本文選題：智能交通系統(tǒng) + 車輛自組織網絡��； 參考：《計算機應用研究》2014年11期

【摘要】：隨著汽車保有量的迅速增加,城市道路交通擁堵變得尤為嚴重,精確地檢測交通態(tài)勢可以幫助緩解交通問題。為此,提出一種基于車輛自組織網絡(vehicular Ad hoc networks,VANETs)的交通態(tài)勢檢測方法——TraSDVANET(traffic situation detection method based on VANETs)。在該方法中,車輛自動聚簇,然后主動向簇頭匯報當前自身的位置和速度信息;簇頭根據收到的信息計算簇內的車輛密度和路面上的加權平均速度,之后基于模糊邏輯判斷簇內的交通態(tài)勢。仿真結果表明,在四種車輛場景下,TraSD-VANET檢測準確程度比協(xié)作檢測方法 CoTEC(cooperative traffic congestion detection)平均高16%。該方法在道路交通態(tài)勢檢測中有重要的應用價值。
[Abstract]:With the rapid increase of vehicle ownership, urban road traffic congestion becomes particularly serious, accurate detection of traffic situation can help alleviate traffic problems. Therefore, a traffic situation detection method based on vehicle Ad hoc Networks (Ad hoc Networks) is proposed. In this method, the vehicle clusters automatically, and then reports the current position and speed information to the cluster head, which calculates the vehicle density in the cluster and the weighted average speed on the road according to the information received. Then the traffic situation in the cluster is judged based on fuzzy logic. Simulation results show that the accuracy of TraSD-VANET detection in four vehicle scenarios is 16 times higher than that of collaborative detection method (CoTEC(cooperative traffic congestion detection). This method has important application value in road traffic situation detection.
【作者單位】： 電子科技大學移動互聯(lián)實驗室;
【基金】：國家自然科學基金資助項目(61071099)
【分類號】：TN929.5
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本文編號：1877077