【正文】 ns by keeping conflict traffic flows apart. The optimal performance of the signalized intersections is the bination of time value, environmental effects and traffic safety. Our goal is the optimal system, but we need to decide what attributes and weights will be used to judge optimality. The entire knowledge of the system designer about the process, traffic signal control in this case, to be controlled is stored as rules in the knowledge base. Thus the rules have a basic influence on the closedloop behaviour of the system and should therefore be acquired thoroughly. The development of rules is time consuming, and designers often have to translate process knowledge into appropriate rules. Sugeno and Nishida mentioned four ways to derive fuzzy control rules: 1. operators experience 2. control engineer39。. Taking this remark seriously, we study systematically manyvalued equivalence, . fuzzy similarity. It turns out that, starting from the Lukasiewicz welldefined manyvalued logic, we are able to construct a method performing fuzzy reasoning such that the inference relies only on experts knowledge and on welldefined logical concepts. Therefore we do not need any artificial defuzzification method (like Center of Gravity) to determine the final output of the inference. Our basic observation is that any fuzzy set generates a fuzzy similarity, and that these similarities can be bined to a fuzzy relation which turns out to a fuzzy similarity, too. We call this induced fuzzy relation total fuzzy similarity. Fuzzy IF THEN inference systems are, in fact, problems of choice: pare each IFpart of the rule base with an actual input value, find the most similar case and fire the corresponding THENpart。 ３ ? influence mode and route choice。結(jié)果對兩相控制和 PappisMamdani 控制表明 ,模糊控制應用領(lǐng)域很廣。該算法尋找最相似的實際 IFpart 輸入值 ,并給出了相應的 THENpart 然后被解雇了。摘要模糊控制是有能力處理多目標的、多維的和復雜的交通狀況 ,如交通信號。該主算子的來講模糊建模的控制措施 6。如果系統(tǒng)相關(guān)知識是為代表的 IFTHEN—— 簡單模糊控制器的規(guī)則 ,fuzzybased 可以控制系統(tǒng)具有效率及減輕。安全、最小化最大化 ,減少延遲環(huán)境方面的一些目標的控制 ,但這是很難處理大家聚在一起 ,傳統(tǒng)的交通信號控制。然而 ,交通系統(tǒng)的效率 ,甚至可以模糊。原來 ,從 Lukasiewicz 多值邏輯的定義 ,我們能構(gòu)建出一個模糊推理方法的表演 ,依賴于專家知識推理和只在定義的邏輯概念。不過它們當中的主要部分 ,受含糊不清的根基 。所以 ,它很可 能是很有競爭力的模糊控制在復雜真實的十字路口的地方傳統(tǒng)的優(yōu)化方法的使用是有問題的。對于好的結(jié)果 ,一個經(jīng)驗豐富的策劃人和微調(diào)領(lǐng)域中是必要的。降低汽車排放 ?、噪聲和視覺入侵 。檢測的發(fā)展和計算機技術(shù)改變了交通信號控制從定時開環(huán)規(guī)定自適應反饋控制。在 areawide 交 叉口控制偏移是之間也發(fā)生了變化。因為這個原因 ,自適應信號控制在大多數(shù)情況下不是建立在精確的優(yōu)化上 ,而是建立在綠色的擴展原理。事實上 ,最古老的文化之一的潛力的例子是一個模擬的模糊控制在一個 intersection 交通信號控制的兩個單向的街道。此外 ,模糊邏輯有能力理解語言指令和控制策略的基礎(chǔ)上產(chǎn)生的先驗的溝通。此外 ,專家系統(tǒng)的性能應相當于人類專家 :它應該得到同樣的結(jié)果 ,專家給 ,但提醒當控制問題是如此模糊 ,專家是不確定適當?shù)男袨椤Ｎ覀儼堰@稱為誘導模糊關(guān)系總模糊相似度。取決于權(quán)利的分配方式。 基于模糊邏輯控制器的設(shè)計來捕獲的關(guān)鍵因素 ,而不需要控制過程中許多詳細的數(shù)學公式。我們的目標是優(yōu)化系統(tǒng) ,但是我們需要來決定什么屬性和重量將被用來判斷最優(yōu)。 通常一個組合這些現(xiàn)象的一些方法是必要的 ,以獲得較好效果。這個規(guī)則庫的發(fā)展是在 1996 年秋季。結(jié)果對車輛和行人延誤或平均平均車輛延誤 ,在大多數(shù)情況下更好的在模糊相似度為基礎(chǔ)的控制比在其他的控制系統(tǒng)。最大的好處 ,或許 ,達到更復雜的十字路口和環(huán)境。 ? reduce vehicle emissions, noise and visual intrusion。s knowledge 3. fuzzy modelling of the operator39。Fuzzy membership...represents similarities of objects to imprecisely defined properties39。 原文： Intelligent traffic lights Abstract： Signal control is a necessary measure to maintain the quality and safety of traffic circulation. Further development of present signal control has great potential to reduce travel times, vehicle and accident costs, and vehicle emissions. The development of detection and puter technology has changed traffic signal control from fixedtime openloop regulation to adaptive feedback control. Present adaptive control methods, like the British MOVA, Swedish SOS (isolated signals)