<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Measurement of Inter- and Intra-city Connectivity Using Vehicle Probe Data</style></title><secondary-title><style face="normal" font="default" size="100%">Measuring Connectivity Within and Among Cities in ASEAN</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Connectivity</style></keyword><keyword><style  face="normal" font="default" size="100%">Probe data</style></keyword><keyword><style  face="normal" font="default" size="100%">Urban</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.ide.go.jp/English/Publish/Download/Brc/26.html</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">26</style></number><publisher><style face="normal" font="default" size="100%">JETRO Bangkok/IDE-JETRO</style></publisher><pub-location><style face="normal" font="default" size="100%">Bangkok</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This chapter analyzes intra- and  inter-city connectivity using the vehicle probe  data  for  selected  48-hour  slots  in  March  and  September  in  2017  and  2018.  I demonstrate the potential analyses by aggregating the probe data of commercial vehicles with  overlay  to  geographical  extents  of  the  majo r  cit ies  ident ified  by  night-time  light  satellite image data.The cit ies  could  be classified  into  more  vehicles  in  the  daytime  or  night time, which were likely associated with drivers’ preference on traffic conditions by the time. Some cities indicated notable changes of driving speeds by the time, possibly owing to traffic condition with  people’s  commuting  as  well  as  transport  infrastructure,  such as highways. More than half of the vehicles were traveling only two cities within the 48-hour periods, which were possibly shuttle trips between two cities. Some cities in the large  industrial  areas  and  inland  cities  indicated  high  proportion  of  vehicles  were  travelling more than two cities, indicating contribution to connectivity among the city.</style></abstract><section><style face="normal" font="default" size="100%">2</style></section></record></records></xml>