【正文】 if it is not unique, use a criteria given by an expert to proceed. Based on the Lukasiewicz welldefined many valued logic, we show how this method can be carried out formally. Hypothesis and Principles of Fuzzy Traffic Signal Control Traffic signal control is used to maximize the efficiency of the existing traffic systems [6]. However, the efficiency of traffic system can even be fuzzy. By providing temporal separation of rights of way to approaching flows, traffic signals exert a profound influence on the efficiency of traffic flow. They can operate to the advantage or disadvantage of the vehicles or pedestrians。 ? improve priority for buses, trams and other public service vehicles。改進的最大延時超過 20%,這意味著模糊控制的效率可以比傳統(tǒng)的 vehicleactuated 控制的效率。交通信號控制系統(tǒng)三個現(xiàn)實的方法來構(gòu)造算法和仿真模型檢驗他們的表現(xiàn)。模糊控制的典型優(yōu)點是簡單的流程 ,有效控制 ,提高產(chǎn)品質(zhì)量 。髓啟發(fā)式的設(shè)計規(guī)則 7。的主要目標是確保交通信號控制交叉 口安全系統(tǒng)通過保持沖突交通流分開。 causeconsequence 關(guān)系的解釋也不可能在交通信號控制。通過提供時間分離的權(quán)利的方式接近流動 ,交通信號產(chǎn)生深刻影 響了效率的交通流。所以 ,我們不需要任何人造的解模糊化方法確定 (如重心 )決定最后輸出的推斷。即使它們大都是古典數(shù)學方法表現(xiàn)更好 ,他們還帶有黑色的盒子 ,如德模糊化 ,這是很難證明數(shù)學或邏輯的。 2．模糊邏輯：介紹了模糊邏輯 ,并成功地應(yīng)用于大范圍的自動控制任務(wù)。模糊控制已經(jīng)被證明是成功的 ,在這些問題中 ,精確的數(shù)學建模是困難的或不可能的 ,但一名有經(jīng)驗的 人可以控制的工藝操作。為所有道路改善安全 ?用戶群。目前的自適應(yīng)控制方法 ,像英國、瑞典 MOVA SOS)和英國 (孤立的信號 (areawide 又控制 ),采用數(shù)學優(yōu)化與仿真技術(shù)來調(diào)整信號波動的時間觀察到的交通流實時的。優(yōu)化是通過改變時間和周期長度的綠色的信號。 在自適應(yīng)交通信號控制的彈性增強的增加的數(shù)量在 周期層疊的綠色階段 ,從而使數(shù)學優(yōu)化非常復(fù)雜和困難。因此 ,交通信號控制是一種適合于任務(wù)特別為模糊控制。最大的好處模糊邏輯是有機會模型與不確定的模糊決策。例如 ,如果 然后模糊規(guī)則 ,它們在核心的模糊推理系統(tǒng) ,經(jīng)常報道的工作方式 ,是 Ponens概括規(guī)則推理機制的經(jīng)典 ,但隨便起來就不是這樣的 ,這之間的關(guān)系 ,這些規(guī)則和多值邏輯是任何已知的復(fù)雜和人工。我們基本的觀察是 ,任何的模糊集的生成一個模糊相似度 ,這些相似之處可以結(jié)合到一個模糊關(guān)系 ,變成了一個模 糊相似度 ,太。它們能操控的優(yōu)勢或者劣勢的車輛和行人的 。這些都是典型特征的模糊控制。最優(yōu)性能的十字路口相結(jié)合的系統(tǒng)工程 ,環(huán)境影響時間價值和交通安全。往往在線改編的規(guī)則。 3． FUSICO： FUSICOproject 塑造出的經(jīng)驗的警察。要解決問題 ,類似的仿真 Mamdani nonfuzzy和古典風格的模糊推理系統(tǒng) ,也是。 根據(jù)這些結(jié)果 ,我們可以說 ,模糊信號控制可以多目標和更有效率 ,比常規(guī)自適應(yīng)信號控制現(xiàn)在。 ? provide better and safer facilities for pedestrians, cyclists and other vulnerable road users。 depend on how the rights of ways are allocated. Consequently, the proper application, design, installation, operation, and maintenance of traffic signals is critical to the orderly safe and efficient movement of traffic at intersections. In traffic signal control, we can find some kind of uncertainties in many levels. The inputs of traffic signal control are inaccurate, and that means that we cannot handle the traffic of approaches exactly. The control possibilities are plicated, and handling these possibilities are ５ an extremely plex task. Maximizing safety, minimizing environmental aspects and minimizing delays are some of the objectives of control, but it is difficult to handle them together in the traditional traffic signal control. The causeconsequence relationship is also not possible to explain in traffic signal control. These are typical features of fuzzy control. Fuzzy logic based controllers are designed to capture the key factors for controlling a process without requiring many detailed mathematical formulas. Due to this fact, they have many advantages in real time applications. The controllers have a simple putational structure, since they do not require many numerical calculations. The IFTHEN logic of their inference rules does not require much putational time. Also, the controllers can operate on a large range of inputs, since different sets of control rules can be applied to them. If the system related knowledge is represented by simple fuzzy IFTHEN rules, a fuzzybased controller can control the system with efficiency and ease. The main goal of traffic signal control is to ensure safety at signalized intersectio