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- W2914663242 abstract "This paper observes aggregated route choice patterns (i.e. vehicle distance traveled in different roadway classes, regional split ratios and average trip lengths) in a large scale mixed urban/freeway system through an extensive data set of 20,000 taxis in Shenzhen, China. It also reconstructs the aggregated patterns through shortest path algorithm that is based on various travel cost functions. We replace each observed trajectory with a shortest path that connects the same origin and destination points, and reproduce aggregated variables. We observe that link-level and regional interpretation of travel cost results in similar aggregated patterns. These results can enhance parsimonious network models and lead to better traffic predictions for large-scale congested networks." @default.
- W2914663242 created "2019-02-21" @default.
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- W2914663242 date "2016-01-01" @default.
- W2914663242 modified "2023-10-02" @default.
- W2914663242 title "Observing and reconstructing aggregated dynamic route choice patterns for large-scale mixed urban/freeway networks" @default.
- W2914663242 hasPublicationYear "2016" @default.
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