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The impact of mandating a driving lesson for elderly drivers in Japan using count data models: Case study of Toyota City

机译:使用计数数据模型对日本老年司机授权驾驶课程的影响:丰田市案例研究

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摘要

As one crucial mobility problem for elderly drivers, vehicle crashes due to elderly drivers account for an increased ratio of total vehicle crashes in recent years in Japan. Mandating a driving lesson for elderly drivers was implemented and revised continuously to reduce the number of vehicle crashes. To perform a practical driving lesson for elderly drivers, it is essential to evaluate whether it can reduce vehicle crashes significantly or not. Most previous studies only investigated its effects on fatal or severe rates using rather simple methods, without consideration for the increasing number of elderly drivers and the variability of vehicle crashes in different months. To bridge these research gaps, this study examines the impact of mandating a driving lesson for elderly drivers by some advanced statistical methods based on a monthly level. Vehicle crash records from April 2005 to December 2019 collected in Toyota City, Japan are used for empirical analysis. Three types of count data models, i.e., the Poisson regression model, the Negative Binomial regression model, and the Poisson Integer Valued Autoregressive (INAR) (1) model are proposed in this study. A comparison of three proposed models was implemented to indicate the similarity and distinction of estimation results. The significant findings of this study suggest that: 1) three proposed models have the same prediction accuracy referring to indexes of Root Mean Squared Error, Mean Absolute Error, and Mean Squared Error; 2) all of them indicate that the revision of license renewal legislation for elderly drivers in March 2017 is a significant factor negatively affecting the number of vehicle crashes at a 10 % significance level; 3) all of them indicate that the number of drivers aged 65 years or older and month-variability are significant factors affecting the number of vehicle crashes at least a 10 % significance level; 4) the time-series nature of vehicle crashes due to elderly drivers was not existing indicated by the result of the Poisson INAR (1) model. Statistical methods proposed in this study can be referred by researchers and engineers to evaluate the effects of traffic safety measures in the research field of traffic and transportation engineering.
机译:作为老年司机的一个至关重要的流动性问题,由于老年人司机占日本总车辆崩溃比例增加的车辆崩溃。授权为老年司机提供驾驶课程,并不断修改,以减少车辆崩溃的数量。为了为老年司机执行实用的驾驶课程,必须评估它是否可以显着减少车辆撞击。最先前的研究仅使用相当简单的方法调查其对致命或严重利率的影响,而不考虑越来越多的老年驾驶员和不同月份车辆崩溃的可变性。为了弥合这些研究差距,本研究审查了将老年驾驶员授权为老年驾驶员的驾驶课程的影响。从2005年4月到2019年12月在丰田市收集的车辆崩溃记录用于日本,用于实证分析。本研究提出了三种类型的计数数据模型,即泊松回归模型,泊松回归模型,负二项式回归模型和泊松整数有价值的自动评论(INAR)(1)模型。实施了三种建议模型的比较,以指示估计结果的相似性和区分。本研究的重要发现表明:1)三个提出的模型具有相同的预测精度,指的是根均方误差,平均误差和均方误差的指标; 2)所有这些都表明,2017年3月的老年司机的许可续签立法是对10%重要水平的船舶数量负面影响的重要因素; 3)所有这些都表明65岁或以上的司机数量和月变异性是影响车辆数量崩溃至少10%的重要因素; 4)由于泊松INAR(1)模型的结果表示,由于老年驾驶员而言,车辆撞车的时序性质不存在。本研究中提出的统计方法可以由研究人员和工程师提及,以评估交通安全措施在交通运输工程研究领域的影响。

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