of feedback including multiple dimensions:content,source,medium of delivery,timing and frequency.Importantly,its effectiveness in improving an individual performance depends on effective utilization of these characteristics.The results showed that the most effective type of feedback(considering all feedback characteristics)in improving young novice drivers’performance in terms of speed compliance is feedback about performance,financial and safety implications(content),provided verbally and graphically(medium in which provided),by an instructor(researcher;source),immediately after the drive(time),once or twice(frequency).These results have important implications for the development of new training approaches to improving young drivers’speed management behaviour.展开更多
文摘In line with European developments, a Dutch second phase coaching program, referred to as the DX- （Driver Xperience） program, was developed for young novice drivers to counteract their high accident risk. More specifically, the aim of the DX-program was to enable young drivers to make responsible decisions and develop positive attitudes regarding four levels of the driving task： combining life style and driving, planning and navigation, participating in different traffic situations and handling the vehicle. In this paper, the design principles of the program are described. The empirical study focused on the entry characteristics of the participating young drivers （n = 3,117） as compared to a reference group of young drivers （n = 345）. Results show that the DX-program attracted young drivers that, in some respects, showed a more risky profile than average young drivers in terms of speed violations, anger and the number of fines. In addition, four groups of participants with sharply differing driving styles could be distinguished. Implications for educational design and follow-up research are discussed within the theoretical framework of self-regulated learning.
文摘Motor vehicle crashes are the leading cause of the death of teenagers in the United States.Young drivers have shown a higher propensity to get involved in crashes due to using a cellphone while driving,breaking the speed limit,and reckless driving.This study analyzed motor vehicle crashes involving young drivers using New Jersey crash data.Specifically,four years of crash data(2016-2019)were gathered and analyzed.Different machine learning(ML)methods,such as Random Forest,Light GBM,Catboost,and XGBoost,were used to predict the injury severity.The performance of the models was evaluated using accuracy,precision,and recall scores.In addition,interpretable ML techniques like sensitivity analysis and Shapley values were conducted to assess the most influential factors’impacts on young driver-related crashes.The results revealed that XGBoost performed better than Random Forest,CatBoost,and LightGBM models in crash severity prediction.Results from the sensitivity analysis showed that multi-vehicle crashes,angular crashes,crashes at intersections,and dark-not-lit conditions had increased crash severity.A partial dependence plot of SHAP values revealed that speeding in clear weather had a higher likelihood of injury crashes,and multi-vehicle crashes at the intersection had more injury crashes.We expect that the results obtained from this study will help policymakers and practitioners take appropriate countermeasures to improve the safety of young drivers in New Jersey.
文摘In Australia,and around the world,there is a continuous debate about the ways of delivering a message,instruction,or feedback effectively to improve students’learning and performance.Contemporary cognitive skills training approaches have emerged as a result of further development of effective cognitive skills training in different contexts,such as education,aviation,and driving.One of the effective cognitive-based training is feedback.Feedback is an important component in learning,including the development of safe driving for novice drivers.Research shows that feedback can reduce the number of speeding occurrences,and the likelihood of speeding-related incidents and accidents,but it is not clear how to provide effective feedback to young learners.This paper reviews the literature and examines various aspects of feedback as a training intervention for young drivers and provides recommendation for effective use for young learners.The results explored the characteristics of feedback including multiple dimensions:content,source,medium of delivery,timing and frequency.Importantly,its effectiveness in improving an individual performance depends on effective utilization of these characteristics.The results showed that the most effective type of feedback(considering all feedback characteristics)in improving young novice drivers’performance in terms of speed compliance is feedback about performance,financial and safety implications(content),provided verbally and graphically(medium in which provided),by an instructor(researcher;source),immediately after the drive(time),once or twice(frequency).These results have important implications for the development of new training approaches to improving young drivers’speed management behaviour.
