To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states,a road traffic states estimation algorithm based on matching of the regional traffic at...To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states,a road traffic states estimation algorithm based on matching of the regional traffic attracters was proposed in this work.First of all,the road traffic running states were divided into several different modes.The concept of the regional traffic attracters of the target link was put forward for effective matching.Then,the reference sequences of characteristics of traffic running states with the contents of the target link's traffic running states and regional traffic attracters under different modes were established.In addition,the current and historical regional traffic attracters of the target link were matched through certain matching rules,and the historical traffic running states of the target link corresponding to the optimal matching were selected as the initial recovery data,which were processed with Kalman filter to obtain the final recovery data.Finally,some typical expressways in Beijing were adopted for the verification of this road traffic states estimation algorithm.The results prove that this traffic states estimation approach based on matching of the regional traffic attracters is feasible and can achieve a high accuracy.展开更多
The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial charact...The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.展开更多
Road traffic injury is the fifth leading cause of death and disability in Thailand,with an estimated one million people seriously injured and 14000 deaths each year.Given the magnitude of the problem,it is important t...Road traffic injury is the fifth leading cause of death and disability in Thailand,with an estimated one million people seriously injured and 14000 deaths each year.Given the magnitude of the problem,it is important to validate road traffic injury statistics,in order to determine trends and the effect of prevention efforts.The Ministry of Public Health established an injury surveillance system in 1995 to collect injury data from 4 provincial hospitals and one hospital in Bangkok.This system was designed to evaluate the quality of acute trauma care and referral services,and to improve injury prevention and control at local and national level.However,many injuries are not treated at health facilities where these data are collected.This is the first study to measure the reporting gap for injury statistics on a national level.We compared data from the Thai National Injury Survey to that gathered by the injury surveillance system and find that the former records a rate 3 times higher than the hospital-based injury surveillance system in all five regions(mean injury incidence:596/100000 vs 129/100000).Most injuries that need medical care are not treated in hospital,and do not count in the national statistics in Thailand.展开更多
目的:伤害是儿童和青少年死亡的首位原因。尽管国内外学者已发表数十个儿童非故意伤害风险评估工具,但目前全球并未就已有工具的规范使用形成共识。本研究旨在系统阐明当前国内外涉及0~6岁儿童非故意伤害风险评估工具的特点,以期为工具...目的:伤害是儿童和青少年死亡的首位原因。尽管国内外学者已发表数十个儿童非故意伤害风险评估工具,但目前全球并未就已有工具的规范使用形成共识。本研究旨在系统阐明当前国内外涉及0~6岁儿童非故意伤害风险评估工具的特点,以期为工具的科学选择和优化提供参考。方法:在中国知网、万方、PubMed、Web of Science中检索并筛选从建库至2025年1月收录的与儿童非故意伤害风险评估相关的文献。建立资料信息提取表,从文献中提取儿童非故意伤害评估工具的基本特征、评估形式、定量计分方法和评判标准、评估维度、信度和效度,以及涉及的非故意伤害类型等。结果:共纳入50个涉及0~6岁儿童非故意伤害风险的评估工具,其中35个评估工具评估2种及以上的非故意伤害类型。分别有38、2、3及7个评估工具采取儿童照护人自我报告、调查员询问、调查员现场观察及结合多种方式实施风险评估。评估工具涉及的4个维度为知识、态度、行为、环境,11个工具涵盖3个维度,仅1个工具全面涵盖4个维度。19个评估工具有明确的计分方法,14个评估工具有风险判定标准,11个评估工具同时有计分方法及风险判定标准,28个评估工具既无计分方法又无风险判定标准。22个评估工具已有信度和/或效度方面的评价。25个英文评估工具中,仅有3个有汉化版本。结论:目前暂无工具能同时满足6岁以下儿童所有常见非故意伤害类型风险评估的需要,建议在实践中结合具体用途选择恰当的工具。此外,针对现有工具的不足,建议开展优化工作,如翻译英文工具并评估其信效度、对缺乏评分方法和判断标准的工具制订相应的量化评估方法和评判标准、针对现有工具涉及不足的重要非故意伤害类型(如道路交通伤害、溺水)开发适用于中国儿童的风险评价工具。展开更多
基金Projects(D07020601400707,D101106049710005)supported by the Beijing Science Foundation Plan Project,ChinaProjects(2006AA11Z231,2012AA112401)supported by the National High Technology Research and Development Program of China(863 Program)Project(61104164)supported by the National Natural Science Foundation of China
文摘To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states,a road traffic states estimation algorithm based on matching of the regional traffic attracters was proposed in this work.First of all,the road traffic running states were divided into several different modes.The concept of the regional traffic attracters of the target link was put forward for effective matching.Then,the reference sequences of characteristics of traffic running states with the contents of the target link's traffic running states and regional traffic attracters under different modes were established.In addition,the current and historical regional traffic attracters of the target link were matched through certain matching rules,and the historical traffic running states of the target link corresponding to the optimal matching were selected as the initial recovery data,which were processed with Kalman filter to obtain the final recovery data.Finally,some typical expressways in Beijing were adopted for the verification of this road traffic states estimation algorithm.The results prove that this traffic states estimation approach based on matching of the regional traffic attracters is feasible and can achieve a high accuracy.
