{"title":"Analysis of Naturalistic Driving Events in Honolulu (Pre-COVID)","authors":"Luana Carneiro Pereira, P. Prevedouros","doi":"10.1061/9780784484333.013","DOIUrl":null,"url":null,"abstract":"Dashboard cameras and sensors were installed in 233 taxi vans in Honolulu, Hawaii. They produced many hours of naturalistic driving data (NDD) between fall 2019 and spring 2020 in the form of 20 s recorded events. The study achieved its objectives to (1) collect data from naturalistic driving events where driving maneuvers caused acceleration or deceleration in any direction of 0.5g or higher, (2) develop a database suitable for statistical analysis, (3) derive basic statistics for all variables, and (4) investigate correlations between variables. The database included a total of 402 harsh events, of which were 398 near-crashes and 4 were crashes. Several variables such as road, environmental, driver, and vehicle characteristics were coded for each event. The installation of an NDD system by the taxi company proved to be a successful tool for coaching drivers, and for providing statistically significant insights into traffic safety factors relating to near-miss events, such as wider expressways come with a higher risk for near rear-end events;urban roads without parking lower the risk of near rear-end events;light traffic density significantly reduces the risk of rear-end events on freeways;and, mobile phone usage has a positive and significant coefficient that increases the risk of highway rear-end events. © ASCE.","PeriodicalId":136641,"journal":{"name":"International Conference on Transportation and Development 2022","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Transportation and Development 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1061/9780784484333.013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
檀香山自然驾驶事件分析(疫情前)
在夏威夷檀香山的233辆出租车上安装了仪表盘摄像头和传感器。他们以20年代记录事件的形式,在2019年秋季至2020年春季期间生成了数小时的自然驾驶数据(NDD)。本研究达到了以下目的:(1)收集驾驶动作导致任何方向加速或减速0.5g及以上的自然驾驶事件的数据;(2)建立适合统计分析的数据库;(3)对所有变量进行基本统计;(4)研究变量之间的相关性。该数据库共包含402起恶劣事件,其中398起接近坠机,4起已经坠机。为每个事件编码了道路、环境、驾驶员和车辆特征等几个变量。出租车公司安装的NDD系统被证明是一种成功的指导司机的工具,并提供了与险些事故有关的交通安全因素的统计意义重大的见解,例如,较宽的高速公路发生近尾事故的风险较高;没有停车位的城市道路发生近尾事故的风险较低;轻交通密度显著降低高速公路发生追尾事件的风险;以及,手机使用对高速公路追尾事故风险的增加具有显著的正相关系数。©第3期。
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