{"title":"浮动车数据质量对拥堵识别的影响","authors":"Wolfgang Blumthaler, Bartosz Bursa, M. Mailer","doi":"10.18757/EJTIR.2020.20.4.5304","DOIUrl":null,"url":null,"abstract":"This paper explores the usability of floating car data (FCD) of mixed quality in congestion analysis on motorways. The specific data quality aspects that we are investigating are the number and density of trajectories, the GPS interval, and the fleet representativeness. We use a dataset provided by the German Automobile Club ADAC covering the Tyrolean road network in 2016. From this dataset, trajectories along the A12 motorway were extracted for congestion analysis. These data are characterized by high GPS time interval, low number of trajectories, and are not representative for total traffic due to overrepresentation of trucks. The influence of these quality parameters on congestion identification is explored by analyzing the parameter distribution among different congestion types. In addition, we validate the results by comparing them with congestion incidents obtained from the stationary detector data (SDD) and examining the impact of quality parameters on the validation results. We find that the given data set does not allow short-term congestion patterns to be identified due to quality flaws. Especially the low number of trajectories proved problematic, whereas the influence of other parameters was less distinct. Despite these flaws, for large-scale congestion incidents, floating car data provide outcomes similar to those derived from stationary detectors.","PeriodicalId":46721,"journal":{"name":"European Journal of Transport and Infrastructure Research","volume":" ","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Influence of floating car data quality on congestion identification\",\"authors\":\"Wolfgang Blumthaler, Bartosz Bursa, M. Mailer\",\"doi\":\"10.18757/EJTIR.2020.20.4.5304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper explores the usability of floating car data (FCD) of mixed quality in congestion analysis on motorways. The specific data quality aspects that we are investigating are the number and density of trajectories, the GPS interval, and the fleet representativeness. We use a dataset provided by the German Automobile Club ADAC covering the Tyrolean road network in 2016. From this dataset, trajectories along the A12 motorway were extracted for congestion analysis. These data are characterized by high GPS time interval, low number of trajectories, and are not representative for total traffic due to overrepresentation of trucks. The influence of these quality parameters on congestion identification is explored by analyzing the parameter distribution among different congestion types. In addition, we validate the results by comparing them with congestion incidents obtained from the stationary detector data (SDD) and examining the impact of quality parameters on the validation results. We find that the given data set does not allow short-term congestion patterns to be identified due to quality flaws. Especially the low number of trajectories proved problematic, whereas the influence of other parameters was less distinct. Despite these flaws, for large-scale congestion incidents, floating car data provide outcomes similar to those derived from stationary detectors.\",\"PeriodicalId\":46721,\"journal\":{\"name\":\"European Journal of Transport and Infrastructure Research\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Transport and Infrastructure Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.18757/EJTIR.2020.20.4.5304\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Transport and Infrastructure Research","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.18757/EJTIR.2020.20.4.5304","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Influence of floating car data quality on congestion identification
This paper explores the usability of floating car data (FCD) of mixed quality in congestion analysis on motorways. The specific data quality aspects that we are investigating are the number and density of trajectories, the GPS interval, and the fleet representativeness. We use a dataset provided by the German Automobile Club ADAC covering the Tyrolean road network in 2016. From this dataset, trajectories along the A12 motorway were extracted for congestion analysis. These data are characterized by high GPS time interval, low number of trajectories, and are not representative for total traffic due to overrepresentation of trucks. The influence of these quality parameters on congestion identification is explored by analyzing the parameter distribution among different congestion types. In addition, we validate the results by comparing them with congestion incidents obtained from the stationary detector data (SDD) and examining the impact of quality parameters on the validation results. We find that the given data set does not allow short-term congestion patterns to be identified due to quality flaws. Especially the low number of trajectories proved problematic, whereas the influence of other parameters was less distinct. Despite these flaws, for large-scale congestion incidents, floating car data provide outcomes similar to those derived from stationary detectors.
期刊介绍:
The European Journal of Transport and Infrastructure Research (EJTIR) is a peer-reviewed scholarly journal, freely accessible through the internet. EJTIR aims to present the results of high-quality scientific research to a readership of academics, practitioners and policy-makers. It is our ambition to be the journal of choice in the field of transport and infrastructure both for readers and authors. To achieve this ambition, EJTIR distinguishes itself from other journals in its field, both through its scope and the way it is published.