國立虎尾科技大學 |

Space-Time Transportation System Modelling : = From Traveler's Characteristics to the Network Design Problem.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Space-Time Transportation System Modelling :/
其他題名:	From Traveler's Characteristics to the Network Design Problem.
作者:	Parsafard, Mohsen.
面頁冊數:	1 online resource (123 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: A.
標題:	Transportation. -
電子資源:	click for full text (PQDT)
ISBN:	9780355103953

Space-Time Transportation System Modelling : = From Traveler's Characteristics to the Network Design Problem.
Parsafard, Mohsen.

Space-Time Transportation System Modelling :From Traveler's Characteristics to the Network Design Problem. - 1 online resource (123 pages)

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: A.

Thesis (Ph.D.)--University of South Florida, 2017.

Includes bibliographical references

Traditional network design problems only consider the long-term stationary travel patterns (e.g., fixed OD demand) and short-term variations of human mobility are ignored. This study aims to integrate human mobility characteristics and travel patterns into network design problems using a space-time network structure. Emerging technologies such as location-based social network platforms provide a unique opportunity for understanding human mobility patterns that can lead to advanced modeling techniques. To reach our goal, at first multimodal network design problems are investigated by considering safety and flow interactions between different modes of transport. We develop a network reconstruction method to expand a single-modal transportation network to a multi-modal network where flow interactions between different modes can be quantified. Then, in our second task, we investigate the trajectory of moving objects to see how they can reveal detailed information about human travel characteristics and presence probability with high-resolution detail. A time geography-based methodology is proposed to not only estimate an individual's space-time trajectory based on his/her limited space-time sample points but also to quantify the accuracy of this estimation in a robust manner. A series of measures including activity bandwidth and normalized activity bandwidth are proposed to quantify the accuracy of trajectory estimation, and cutoff points are suggested for screening data records for mobility analysis.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355103953Subjects--Topical Terms:

558117
Transportation.
Index Terms--Genre/Form:

554714
Electronic books.

Space-Time Transportation System Modelling : = From Traveler's Characteristics to the Network Design Problem.
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500 $a Source: Dissertation Abstracts International, Volume: 78-12(E), Section: A.
500 $a Adviser: Xiaopeng Li.
502 $a Thesis (Ph.D.)--University of South Florida, 2017.
504 $a Includes bibliographical references
520 $a Traditional network design problems only consider the long-term stationary travel patterns (e.g., fixed OD demand) and short-term variations of human mobility are ignored. This study aims to integrate human mobility characteristics and travel patterns into network design problems using a space-time network structure. Emerging technologies such as location-based social network platforms provide a unique opportunity for understanding human mobility patterns that can lead to advanced modeling techniques. To reach our goal, at first multimodal network design problems are investigated by considering safety and flow interactions between different modes of transport. We develop a network reconstruction method to expand a single-modal transportation network to a multi-modal network where flow interactions between different modes can be quantified. Then, in our second task, we investigate the trajectory of moving objects to see how they can reveal detailed information about human travel characteristics and presence probability with high-resolution detail. A time geography-based methodology is proposed to not only estimate an individual's space-time trajectory based on his/her limited space-time sample points but also to quantify the accuracy of this estimation in a robust manner. A series of measures including activity bandwidth and normalized activity bandwidth are proposed to quantify the accuracy of trajectory estimation, and cutoff points are suggested for screening data records for mobility analysis.
520 $a Finally, a space-time network-based modeling framework is proposed to integrate human mobility into network design problems. We construct a probabilistic network structure to quantify human's presence probability at different locations and time. Then, a Mixed Integer Nonlinear Programming (MINLP) model is proposed to maximize the spatial and temporal coverage of individual targets. To achieve near optimal solutions for large-scale problems, greedy heuristic, Lagrangian relaxation and simulated annealing algorithms are implemented to solve the problem. The proposed algorithms are implemented on hypothetical and real world numerical examples to demonstrate the performance and effectiveness of the methodology on different network sizes and promising results have been obtained.
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538 $a Mode of access: World Wide Web
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