947 resultados para Trip purpose.


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Federal Highway Administration, Washington, D.C.

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Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

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Federal Highway Administration, Office of Highway Policy Information, Washington, D.C.

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Transportation Department, Office of Systems Engineering, Washington, D.C.

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Urban Mass Transportation Administration, Washington, D.C.

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Federal Highway Administration, Highway Statistics Division, Washington, D.C.

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Federal Highway Administration, Washington, D.C.

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Federal Highway Administration, Washington, D.C.

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Federal Highway Administration, Washington, D.C.

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Texas Department of Transportation, Austin

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Mode of access: Internet.

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Federal Highway Administration, Washington, D.C.

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Transportation Department, Office of University Research, Washington, D.C.

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Transportation Department, Office of University Research, Washington, D.C.

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Federal Highway Administration, Washington, D.C.