N. Naharudin, M. Ahamad, Ahmad Farhan Mohd Sadullah
{"title":"Pedestrian-attractiveness score for the first/last mile transit route using spatial data collected with a mobile positioning application","authors":"N. Naharudin, M. Ahamad, Ahmad Farhan Mohd Sadullah","doi":"10.1109/EURONAV.2017.7954195","DOIUrl":null,"url":null,"abstract":"Transit services or public transportation is expected to be able to not only provide a good mobility and accessibility to people in a city, but it should allow a pleasant journey to them to attract people to ride it. It can be influenced by the presence of built environments such as the pedestrian facilities and furniture along the walking route. Therefore, many studies have attempted to measure the attractiveness of the first/last mile (FLM) transit journey, however, there seem to be limitations in those studies. First, there is a lack of pedestrian data available. This could affect the precision of measuring the pedestrian attractiveness. Second, there is a lack of studies implementing such data to analyze the pedestrian-attractiveness itself. This paper proposes a framework combining spatial data collection for pedestrian data with spatial analysis to measure the pedestrian-attractiveness of the FLM transit journey. It will utilize the mobile positioning procedure to collect the data as it is the most efficient method to collect thousands of pedestrian data on the ground in a short amount of time. It uses a mobile mapping application available on the market to collect data in the field. The collected spatial data will then be used as attributes in the spatial analysis of the pedestrian routes of the FLM transit journey. The outcome of the framework will be a score indicating the pedestrian-attractiveness of the FLM transit journey. The results show that the pedestrian-attractiveness score can be influenced by the number of built environments present along the walking route and public preferences of these. A station with a higher number of built environments will score more than the other. Similarly, a station with a more preferred parameters will also score higher.","PeriodicalId":145124,"journal":{"name":"2017 European Navigation Conference (ENC)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 European Navigation Conference (ENC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURONAV.2017.7954195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Transit services or public transportation is expected to be able to not only provide a good mobility and accessibility to people in a city, but it should allow a pleasant journey to them to attract people to ride it. It can be influenced by the presence of built environments such as the pedestrian facilities and furniture along the walking route. Therefore, many studies have attempted to measure the attractiveness of the first/last mile (FLM) transit journey, however, there seem to be limitations in those studies. First, there is a lack of pedestrian data available. This could affect the precision of measuring the pedestrian attractiveness. Second, there is a lack of studies implementing such data to analyze the pedestrian-attractiveness itself. This paper proposes a framework combining spatial data collection for pedestrian data with spatial analysis to measure the pedestrian-attractiveness of the FLM transit journey. It will utilize the mobile positioning procedure to collect the data as it is the most efficient method to collect thousands of pedestrian data on the ground in a short amount of time. It uses a mobile mapping application available on the market to collect data in the field. The collected spatial data will then be used as attributes in the spatial analysis of the pedestrian routes of the FLM transit journey. The outcome of the framework will be a score indicating the pedestrian-attractiveness of the FLM transit journey. The results show that the pedestrian-attractiveness score can be influenced by the number of built environments present along the walking route and public preferences of these. A station with a higher number of built environments will score more than the other. Similarly, a station with a more preferred parameters will also score higher.