混合車流下之綠色適應性交通號誌控制模式

Abstract

傳統號誌控制模式強調路口車流延滯之最小化或者是幹道續進車流速度之最大化。然而，為能達到永續目標，應改以能源消耗及污染排放減量作為號誌控制模式之績效評估指標。特別是接近環境敏感地區（如學校、醫院及住宅區）的路口，應將污染濃度標準上限作為號誌控制模式之限制條件之一。為能有效進行號誌控制模式之最佳化過程，一個中觀車流模式：格位傳遞模式（CTM ; Daganzo, 1994; 1995），能夠有效及精確地模擬不同車流狀態下之車流運作行為。惟CTM原係針對純車流設計，並未考量混合車流行為。然在許多亞洲城市中，機車是一項非常普遍且常見的運具。但機車運行行為與汽車及公車明顯不同，它不必遵循車道線。事實上，機車常與許多車輛同在一車道內，不符傳統跟車理論，導致許多車流模擬模式無法模擬機車車流行為。 基此，本研究擬以三個研究年度進行研究。其中，第一個研究年期已獲貴會補助（NSC 100-2221-E- 009-121），研究主題為：建立及驗證混合車流格位傳遞模式，旨在考量不同交通組成（汽車及機車）及不同交通狀態下，不同車種進入下一格位時之競爭行為，建立一個混合車流格位傳遞模式，並透過實地車流資料調查與比較，驗證模式之準確性，其成果已於2011年接受發表於運輸學刊（TSSCI）。同時也透過簡單之污染排放與擴散模式，建構一混合車流污染排放與擴散模式，並發表於中華民國運輸學會100年學術論文研討會，該文也被推薦收錄於運輸學刊（TSSCI）。基此，本研究擬以此一研究成果為基礎，以兩個研究年期繼續進行下列研究： 1.第一個研究年期：建立混合車流污染排放與擴散模式 本研究將以第一個研究年期所建立的混合車流模式為基礎，進一步推估在不同交通組成及狀態下之能源消耗與污染排放總量。進而，納入污染擴散模式以推估路口不同距離下之污染濃度擴散情形。 2.第二個研究年期：建立交通感應式號誌控制模式 本研究將進一步建立交通感應式號誌控制模式，能同時最小化能源消耗及污染排放總量，並符合路側環境敏感地區之污染濃度限制。

Traditional traffic signal control models aim to minimize traffic delay at intersections or maximize travel speed along a corridor. However, in order to achieve sustainability, the performance of traffic signal control models should be evaluated by their capacities in reducing energy consumption and emissions of traffic. Especially, at the intersections near the environmental sensitive areas, such as schools, hospitals, residential areas, a limitation of emission concentration should be considered while optimizing the traffic signal timing plan. To efficiently facilitate the optimization process of traffic signal control models, a mesoscopic traffic simulation model, Cell Transmission Model (CTM), proposed by Daganzo (1994, 1995), has been proven that it can accurately replicate the traffic behaviors under various traffic conditions. The CTM is originally designed for pure traffic simulation. However, motorcycles are prevailing in many Asian cities. Unlike most cars and buses which will move within the lane, motorcycles in practice do not follow the lane disciplines. Motorcycles in effect move in a rather erratic manner without obeying the lane disciplines. Sometimes the motorcycles follow the lead vehicles; but more than often, they share the “same lane” with the moving cars or break into two moving cars in the same lane. Consequently, many traffic simulation models have limited capability in capturing the movement behaviors of motorcycles. Based on our previous project entitled as “Green traffic-responsive signal control model under mixed traffic conditions” (NSC 100-2221-E-009-121), in the first research year, this study will further extend the mixed traffic simulation to energy consumption and emissions under various traffic compositions and conditions (free-flow, synchronized and congested). In addition, the diffusion model of emitted pollutions from these moving vehicles will be also developed so as to estimate the emission concentration at an arbitrary distance from the road. In the second year, this study will develop a traffic-responsive signal control model, which can adaptively optimize the signal control mechanism along a corridor to meet the limitation of emission concentration near road-side sensitive areas and to minimize energy consumption and emissions.