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Identifying spatio-temporal patterns of bus bunchi ng in urba n networks
| 题名： | Identifying spatio-temporal patterns of bus bunchi ng in urba n networks |
| 正文语种： | 英文 |
| 作者： | Christina A. Iliopoulou;Christina P. Milioti;Eleni I. Vlahogianni;Konstantinos L. Kepaptsoglou |
| 作者单位： | National Technical University of Athens |
| 关键词： | Bus bunching; k-means++; service reliability; spatiotemporal clustering |
| 摘要： | The objective of this paper is to identify hot spots of bus bunching events at the network level, both in time and space, using Automatic Vehicle Location (AVL) data from the Athens (Greece) Public Transportation System. A two-step spatio-temporal clustering analysis is employed for identifying localized hot spots in space and time and for refining detected hot spots, based on the n ature of bus bunchi ng eve nts. First, the Spatio-Temporal Density Based Seanning Algorithm with Noise (ST-DBSCAN) is applied to distinguish bunching patterns at the network level and subsequently a k+H-means algorithm is employed to distinguish different types of bunching clusters. Results offer insights on specific time periods and route segme nts, where bus bunchi ng events are more likely to occur and, also, on how bus bunching clusters change over time. Further, headway deviation analysis reveals the differ-en ces in the characteristics of the various bunching event types per line, showing that routes running on shared corridors experienee more issues while underlying causes may vary per line. Collectively, results can help guide practice toward more flexible solutions and control strategies. In deed, depe nding on the type of spatio-temporal patter ns detected, appropriate improvements in service planning and real-time control strategies may be iden-tified in order to mitigate their negative effects and improve quality of service. In light of emerging electric public trans port systems, the proposed framework can be also used to determine preventive strategies and improve reliability in affected stops prior to the deploy-ment of charging infrastructure. |
| 出版日期： | 2020 |
| 出版年： | 2020 |
| 期刊名称： | Journal of Intelligent Transportation Systems Technology Planning and Operations |
| 卷： | Vol24 |
| 期： | No01-06 |
| 页码： | 365-382 |
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