智能交通信號燈畢業(yè)設(shè)計(jì)外文翻譯-交通線路-文庫吧
2025-04-17 00:49 本頁面
【正文】 秋季。 j . they Kari 正常 ,經(jīng)驗(yàn)豐富的交通信號規(guī)劃師 ,工作時(shí)在赫爾辛基理工大學(xué)在這個(gè)時(shí)間。每天工作小組討論 ,他的經(jīng)驗(yàn)幫助我們模型對我們的規(guī)則。 在特定情況下病理交通擁堵或 很少有車輛在循環(huán) 。在那里 firstinfirstout 是唯一合理的控制策略。該算法尋找最相似的實(shí)際 IFpart 輸入值 ,并給出了相應(yīng)的 THENpart 然后被解雇了。交通信號控制系統(tǒng)三個(gè)現(xiàn)實(shí)的方法來構(gòu)造算法和仿真模型檢驗(yàn)他們的表現(xiàn)。要解決問題 ,類似的仿真 Mamdani nonfuzzy和古典風(fēng)格的模糊推理系統(tǒng) ,也是。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)。比較模糊相似度為基礎(chǔ)的模糊控制的控制和 Mamdani 風(fēng)格也強(qiáng)度的假定 ,在近似推理過 程中時(shí) ,一個(gè)基本概念是多值之間的相似的對象 ,而不是一種概括規(guī)則的推理方式 ,Ponens 經(jīng)典。 FUSICO 項(xiàng)目結(jié)果 這個(gè)計(jì)畫的結(jié)果表明 ,模糊信號控制的潛力是孤立交叉口控制的一種方法。比較結(jié)果的PappisMamdani 控制、模糊孤立的人行過街和模糊兩階段的控制是很不錯(cuò)的。結(jié)果表明 ,孤立的人行過街的模糊控制提供了有效的兩種對立的目標(biāo)妥協(xié) ,最低行人延誤和最小的車輛的延誤。結(jié)果對兩相控制和 PappisMamdani 控制表明 ,模糊控制應(yīng)用領(lǐng)域很廣。改進(jìn)的最大延時(shí)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。 根據(jù)這些結(jié)果 ,我們可以說 ,模糊信號控制可以多目標(biāo)和更有效率 ,比常規(guī)自適應(yīng)信號控制現(xiàn)在。最大的好處 ,或許 ,達(dá)到更復(fù)雜的十字路口和環(huán)境。這 FUSICOproject 仍在繼續(xù)。目的是將一步步的更復(fù)雜的交通信號 ,并繼續(xù)對模糊控制理論著作。第一個(gè)例子將公共交通優(yōu)先考慮的問題。 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) and British SCOOT (areawide control), use mathematical optimization and simulation techniques to adjust the signal timing to the observed fluctuations of traffic flow in real time. The optimization is done by changing the green time and cycle lengths of the signals. In areawide control the offsets between intersections are also changed. Several methods have been developed for determining the optimal cycle length and the minimum delay at an intersection but, based on uncertainty and rigid nature of traffic signal control, the global optimum is not possible to find out. ： As a result of growing public awareness of the environmental impact of road traffic many authorities are now pursuing policies to: ? manage demand and congestion。 ３ ? influence mode and route choice。 ? improve priority for buses, trams and other public service vehicles。 ? provide better and safer facilities for pedestrians, cyclists and other vulnerable road users。 ? reduce vehicle emissions, noise and visual intrusion。 and ? improve safety for all road user groups. In adaptive traffic signal control the increase in flexibility increases the number of overlapping green phases in the cycle, thus making the mathematical optimization very plicated and difficult. For that reason, the adaptive signal control in most cases is not based on precise optimization but on the green extension principle. In practice, uniformity is the principle followed in signal control for traffic safety reasons. This sets limitations to the cycle time and phase arrangements. Hence, traffic signal control in practice are based on tailormade solutions and adjustments made by the traffic planners. The modern programmable signal controllers with a great number of adjustable parameters are well suited to this process. For good results, an experienced planner and finetuning in the field is needed. Fuzzy control has proven to be successful in problems where exact mathematical modelling is hard or impossible but an experienced human can control the process operator. Thus, traffic signal control in particular is a suitable task for fuzzy control. Indeed, one of the oldest exa
畢業(yè)設(shè)計(jì)相關(guān)推薦
鄂ICP備17016276號-1