【摘要】：行程時(shí)間采集和評估是先進(jìn)交通信息系統(tǒng)分析交通運(yùn)行狀況的依據(jù)和基礎(chǔ),交通出行者及交通管理者經(jīng)常采用其進(jìn)行評價(jià)交通狀態(tài)或者作為下一步交通決策的依據(jù)。手機(jī)切換定位的交通信息采集技術(shù)具有投資成本低、數(shù)據(jù)量龐大,信息覆蓋范圍廣等諸多優(yōu)點(diǎn),逐漸成為了當(dāng)前智能交通信息采集的重要手段,在利用手機(jī)切換技術(shù)獲取行程時(shí)間過程中,兩個(gè)連續(xù)采樣點(diǎn)之間車輛可能跨越多個(gè)部分路段或完整路段,但是行程時(shí)間信息發(fā)布一般以完整路段為基本單位,因此需要將跨越不同路段的樣本車輛采樣間隔時(shí)間分配至每條路段上。對于快速路而言,其運(yùn)行狀態(tài)簡單,采用基本路段比例法即可完成行程時(shí)間分配,且分配誤差��；但是對于城市干道而言,由于信號控制交叉口的存在等問題導(dǎo)致行程時(shí)間分配難以處理,需要考慮信號交叉口引起的停車等待時(shí)間及加減速延誤,信號控制設(shè)施類型及信號配時(shí)方案對停車延誤時(shí)長起著決定性作用,但是現(xiàn)有城市干道行程時(shí)間分配方法多數(shù)沒有假設(shè)信號控制設(shè)施類型及信號配時(shí)方案為已知條件,少數(shù)考慮了信號控制設(shè)施相關(guān)信息的方法,其模型輸入?yún)?shù)多且復(fù)雜、可移植性弱。因此本文在假設(shè)信號控制相關(guān)信息為已知條件下,提出修正Hellinga模型及信號時(shí)間序列模型對交叉口延誤精確分配,通過仿真平臺獲取手機(jī)切換定位數(shù)據(jù)將這兩種方法與Hellinga模型(Hellinga教授2008年提出的分配理論模型)及神經(jīng)網(wǎng)絡(luò)進(jìn)行對比分析,最終得出結(jié)論：在暢通狀態(tài)下,修正Hellinga模型及信號時(shí)間序列模型這種精細(xì)化的結(jié)合交叉口信號信息的方法優(yōu)于神經(jīng)網(wǎng)絡(luò)及Hellinga模型,在擁堵狀態(tài)下,修正Hellinga模型分配效果依然最優(yōu)。
[Abstract]:The acquisition and evaluation of travel time is the basis and basis for the advanced traffic information system to analyze the traffic operation status. Traffic travelers and traffic managers often use it to evaluate the traffic status or to take it as the basis for the next step of traffic decision-making. With the advantages of low investment cost, large amount of data, wide coverage of information and so on, the technology of mobile phone switching and positioning has gradually become an important means of intelligent transportation information collection. In the process of obtaining travel time by using mobile phone switching technology, vehicles between two continuous sampling points may span several parts of a section or a whole section of a road, but the information of travel time is generally issued on a complete section as the basic unit. Therefore, sample vehicle sampling intervals across different sections need to be allocated to each section. For the expressway, its running state is simple, the travel time distribution can be completed by using the basic road section proportion method, and the distribution error is small, but for the urban trunk road, Due to the existence of signal-controlled intersection and other problems, it is difficult to deal with the travel time distribution, so it is necessary to consider the waiting time and acceleration and deceleration delay caused by signalized intersection. The type of signal control facilities and the signal timing scheme play a decisive role in the delay time, but most of the existing methods do not assume that the type of signal control facilities and the signal timing scheme are known conditions. A few methods which consider the information of signal control facilities have many input parameters, complex input parameters and weak portability. Therefore, under the assumption that the signal control information is known, the modified Hellinga model and the signal time series model are proposed to assign the intersection delay accurately. The two methods are compared with Hellinga model (assignment theory model proposed by Professor Hellinga in 2008) and neural network through the acquisition of mobile phone handoff location data by simulation platform. The modified Hellinga model and the signal time series model are better than the neural network and Hellinga model in combining the intersection signal information. In the congested condition, the modified Hellinga model still has the best allocation effect.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U491.1

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