本文選題：高速公路 + 模糊C-均值��； 參考：《華南理工大學學報(自然科學版)》2014年12期

【摘要】：目前高速公路交通數據資源未得到充分利用,使得管理和建設成本較高的高速公路聯網收費系統只能實現車輛記錄、聯網收費等初級功能,導致交通數據資源的嚴重浪費.為此設計了基于高速公路聯網收費數據的路段行程時間估計方法,提出以大、小車速度變化情況為基礎,采用模糊C-均值聚類方法對高速公路交通狀態(tài)進行判別,并應用VISSIM軟件分別對上述兩種方法驗證分析.結果表明,路段行程時間估計方法能夠獲得高質量的路段行程時間數據,同時交通狀態(tài)判別方法也能夠準確判別出道路上所呈現的交通狀態(tài),可為歷史數據更新提供技術支持,為高速公路交通管理部門提供精確的決策依據.
[Abstract]:At present, the highway traffic data resources have not been fully utilized, making the expressway network toll system with high cost of management and construction can only realize the primary function of vehicle record, network charge and so on, which leads to the serious waste of traffic data resources. Therefore, a road travel time estimator based on the toll data of high-speed public road network is designed. On the basis of the change of the speed of large and small cars, the fuzzy C- means clustering method is used to distinguish the traffic state of the expressway, and the above two methods are verified and analyzed with the VISSIM software. The results show that the link travel time estimation method can obtain the high quality section travel time data, and the traffic state is judged at the same time. The other methods can also accurately identify the traffic status on the road, providing technical support for the updating of historical data and providing accurate decision-making basis for the highway traffic management department.
【作者單位】： 吉林大學汽車仿真與控制國家重點實驗室;吉林大學交通學院;
【基金】：國家科技支撐計劃項目(2014BAG03B03) 山東省省管企業(yè)科技創(chuàng)新項目(20122150251-5)
【分類號】：U491

【參考文獻】

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本文編號：2085917