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A platform for research: civil engineering, architecture and urbanism
Transit Voronoi diagrams in multi-mode public transport networks
Abstract Network Voronoi diagrams (N-VDs) are effective geometric constructions for partitioning geographical space constrained by road networks. However, they are not applicable for urban areas with well-developed public transport systems. This study proposes new transit Voronoi diagram (T-VD) models for partitioning geographical space constrained by public transport networks. The proposed T-VD models explicitly consider the complexities of a public transport network, including transfers between different transport modes, dynamic transit schedules, changing network topologies, etc. To efficiently construct T-VDs, geo-computational algorithms are developed by modifying and integrating classical shortest-path algorithms in road networks and transit shortest-path algorithms in public transport networks. Case study results show significant differences between T-VDs and N-VDs, highlighting the need for using T-VDs in urban areas with well-developed public transport systems. The developed geo-computational algorithms efficiently constructed T-VDs in large-scale public transport networks within satisfactory computational times.
Highlights Transit Voronoi diagrams (T-VDs) for partitioning geographical space constrained by public transport networks. T-VDs consider the complexities of a public transport network, e.g., dynamic transit schedules. Efficient algorithms are developed to construct T-VDs. Case study results show significant differences between T-VDs and existing Voronoi diagrams.
Transit Voronoi diagrams in multi-mode public transport networks
Abstract Network Voronoi diagrams (N-VDs) are effective geometric constructions for partitioning geographical space constrained by road networks. However, they are not applicable for urban areas with well-developed public transport systems. This study proposes new transit Voronoi diagram (T-VD) models for partitioning geographical space constrained by public transport networks. The proposed T-VD models explicitly consider the complexities of a public transport network, including transfers between different transport modes, dynamic transit schedules, changing network topologies, etc. To efficiently construct T-VDs, geo-computational algorithms are developed by modifying and integrating classical shortest-path algorithms in road networks and transit shortest-path algorithms in public transport networks. Case study results show significant differences between T-VDs and N-VDs, highlighting the need for using T-VDs in urban areas with well-developed public transport systems. The developed geo-computational algorithms efficiently constructed T-VDs in large-scale public transport networks within satisfactory computational times.
Highlights Transit Voronoi diagrams (T-VDs) for partitioning geographical space constrained by public transport networks. T-VDs consider the complexities of a public transport network, e.g., dynamic transit schedules. Efficient algorithms are developed to construct T-VDs. Case study results show significant differences between T-VDs and existing Voronoi diagrams.
Transit Voronoi diagrams in multi-mode public transport networks
Chen, Bi Yu (author) / Teng, Wenxin (author) / Jia, Tao (author) / Chen, Hui-Ping (author) / Liu, Xianglong (author)
2022-06-14
Article (Journal)
Electronic Resource
English
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