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dc.contributor.advisorChiu, Yi-Changen_US
dc.contributor.authorZhu, Lei
dc.creatorZhu, Leien_US
dc.date.accessioned2015-03-24T19:52:25Z
dc.date.available2015-03-24T19:52:25Z
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/10150/347053
dc.description.abstractThe transportation routing map is increasingly used in various transportation network modeling applications such as vehicle navigation and traffic assignment modeling. A typical navigation GIS map contains all detailed road facility layers and may not be as computationally efficient as a lower-resolution map for path finding. A lower-resolution transportation routing map retains only route-finding related roadways and is efficient for path finding but may result in sub-optimal routes because of misclassification links. With the goal in balancing the traffic analysis requirement of intended application and computation requirements of transportation navigation and traffic assignment, the systematic abstraction of the lower-resolution transportation routing map from high resolution map is an important and non-trivial task. For vehicle navigation applications, the traffic analysis requirement is the shortest path quality. An innovative transportation routing map abstraction method or Connectivity Enhancement Algorithm (CEA) is proposed to deal with vehicle navigation application routing map abstraction. The algorithm starts from a low-resolution network and keeps updating the map by adding links and nodes when it processes each search set. The outcome of the algorithm is an abstract map that retains the original detailed map's hierarchical structure with quality topological connectivity at a significant computations saving. With the development of traffic assignment modeling, a detailed network is desired to describe the real world traffic network. It is the consensus that one should not directly apply a GIS map blind-sight without a systematic approach and unnecessarily overuse the network details causes excessive run time. The traffic analysis requirement of those applications is the dynamic user equilibrium (DUE) condition network performance is identical or near-identical with high resolution network. The lowest network resolution level that meets the requirements of emerging traffic analysis is not easy to determine. The proposed traffic analysis network abstraction method gives a solution for this problem. It is an iterative network abstraction approach and considers the link travel time with DUE traffic condition. The case study and numerical analysis prove that the two network abstraction methods are sound and promising. The transportation routing map abstraction method could detect most misclassification links and is robust for different network scales. The abstracted navigation map provides the identical or near-identical SP cost/travel time for any OD pair while the computation burden is much lighter than that on original map. In another hand, the case studies about the traffic analysis network abstraction tell that the method converges very quick and the rendered the abstracted network that has lowest resolution of network or least links and nodes but the DUE condition network performance or trips cost/travel time is much closer to that on the original map.
dc.language.isoen_USen
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectGIS topology analysisen_US
dc.subjectnetwork abstractionen_US
dc.subjectshortest pathen_US
dc.subjectvehicle navigationen_US
dc.subjectCivil Engineeringen_US
dc.subjectdynamic traffic assignmenten_US
dc.titleRouting Map Topology Analysis and Applicationen_US
dc.typetexten
dc.typeElectronic Dissertationen
dc.contributor.chairChiu, Yi-Changen_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberChiu, Yi-Changen_US
dc.contributor.committeememberWu, Yao-Janen_US
dc.contributor.committeememberTong, Daoqinen_US
dc.contributor.committeememberFan, Nengen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineCivil Engineeringen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2018-06-14T11:40:12Z
html.description.abstractThe transportation routing map is increasingly used in various transportation network modeling applications such as vehicle navigation and traffic assignment modeling. A typical navigation GIS map contains all detailed road facility layers and may not be as computationally efficient as a lower-resolution map for path finding. A lower-resolution transportation routing map retains only route-finding related roadways and is efficient for path finding but may result in sub-optimal routes because of misclassification links. With the goal in balancing the traffic analysis requirement of intended application and computation requirements of transportation navigation and traffic assignment, the systematic abstraction of the lower-resolution transportation routing map from high resolution map is an important and non-trivial task. For vehicle navigation applications, the traffic analysis requirement is the shortest path quality. An innovative transportation routing map abstraction method or Connectivity Enhancement Algorithm (CEA) is proposed to deal with vehicle navigation application routing map abstraction. The algorithm starts from a low-resolution network and keeps updating the map by adding links and nodes when it processes each search set. The outcome of the algorithm is an abstract map that retains the original detailed map's hierarchical structure with quality topological connectivity at a significant computations saving. With the development of traffic assignment modeling, a detailed network is desired to describe the real world traffic network. It is the consensus that one should not directly apply a GIS map blind-sight without a systematic approach and unnecessarily overuse the network details causes excessive run time. The traffic analysis requirement of those applications is the dynamic user equilibrium (DUE) condition network performance is identical or near-identical with high resolution network. The lowest network resolution level that meets the requirements of emerging traffic analysis is not easy to determine. The proposed traffic analysis network abstraction method gives a solution for this problem. It is an iterative network abstraction approach and considers the link travel time with DUE traffic condition. The case study and numerical analysis prove that the two network abstraction methods are sound and promising. The transportation routing map abstraction method could detect most misclassification links and is robust for different network scales. The abstracted navigation map provides the identical or near-identical SP cost/travel time for any OD pair while the computation burden is much lighter than that on original map. In another hand, the case studies about the traffic analysis network abstraction tell that the method converges very quick and the rendered the abstracted network that has lowest resolution of network or least links and nodes but the DUE condition network performance or trips cost/travel time is much closer to that on the original map.


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