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  • 學位論文

考量旅次起迄需求量下車輛偵測器佈設策略之研究

A Study on Vehicle Detector Deployment Configuration Strategies by Considering the Estimation of Origin-Destination Demands Using Link Traffic Flows

指導教授 : 胡守任

摘要


旅次起迄(Trip Origin-Destination, OD)為影響交通狀況的重要因素之一,旅次起迄資料主要說明在特定區域內的旅行方向、運具移動型態、旅次長度等資訊,無論在運輸規劃、路網設計,以及場站選擇中,皆提供重要的資訊。 旅次起迄量等資訊之獲得實屬不易,隨著路段車流資料蒐集技術的進步,多利用車輛偵測器蒐集路網相關交通流量資料,進一步利用於各項有用的交通相關資訊之推估,因此在兼顧獲得足夠且有效的交通資訊以及降低偵測器佈設成本之下,如何有效的將車輛偵測器適量、適所的佈設與使用,對於OD推估工作有很大的影響,因此本研究主要的目的在於探討如何在有限的資源下,進行偵測器佈設策略的擬定,進一步獲得較佳的交通參變數推估值,該議題亦為目前進行現代化交通管理工作中重要的一環。 由於偵測器佈設之課題,較屬於長期運輸規劃之議題,因此,本研究擬以交通量指派理論為基礎,以適當的描述路網均衡下路徑選擇之情形,並進行旅次起迄與偵測器佈設問題之求解。在求解使用者均衡之交通量指派問題上,透過梯度投影法(Gradient projection, GP)求解,並獲得以路徑為基礎的相關資訊;在流量倒推旅次起迄量的課題上,由於真實OD量未知,故使用基本的最小平方估計量,進行旅次起迄需求涵蓋量的推估與檢驗。本研究針對上述議題,從靜態長期運輸規劃的觀點出發,構建相關的數學解析性模型,並進行數學規劃模式的求解與分析。 在數值分析方面,本研究針對前述數學規劃模式以及線性獨立路段佈設策略進行小、中、大型路網,以及原始OD需求和兩倍OD需求的測試,根據模式測試結果顯示,透過有限數量及策略性的佈設車輛偵測器,即能夠獲得有效的路網旅次起迄資訊涵蓋,並且偵測器佈設數量隨著路網規模及路網運輸需求的提升,亦隨之增加;而在線性獨立佈設策略部份,在路段觀測流量未知之情形下,藉由歷史OD需求量,可以有效提供路網中偵測器佈設策略之擬定,在中、小型路網規模下,能夠獲得有效的資訊涵蓋量,並且在大型路網中,亦能夠獲得不錯的路網資訊量。

並列摘要


Trip origin-destination (OD) is one of the crucial factors that affect traffic state in a highway network. Network OD data depict both the spatial and temporal distributions of corresponding trip demands, including travel direction, route choice, departure time, and trip length, etc. Therefore, it is one of the key components in transportation planning, network design, and terminal selection. However, in practice it is not easy to collect true OD trip demands. As the development of traffic flow data collection technology, link traffic flows data are collected by vehicle detector and used to infer network OD trip demands. Therefore, an effective vehicle detector deployment plan is one of the key issues in modern traffic control and management. The vehicle detector deployment configuration problem is essentially a long-term transportation planning issue. The purpose of the present research is to conduct route choice behavior description and model solving by traffic assignment theorem. Furthermore, we solve the user equilibrium (UE) problem by gradient projection method (GP) to obtain some additional path-based information. Since true OD trip demands are unknown, we conduct OD demand estimation and OD demand covering rate verification by the least square estimator. To summarize all of above, the present research is based on static transportation planning to construct mathematical analytical models and model solving and analysis. To demonstrate the feasibility of the proposed models, some simplified networks including small, middle, and large network sizes were employed to conduct the case study under original trip OD demands and twice of the OD demands. The numerical results indicate that using finite quantity of vehicle detectors and deployed it strategically can obtain effective network trip OD information coverage. Besides, the number of deployed vehicle detectors increase with the scale of network size and network OD demands. The result of linearly independent deployment configuration strategies indicate that by only means of prior OD demands can find the relatively important links of all without link traffic flow measurements. Moreover, linearly independent deployment configuration strategies can obtain excellent OD demand covering rate on the cases of small and middle network, and satisfactory results for the large network cases.

參考文獻


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被引用紀錄


鄭家豪(2015)。電子收費系統資料於交通管理策略之研究〔碩士論文,逢甲大學〕。華藝線上圖書館。https://doi.org/10.6341%2ffcu.M0206417
林明鴻(2014)。主要路段旅次指派模型-以台北車站周圍交通為例〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0006-2907201416020400

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