{"title":"了解主干道上超速模式分布的GeoVisual分析:评估弱势道路使用者的交通安全","authors":"I. Kveladze, N. Agerholm","doi":"10.1080/17489725.2020.1823497","DOIUrl":null,"url":null,"abstract":"ABSTRACT Arterial roads have operational significance and play a substantial role in the mobility of modern society. They make up the majority of road network in urban and rural areas and allow high-speed movement despite traffic-controlling elements. In densely populated areas where the presence of Vulnerable Road Users (VRUs) is high, high-speed movement is problematic, and speed calming measures are needed to improve traffic safety, since many VRUs do crossroads, regardless of the road network regulations. These aspects have been researched in the traffic domain in a small scale, and not much has been investigated from a visualisation perspective. To provide comprehensive insights on the movement characteristics of arterial roads, we propose a GeoVisual Analytics (GVA) approach. GVA techniques are suitable solutions to display and extract knowledge from large amounts of Floating Car Data (FCD) collected through on-board devices of vehicles. By cross-sector collaboration between cartographic and traffic experts, five arterial road segments in Aalborg City were selected to answer where and when in particular VRUs do cross streets by ignoring traffic rules. Based on clusters of large unexplainable deviations from driving speed in FCD, the results uncovered meaningful patterns from complex traffic movements. They also allowed for the provision of some recommendations that are critical for traffic safety in urban areas.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"14 1","pages":"201 - 230"},"PeriodicalIF":1.2000,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2020.1823497","citationCount":"2","resultStr":"{\"title\":\"GeoVisual analytics for understanding the distribution of speeding patterns on arterial roads: assessing the traffic safety of vulnerable road users\",\"authors\":\"I. Kveladze, N. Agerholm\",\"doi\":\"10.1080/17489725.2020.1823497\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Arterial roads have operational significance and play a substantial role in the mobility of modern society. They make up the majority of road network in urban and rural areas and allow high-speed movement despite traffic-controlling elements. In densely populated areas where the presence of Vulnerable Road Users (VRUs) is high, high-speed movement is problematic, and speed calming measures are needed to improve traffic safety, since many VRUs do crossroads, regardless of the road network regulations. These aspects have been researched in the traffic domain in a small scale, and not much has been investigated from a visualisation perspective. To provide comprehensive insights on the movement characteristics of arterial roads, we propose a GeoVisual Analytics (GVA) approach. GVA techniques are suitable solutions to display and extract knowledge from large amounts of Floating Car Data (FCD) collected through on-board devices of vehicles. By cross-sector collaboration between cartographic and traffic experts, five arterial road segments in Aalborg City were selected to answer where and when in particular VRUs do cross streets by ignoring traffic rules. Based on clusters of large unexplainable deviations from driving speed in FCD, the results uncovered meaningful patterns from complex traffic movements. They also allowed for the provision of some recommendations that are critical for traffic safety in urban areas.\",\"PeriodicalId\":44932,\"journal\":{\"name\":\"Journal of Location Based Services\",\"volume\":\"14 1\",\"pages\":\"201 - 230\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2020-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/17489725.2020.1823497\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Location Based Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/17489725.2020.1823497\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Location Based Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17489725.2020.1823497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
GeoVisual analytics for understanding the distribution of speeding patterns on arterial roads: assessing the traffic safety of vulnerable road users
ABSTRACT Arterial roads have operational significance and play a substantial role in the mobility of modern society. They make up the majority of road network in urban and rural areas and allow high-speed movement despite traffic-controlling elements. In densely populated areas where the presence of Vulnerable Road Users (VRUs) is high, high-speed movement is problematic, and speed calming measures are needed to improve traffic safety, since many VRUs do crossroads, regardless of the road network regulations. These aspects have been researched in the traffic domain in a small scale, and not much has been investigated from a visualisation perspective. To provide comprehensive insights on the movement characteristics of arterial roads, we propose a GeoVisual Analytics (GVA) approach. GVA techniques are suitable solutions to display and extract knowledge from large amounts of Floating Car Data (FCD) collected through on-board devices of vehicles. By cross-sector collaboration between cartographic and traffic experts, five arterial road segments in Aalborg City were selected to answer where and when in particular VRUs do cross streets by ignoring traffic rules. Based on clusters of large unexplainable deviations from driving speed in FCD, the results uncovered meaningful patterns from complex traffic movements. They also allowed for the provision of some recommendations that are critical for traffic safety in urban areas.
期刊介绍:
The aim of this interdisciplinary and international journal is to provide a forum for the exchange of original ideas, techniques, designs and experiences in the rapidly growing field of location based services on networked mobile devices. It is intended to interest those who design, implement and deliver location based services in a wide range of contexts. Published research will span the field from location based computing and next-generation interfaces through telecom location architectures to business models and the social implications of this technology. The diversity of content echoes the extended nature of the chain of players required to make location based services a reality.