本文關(guān)鍵詞：基于多智能體分群同步的城市路網(wǎng)交通控制　出處：《控制理論與應(yīng)用》2014年11期 　論文類型：期刊論文

  更多相關(guān)文章： 城市交通網(wǎng)絡(luò) 過(guò)飽和 交通控制 多智能體系統(tǒng) 分群同步

【摘要】：在城市交通網(wǎng)絡(luò)中,經(jīng)常出現(xiàn)某些路段較為擁堵,而其它路段內(nèi)仍有空間未被充分利用.為了解決該問(wèn)題,本文提出一種路網(wǎng)分群一致算法.首先,以路段的空間占有率為狀態(tài),建立交通網(wǎng)絡(luò)狀態(tài)空間模型,描述路網(wǎng)中車流的傳遞關(guān)系;進(jìn)一步,將路網(wǎng)中的各條路段抽象為智能體,提出路網(wǎng)多智能體分群一致算法,將路段集劃分為若干個(gè)非空不交子集,每個(gè)子集內(nèi)的路段狀態(tài)可達(dá)一致,不同子集的一致?tīng)顟B(tài)不同.從而,該算法可使各路段的空間占有率達(dá)到均衡,減輕局部擁堵,減少車輛延誤時(shí)間.最后,采用VISSIM交通仿真軟件對(duì)北京市望京地區(qū)的實(shí)際網(wǎng)絡(luò)進(jìn)行仿真,仿真結(jié)果說(shuō)明了本文方法的可行性和有效性.
[Abstract]:In the city traffic network, often appear some sections of more congestion, while other sections are still in the space is not fully utilized. In order to solve this problem, this paper proposes a network clustering consensus algorithm. Firstly, the road space occupancy status, establish traffic network state space model, describing the transfer relation of road network traffic flow further, the roads; road network is abstracted as agent, multi-agent network proposed clustering algorithm is consistent, will be divided into several sections in non empty subset, within each subset of link state reachability, different subsets of different consistent state. Thus, the algorithm can make each section of the space occupancy in equilibrium, relieve local congestion, reduce vehicle delay time. Finally, the actual network of Wangjing area in Beijing city was simulated using VISSIM traffic simulation software, the simulation shows that the method in this paper The feasibility and effectiveness of it.

【作者單位】： 北方工業(yè)大學(xué)城市道路交通智能控制技術(shù)北京市重點(diǎn)實(shí)驗(yàn)室;北京交通大學(xué)交通運(yùn)輸學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(51308005) 北京市教委科研計(jì)劃項(xiàng)目(PXM2013_014212_000031) 北京市屬高等學(xué)校高層次人才引進(jìn)與培養(yǎng)計(jì)劃項(xiàng)目(CIT&TCD201304002)
【分類號(hào)】：U491.54;TP18
【正文快照】： Urban traffic network control based on cluster consensus ofmulti-agent systemsWANG Li1,LI Dai、HE Zhong-he1,MA Xu-hui2(1.Beijing Key Lab of Urban Intelligent Traffic Control Technology,North China University of Technology,Beijing 100144,China;2.School of

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本文編號(hào)：1399475