基金Projects(LQ16E080012,LY14F030012)supported by the Zhejiang Provincial Natural Science Foundation,ChinaProject(61573317)supported by the National Natural Science Foundation of ChinaProject(2015001)supported by the Open Fund for a Key-Key Discipline of Zhejiang University of Technology,China
文摘The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.
文摘Road traffic injury is the fifth leading cause of death and disability in Thailand,with an estimated one million people seriously injured and 14000 deaths each year.Given the magnitude of the problem,it is important to validate road traffic injury statistics,in order to determine trends and the effect of prevention efforts.The Ministry of Public Health established an injury surveillance system in 1995 to collect injury data from 4 provincial hospitals and one hospital in Bangkok.This system was designed to evaluate the quality of acute trauma care and referral services,and to improve injury prevention and control at local and national level.However,many injuries are not treated at health facilities where these data are collected.This is the first study to measure the reporting gap for injury statistics on a national level.We compared data from the Thai National Injury Survey to that gathered by the injury surveillance system and find that the former records a rate 3 times higher than the hospital-based injury surveillance system in all five regions(mean injury incidence:596/100000 vs 129/100000).Most injuries that need medical care are not treated in hospital,and do not count in the national statistics in Thailand.
文摘目的:伤害是儿童和青少年死亡的首位原因。尽管国内外学者已发表数十个儿童非故意伤害风险评估工具,但目前全球并未就已有工具的规范使用形成共识。本研究旨在系统阐明当前国内外涉及0~6岁儿童非故意伤害风险评估工具的特点,以期为工具的科学选择和优化提供参考。方法:在中国知网、万方、PubMed、Web of Science中检索并筛选从建库至2025年1月收录的与儿童非故意伤害风险评估相关的文献。建立资料信息提取表,从文献中提取儿童非故意伤害评估工具的基本特征、评估形式、定量计分方法和评判标准、评估维度、信度和效度,以及涉及的非故意伤害类型等。结果:共纳入50个涉及0~6岁儿童非故意伤害风险的评估工具,其中35个评估工具评估2种及以上的非故意伤害类型。分别有38、2、3及7个评估工具采取儿童照护人自我报告、调查员询问、调查员现场观察及结合多种方式实施风险评估。评估工具涉及的4个维度为知识、态度、行为、环境,11个工具涵盖3个维度,仅1个工具全面涵盖4个维度。19个评估工具有明确的计分方法,14个评估工具有风险判定标准,11个评估工具同时有计分方法及风险判定标准,28个评估工具既无计分方法又无风险判定标准。22个评估工具已有信度和/或效度方面的评价。25个英文评估工具中,仅有3个有汉化版本。结论:目前暂无工具能同时满足6岁以下儿童所有常见非故意伤害类型风险评估的需要,建议在实践中结合具体用途选择恰当的工具。此外,针对现有工具的不足,建议开展优化工作,如翻译英文工具并评估其信效度、对缺乏评分方法和判断标准的工具制订相应的量化评估方法和评判标准、针对现有工具涉及不足的重要非故意伤害类型(如道路交通伤害、溺水)开发适用于中国儿童的风险评价工具。
