本文選題：路徑規(guī)劃　切入點：時間可靠性　出處：《北京交通大學》2017年碩士論文

【摘要】：隨著經濟社會的發(fā)展,城市規(guī)模的不斷擴大,城市人口顯著增長,機動車保有量顯著增加,城市交通供需矛盾導致的擁堵問題日漸突出。如何提高城市居民的出行效率,緩解城市交通擁堵,成為交通科學關注的一個重要科學問題。其中,如何準確的找到可靠最短路徑引起了交通科學領域研究者的普遍關注。本文目標是為出行者提供出行時間依概率可靠的路徑規(guī)劃方案。(1)總結了三種典型的可靠最短路徑模型(TTB模型、METT模型、MMD模型),通過分析各模型的適用條件,發(fā)現魯棒性下的MMD模型在高延遲路網中會產生過多可選擇路徑(通過在測算路網中放大各個路段的最大延遲倍數,算法就會生成過多的路徑選擇),從而導致最可靠路徑的信息被掩蓋。通過比較魯棒性模型和非魯棒性模型的關聯性,發(fā)現可以利用概率分布函數擬合最大延遲參數,保證MMD模型只產生一條可靠路徑。(2)考慮實際交通狀況與不同居民的出行需求,提出了 3種改進的啟發(fā)式函數的定義。1、回避擁堵。利用路段的實際距離與其對應的85%車速,估算路段出行時間;通過Dijkstra最短路徑估算當前節(jié)點至終點的最少出行時間。2、路段歷史平均出行時間最短。利用路段不同時間間隔下平均通行時間的最小值,估算路段出行時間;通過Dijkstra最短路徑估算當前節(jié)點至終點的最少出行時間。3、躲避信號交叉口。考慮到信號燈等待時間,對于一次出行的總時間有較大影響,我們提出了以經過的交叉口數作為路徑通行時間估計的啟發(fā)式函數。(3)利用北京市浮動車數據,通過擬合數據說明對路段通行時間正態(tài)分布假設的合理性;通過對比靜態(tài)下早、晚高峰時段不同風險態(tài)度人群面對同一OD對的路徑選擇,發(fā)現北京晚高峰時段交通擁堵更嚴重;研究還發(fā)現,三種改進的啟發(fā)式函數定義均能有效降低算法復雜度,并提高計算效率。特別是定義(2)和定義(3),可以將計算效率提高到原算法計算效率的10倍。本文利用北京市交通實際數據對可靠最短路徑的模型與算法展開了深入研究�？偨Y了不同模型之間的特點,針對TTB模型下的A*啟發(fā)式算法提出三種改進方式,并利用實際路網進行了驗證。本文的研究工作,將為城市居民獲得出行時間依概率可靠的路徑規(guī)劃方案提供理論基礎。
[Abstract]:With the development of economy and society, the urban scale is expanding, the urban population is increasing significantly, the number of motor vehicles is increasing significantly, and the congestion problem caused by the contradiction of urban traffic supply and demand is becoming more and more serious. How to improve the travel efficiency of urban residents? Alleviating urban traffic jams has become an important scientific issue in traffic science. Among them, How to find the reliable shortest path accurately has aroused the widespread concern of the researchers in the field of transportation science. The aim of this paper is to provide the travelers with the travel time according to the probability of reliable path planning scheme. Short path model TTB model METT model MMD model, through the analysis of the applicable conditions of each model, It is found that the MMD model under robustness can produce too many alternative paths in high delay road networks. By comparing the correlation between the robust model and the non-robust model, it is found that the probability distribution function can be used to fit the maximum delay parameters. To ensure that only one reliable path is generated in the MMD model, taking into account the actual traffic situation and the travel needs of different residents, the definition of three improved heuristic functions is put forward to avoid congestion. The actual distance of the road section and the corresponding 85% speed are used. Estimating the travel time of road section, estimating the minimum travel time from the current node to the end point by Dijkstra shortest path, and the average travel time of the road section is the shortest. Using the minimum value of the average travel time at different time intervals, the travel time of the road section is estimated. The shortest path of Dijkstra is used to estimate the minimum travel time from the current node to the terminal, and to avoid the signalized intersection. Considering the waiting time of the signal light, it has a great influence on the total travel time. We propose a heuristic function of using the number of intersection passes as the heuristic function to estimate the passage time.) using the floating vehicle data in Beijing, we illustrate the rationality of the assumption of normal distribution of road passage time by fitting the data. It is found that traffic congestion is more serious in Beijing during late rush hour when people with different risk attitudes face the same OD pair. The study also finds that the three improved heuristic function definitions can effectively reduce the complexity of the algorithm. The computational efficiency can be improved by 10 times that of the original algorithm, especially the definition of 2) and the definition of "3". In this paper, the model and algorithm of reliable shortest path are deeply studied by using the actual traffic data in Beijing. The characteristics of different models are summarized. This paper proposes three improved methods for the A- heuristic algorithm based on TTB model and verifies it by using the actual road network. The research work in this paper will provide a theoretical basis for urban residents to obtain a reliable path planning scheme of travel time depending on probability.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U491

【參考文獻】

相關期刊論文 前10條

1 李軍;徐志勝;宋占峰;楊峰;吳恩琦;;基于圖論的最低風險水平線路方案自動搜索算法[J];鐵道科學與工程學報;2016年04期

2 張衛(wèi)華;陳俊杰;江楠;;考慮交通能源消耗的出行需求管理策略研究[J];系統(tǒng)工程學報;2015年04期

3 段宗濤;WANG Wei-xing;康軍;李瑩;鄭西彬;程豪;劉研;;面向城市交通網絡的K最短路徑集合算法[J];交通運輸系統(tǒng)工程與信息;2014年03期

4 孟夢;邵春福;曾靜靖;張杰;;組合出行模式下多方式交通流分配模型及算法[J];吉林大學學報(工學版);2014年01期

5 張水艦;劉學軍;楊洋;;動態(tài)隨機最短路徑算法研究[J];物理學報;2012年16期

6 陳京榮;俞建寧;李引珍;;多屬性隨機時間依賴網絡路徑優(yōu)化[J];西南交通大學學報;2012年02期

7 蔡鑒明;李夏苗;楊光華;;基于時變性和可靠性的地震災害應急物流運輸路徑選擇[J];鐵道科學與工程學報;2011年05期

8 王珊;王會舉;覃雄派;周p，

本文編號：1682075