LEADER 03817oam 2200553I 450 001 9910165053703321 005 20230809222702.0 010 $a1-315-35333-4 010 $a1-315-37040-9 024 7 $a10.1201/9781315370408 035 $a(CKB)3710000001059998 035 $a(MiAaPQ)EBC4807054 035 $a(OCoLC)976394033 035 $a(EXLCZ)993710000001059998 100 $a20180420d20172016 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aPublic transport planning with smart card data /$fedited by Fumitaka Kurauchi and Jan-Dirk Schmocker 205 $aFirst edition. 210 1$aBoca Raton, FL :$cCRC Press,$d[2017]. 210 4$dİ2016 215 $a1 online resource (275 pages) $cillustrations, tables 300 $a"A Science Publishers book." 311 $a1-4987-2658-5 311 $a1-4987-2659-3 320 $aIncludes bibliographical references at the end of each chapters and index 327 $tchapter 1 Introduction -- chapter 2 Smart Card Systems and Data Features -- chapter 3 Analysis Challenges -- chapter 4 Categorization of Potential Analysis using Smart Card Data -- chapter 5 Book Overview, What is Missing and Conclusion -- chapter References -- part Part 1: Estimating Passenger Behavior -- chapter 2 Transit Origin-Destination Estimation -- chapter 3 Destination and Activity Estimation -- chapter 4 Modelling Travel Choices on Public Transport Systems with Smart Card Data -- part Part 2: Combining Smart Card Data with other Databases -- chapter 5 Combination of Smart Card Data with Person Trip Survey Data -- chapter 6 A Method for Conducting Before-After Analyses of Transit Use by Linking Smart Card Data and Survey Responses -- chapter 7 Multipurpose Smart Card Data: Case Study of Shizuoka, Japan -- chapter 8 Using Smart Card Data for Agent?Based Transport Simulation -- part Part 3: Smart Card Sata for Evaluation -- chapter 9 Smart Card Data for Wider Transport System Evaluation -- chapter 10 Evaluation of Bus Service Key Performance Indicators using Smart Card Data -- chapter 11 Ridership Evaluation and Prediction in Public Transport by Processing Smart Card Data: A Dutch Approach and Example -- chapter 12 Assessment of Traffic Bottlenecks at Bus Stops -- chapter 13 Conclusions: Opportunities Provided to Transit Organizations by Automated Data Collection Systems, Challenges and Thoughts for the Future. 330 3 $aCollecting fares through smart cards is becoming standard in most advanced public transport networks of major cities around the world. Travellers value their convenience and operators the reduced money handling fees. Electronic tickets also make it easier to integrate fare systems, to create complex time and space differentiated fare systems, and to provide incentives to specific target groups. A less-utilised benefit is the data collected through smart cards. Records, even if anonymous, provide for a much better understanding of passengers? travel behaviour as current literature shows. This information can also be used for better service planning. 606 $aAutomatic data collection systems 606 $aLocal transit$xPlanning 606 $aLocal transit$xFares$xAutomation 606 $aSmart cards 615 0$aAutomatic data collection systems. 615 0$aLocal transit$xPlanning. 615 0$aLocal transit$xFares$xAutomation. 615 0$aSmart cards. 676 $a621.0420287 702 $aKurauchi$b Fumitaka 702 $aSchmocker$b Jan-Dirk$f1976- 712 02$aCRC Press. 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910165053703321 996 $aPublic transport planning with smart card data$92800804 997 $aUNINA