本文選題：交通流 + 跟馳模型��； 參考：《重慶大學(xué)》2014年博士論文

【摘要】：隨著道路交通流量的不斷增加，車輛之間的作用關(guān)系越來越明顯，刻畫車輛作用關(guān)系的內(nèi)在機(jī)理，揭示其演變規(guī)律是提高車流平穩(wěn)性的重要手段。ITS(IntelligentTransport System)系統(tǒng)的廣泛深入應(yīng)用，使得車輛可快速獲取與反饋運(yùn)行信息，并根據(jù)這些信息合理控制自身狀態(tài)，以達(dá)到前后多車的協(xié)同行駛，從而形成一個(gè)有序流動(dòng)的車輛行駛隊(duì)列。然而，傳統(tǒng)的交通流模型未考慮前后多車信息，已難以刻畫車輛相互作用下的車流演變規(guī)律。因此，系統(tǒng)地刻畫ITS環(huán)境下車流演變規(guī)律，進(jìn)而研究提高車流穩(wěn)定性的控制方法已成為亟待攻克的核心關(guān)鍵任務(wù)。 為此，本文以現(xiàn)有交通流微觀模型為基礎(chǔ)，考慮前后多車信息，建立車輛相互作用下的跟馳模型，以揭示ITS環(huán)境下車流演變規(guī)律；在此基礎(chǔ)上，為使模型能適應(yīng)交通系統(tǒng)非線性變化的特點(diǎn)，對模型進(jìn)行時(shí)變參數(shù)標(biāo)定；進(jìn)而研究保證車流平穩(wěn)運(yùn)行的控制策略。論文的主要工作如下： ①考慮鄰近雙前車最優(yōu)速度差及其后視效應(yīng)的綜合作用，構(gòu)建基于前后車信息的CI-CF跟馳模型，揭示考慮前后多車信息的車流演變規(guī)律。 基于FVD(full velocity difference)模型、BLVD(backward looking and velocitydifference)模型，，利用在ITS環(huán)境下獲得的前后車信息，提出一個(gè)考慮鄰近雙前車最優(yōu)速度差和后視效應(yīng)CI-CF(a new comprehensive information car-following)模型。通過線性穩(wěn)定性分析，得到模型的穩(wěn)定性判據(jù)；采用非線性分析方法，推導(dǎo)出mKdV方程，用于描述系統(tǒng)在臨界穩(wěn)定點(diǎn)附近的交通流特性。在周期邊界條件下，運(yùn)用數(shù)值仿真驗(yàn)證車輛啟動(dòng)過程、停止過程、演化過程的理論研究結(jié)果正確性。仿真結(jié)果表明，與FVD模型、BLVD模型相比，綜合考慮鄰近雙前車的最優(yōu)速度差和后視效應(yīng)，可使車流擁有更好的協(xié)同行駛特性，最大程度使得車流運(yùn)行行為趨于一致，真實(shí)刻畫了車流演變規(guī)律。 ②針對跟馳模型時(shí)變參數(shù)標(biāo)定問題，提出一種自校正的參數(shù)標(biāo)定方法，使CI-CF模型更能適應(yīng)交通時(shí)變特性。 為使CI-CF模型能更加準(zhǔn)確地刻畫各類交通非線性現(xiàn)象，必須應(yīng)用實(shí)測交通數(shù)據(jù)對模型進(jìn)行參數(shù)標(biāo)定。首先給出基于最小二乘法的模型參數(shù)標(biāo)定方法；考慮到交通系統(tǒng)時(shí)變特性，然后提出一種自校正的跟馳模型參數(shù)標(biāo)定方法，以解決跟馳模型時(shí)變參數(shù)的標(biāo)定問題。實(shí)驗(yàn)結(jié)果表明，提出的自校正參數(shù)標(biāo)定方法因可以根據(jù)交通環(huán)境的變化來實(shí)時(shí)動(dòng)態(tài)標(biāo)定參數(shù)，與傳統(tǒng)成批處理的最小二乘參數(shù)標(biāo)定法得出一個(gè)恒定的參數(shù)標(biāo)定結(jié)果相比，更能準(zhǔn)確刻畫車流演變規(guī)律。利用提出的參數(shù)標(biāo)定方法對FVD模型、BLVD模型進(jìn)行參數(shù)標(biāo)定，實(shí)驗(yàn)結(jié)果進(jìn)一步證明CI-CF模型能更準(zhǔn)確刻畫車流演變規(guī)律。 ③針對車流平穩(wěn)性控制問題，考慮多前車穩(wěn)態(tài)期望速度效應(yīng)，基于CI-CF模型，提出保證車流平穩(wěn)運(yùn)行的控制策略，形成MSDVE模型。 在Konishi等人的基礎(chǔ)上，充分考慮前方多輛車的信息，以駕駛員期望的穩(wěn)定速度前進(jìn)為目標(biāo)，基于CI-CF模型，設(shè)計(jì)一個(gè)車流平穩(wěn)運(yùn)行的控制策略，形成MSDVE(multiple steady desired velocity effect)模型。運(yùn)用反饋控制理論，得到車流保持穩(wěn)定的條件。