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Multi-resolution Analysis of Disruptions in Different Urban Network Configurations Under Varying Information Scenarios
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Multi-resolution Analysis of Disruptions in Different Urban Network Configurations Under Varying Information Scenarios. |
| 개인저자 | Yu, Zhengyao. |
| 단체저자명 | The Pennsylvania State University. Civil and Environmental Engineering. |
| 발행사항 | [S.l.]: The Pennsylvania State University., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 145 p. |
| 기본자료 저록 | Dissertations Abstracts International 80-12B. Dissertation Abstract International |
| ISBN | 9781392319093 |
| 학위논문주기 | Thesis (Ph.D.)--The Pennsylvania State University, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
Publisher info.: Dissertation/Thesis. Advisor: Gayah, Vikash V. |
| 요약 | Urban networks are suffering more congestion than ever. Aside from recurrent congestion resulting from bottlenecks and signal timing, it is estimated that about 40 percent of the congestion is caused by non-recurring disruptions such as crashes, work zones, and special events. Although many recent works have studied the capacity and efficiency of different network configurations, their performance under such non-recurring disruptions is currently missing in the literature.This dissertation compares three street network configurations under both prior-knowledge and no-prior-knowledge disruptions, where drivers do and do not know about the disruptions ahead of time. Two-way (TW), two-way with prohibited left-turn movements (TWL), and one-way (OW) networks are studied and compared with three approaches at different levels of fidelity. First, a simplified analytical method is applied to networks under light traffic conditions, where drivers are assumed to take the shortest physical route with the fewest turning maneuvers. This step provides initial insights into the problem through paper-and-pen analysis. Second, the Link Transmission Model (LTM) is applied to the networks for light-to-medium traffic demands. Traffic signals will be added at this step and drivers will be routed based on experienced travel time on the links. As a numerical solution to the kinematic wave theory, the LTM can capture network dynamics including intersection spillbacks, which makes it an ideal intermediate model between simplified analytical approach and more comprehensive microscopic simulation. Finally, the networks are tested in a microscopic traffic simulation environment for more detailed and realistic outputs. In addition, mitigation strategies that provide early disruption notification to a subset of vehicles either locally or globally in the networks are also tested in the simulation environment.Based on the results of the experiments, it is recommended that the TW network should be used when traffic demands are expected to be moderate. Because of its flexibility, the TW network can accommodate link disruptions that might occur as long as the network capacity is still higher than the traffic demand. However, the TW network has limited capacity so performs poorly under high traffic demands. For networks operating under high demands, the TWL network is recommended due to its large capacity that allows it to absorb the negative impacts of link disruptions. For all network configurations, it is important to provide road users with early notification to offset the negative impacts when disruptions occur within the most critical (central) part of the network. In the TW network, this is best done using VMSs placed near the disruption while in the TWL network it is more efficient to use a broadcasting strategy (e.g., using in-vehicle navigation systems). For disruptions near the network periphery, no prior information should be provided to road users so that the detour traffic is more likely to use links outside the central area with relatively low traffic, which provides a more even congestion distribution. |
| 일반주제명 | Civil engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
