| 研究生: |
吳昱達 Wu, Yu-Ta |
|---|---|
| 論文名稱: |
可靠度最佳化方法應用於不確定因素下之城市交通法規制定 Extension of Probabilistic Optimization to Urban Traffic Policy-Setting Under Uncertainty |
| 指導教授: |
詹魁元
Chan, Kuei-Yuan |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 機械工程學系 Department of Mechanical Engineering |
| 論文出版年: | 2010 |
| 畢業學年度: | 98 |
| 語文別: | 中文 |
| 論文頁數: | 75 |
| 中文關鍵詞: | 不確定因素下之最佳政策制定 、環境衝擊 、細胞自動機 、可靠度最佳化設計 、不確定因素模擬 |
| 外文關鍵詞: | Optimal Policy Setting under Uncertainty, Environmental Impact, Cellular Automata, Reliability-Based Design Optimization (RBDO), Uncertainty Modeling |
| 相關次數: | 點閱:109 下載:3 |
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交通運輸產生的汙染是城市中空氣汙染的主要來源,而在各類控制交通空氣汙染的方法中,交通管理方法具備了及時性、低研發成本、低推廣失敗風險等優點,因此利用制定適當的法規來控制交通空氣汙染已逐漸被重視。然而在進行法規決策時,環境中存在的不確定因素向來是決策的一大挑戰。
本研究將工程上可靠度最佳化設計的概念延伸至城市交通政策的決策上,首先參考多個現存的交通細胞自動機(CA)模型,發展出一套可模擬多線道汽機車混合車流的交通模型;將此交通模型搭配道路使用者平衡(UE)以用來模擬台南市汽機車的交通行為;利用與高斯擴散模型的結合,可有效評估交通汙染的濃度擴散情形。本論文除提出一套有系統的方法進行交通汙染的評估外,也探討特定政策下交通汙染對周邊造成的環境衝擊與各種不確定因素對環境衝擊的影響,進而實際應用在台南市區域的路網,展示如何應用可靠度最佳化方法來輔助交通法規的制定,在最佳化路網中行車成本的同時,也使道路周邊的空氣品質可符合環保法規限制之標準。
Decision-making in traffic regulations is challenging with uncertainty in the environment. In this research we extend probabilistic engineering design concepts to policy decision-making for urban traffic with variability from field data. City traffic is simulated using user equilibrium and cellular automata. A cellular automata (CA) model is developed by combing existing CA models with tailored rules for local traffic behaviors in Tainan, Taiwan. Both passenger sedans and motorcycles are considered with the possibility of passing between different types of vehicles. The tailpipe emissions from all mobile sources are modeled as Gaussian dispersion with finite line sources. Speed limits of all roads are selected as independent policy design variables, resulting in a problem with 50 dimensions. We first study the impacts of a particular policy-setting on traffic behaviors and on the environment under various sources of uncertainties. The genetic algorithm, combined with probabilistic analysis, is then used to obtain the optimal regulations with the minimal cost to the environment in compliance to the current ambient air quality standards.
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