國立虎尾科技大學 |

Uncovering Urban Mobility Patterns in a Compact City Using Smartcard Data : = A Trip-Pair Clustering Based Approach.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Uncovering Urban Mobility Patterns in a Compact City Using Smartcard Data :/
其他題名:	A Trip-Pair Clustering Based Approach.
作者:	Keong, Ku Weng.
面頁冊數:	1 online resource (103 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-10, Section: A.
Contained By:	Dissertations Abstracts International85-10A.
標題:	Environmental engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9798382222851

Uncovering Urban Mobility Patterns in a Compact City Using Smartcard Data : = A Trip-Pair Clustering Based Approach.
Keong, Ku Weng.

Uncovering Urban Mobility Patterns in a Compact City Using Smartcard Data :A Trip-Pair Clustering Based Approach. - 1 online resource (103 pages)

Source: Dissertations Abstracts International, Volume: 85-10, Section: A.

Thesis (Ph.D.)--University of Macau, 2023.

Includes bibliographical references

This study aims to understand urban mobility patterns in a compact city by clustering passenger trip-pair information from smartcard data. A two-stage model is proposed to cluster passengers based on their trip-pair patterns by using the data from the bus system in Macao, where heavily relies on bus services, with over 40% of mechanized trip being facilitated by buses. For paying the fare, the tap-upon-boarding smartcard is the most used media by passengers. By clustering the passengers, it can identify different travel characteristics, including possible identities, mobility patterns, and regularity. The study also reveals the travel characteristics of Macao, such as the compactness planning and operation by round-the-clock manner.The clustering results have important implications for policy-makers and authorities. Understanding demand and activity patterns promptly can help with appropriate real-life operational strategies such as providing customized service to particular groups. Transit authorities and agencies can implement specific policies based on cluster characteristics, such as scheduling a special timetable to handle regular imbalance travel demand. Additionally, understanding the mobility pattern of each cluster can optimize bus schedules and route planning. The study concludes by highlighting the importance of identifying and formulating tailored policies in line with passenger characteristics and preventing ignorance of potential travel demand.Overall, this study demonstrates the potential of using trip-pair information from smartcard data to cluster passengers and provide valuable insights into urban mobility patterns, ultimately leading to more efficient and effective public transit systems.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382222851Subjects--Topical Terms:

557376
Environmental engineering.
Subjects--Index Terms:

Urban mobility patternsIndex Terms--Genre/Form:

554714
Electronic books.

Uncovering Urban Mobility Patterns in a Compact City Using Smartcard Data : = A Trip-Pair Clustering Based Approach.
LDR:03110ntm a22003737 4500 001 1152643
005 20241209114619.5
006 m o d
007 cr mn ---uuuuu
008 250605s2023 xx obm 000 0 eng d
020 $a 9798382222851
035 $a (MiAaPQ)AAI30994372
035 $a AAI30994372
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Keong, Ku Weng. $3 1479696
245 1 0 $a Uncovering Urban Mobility Patterns in a Compact City Using Smartcard Data : $b A Trip-Pair Clustering Based Approach.
264 0 $c 2023
300 $a 1 online resource (103 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-10, Section: A.
500 $a Advisor: Pang, Kou Kun;Hoi, Lam Soi.
502 $a Thesis (Ph.D.)--University of Macau, 2023.
504 $a Includes bibliographical references
520 $a This study aims to understand urban mobility patterns in a compact city by clustering passenger trip-pair information from smartcard data. A two-stage model is proposed to cluster passengers based on their trip-pair patterns by using the data from the bus system in Macao, where heavily relies on bus services, with over 40% of mechanized trip being facilitated by buses. For paying the fare, the tap-upon-boarding smartcard is the most used media by passengers. By clustering the passengers, it can identify different travel characteristics, including possible identities, mobility patterns, and regularity. The study also reveals the travel characteristics of Macao, such as the compactness planning and operation by round-the-clock manner.The clustering results have important implications for policy-makers and authorities. Understanding demand and activity patterns promptly can help with appropriate real-life operational strategies such as providing customized service to particular groups. Transit authorities and agencies can implement specific policies based on cluster characteristics, such as scheduling a special timetable to handle regular imbalance travel demand. Additionally, understanding the mobility pattern of each cluster can optimize bus schedules and route planning. The study concludes by highlighting the importance of identifying and formulating tailored policies in line with passenger characteristics and preventing ignorance of potential travel demand.Overall, this study demonstrates the potential of using trip-pair information from smartcard data to cluster passengers and provide valuable insights into urban mobility patterns, ultimately leading to more efficient and effective public transit systems.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Environmental engineering. $3 557376
650 4 $a Urban planning. $3 1180826
653 $a Urban mobility patterns
653 $a Public transit systems
653 $a Trip-pair information
655 7 $a Electronic books. $2 local $3 554714
690 $a 0543
690 $a 0775
690 $a 0999
710 2 $a University of Macau. $b Civil and Environmental Engineering. $3 1475749
710 2 $a ProQuest Information and Learning Co. $3 1178819
773 0 $t Dissertations Abstracts International $g 85-10A.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30994372 $z click for full text (PQDT)