仿真結(jié)果表明，在同等條件下，提出的模型所得到的車流平穩(wěn)性運(yùn)行狀況優(yōu)于無控制情況，也優(yōu)于KKH(Konishi K.,et al)模型、ZG(Zhao and Gao)模型的結(jié)果。與ITS(Han X L)模型相比，由于考慮了穩(wěn)定期望速度效應(yīng)，可使交通系統(tǒng)的穩(wěn)定性增強(qiáng)，車流運(yùn)行更加平穩(wěn)。 ④在上述平穩(wěn)性控制策略基礎(chǔ)上，進(jìn)一步考慮后視效應(yīng)的作用，提出基于前后車綜合信息的穩(wěn)態(tài)期望速度控制策略，形成SDVEPF模型。 在考慮多前車穩(wěn)態(tài)期望速度效應(yīng)的穩(wěn)定性控制策略基礎(chǔ)上，進(jìn)一步考慮后視效應(yīng)的影響，提出考慮前后車綜合信息的車流平穩(wěn)性控制策略，形成SDVEPF(steady desired Velocity effect of Preceding and Following Cars)模型。同樣運(yùn)用反饋控制理論，得到車流保持穩(wěn)定的條件。仿真結(jié)果表明，考慮前后車穩(wěn)態(tài)期望速度綜合效應(yīng)作用，車流運(yùn)行狀態(tài)更加平穩(wěn)，車輛速度平滑度和幅度更小，因此，考慮前后車穩(wěn)態(tài)期望速度綜合效應(yīng)的SDVEPF模型，比僅考慮多前車穩(wěn)態(tài)期望速度效應(yīng)的MSDVE模型更利于控制車流平穩(wěn)運(yùn)行。 綜上所述，本文立足于交通系統(tǒng)智能化，提出了更符合交通實(shí)際和具有一定前瞻性的跟馳模型，研究了模型線性與非線性特性、時(shí)變參數(shù)標(biāo)定以及車流平穩(wěn)性控制問題，理論分析和仿真實(shí)驗(yàn)均驗(yàn)證了上述工作的有效性。研究成果為ITS環(huán)境中車流運(yùn)行狀況的刻畫與分析，提供了相關(guān)理論基礎(chǔ)和方法。
[Abstract]:With the increasing traffic flow , the relationship between vehicle and vehicle becomes more and more obvious , the internal mechanism of vehicle interaction is more and more obvious , and its evolution law is revealed as an important means to improve the stability of traffic flow .

In this paper , based on the existing microscopic model of traffic flow , the following vehicle information is taken into consideration , and the following model is established under the interaction of vehicle to reveal the evolution law of traffic flow in ITS environment ;
On this basis , in order to adapt the model to the nonlinear change of the traffic system , the time - varying parameter calibration is carried out on the model ;
Furthermore , the control strategy to ensure the smooth running of traffic flow is studied . The main work of this paper is as follows :

In this paper , the CI - CF following model based on the front and rear vehicle information is constructed in consideration of the comprehensive effects of the optimal speed difference and the rear - view effect of the two - front vehicle .

Based on the FVD ( full velocity difference ) model , BLVD ( backward looking and velocitydifference ) model , a new comprehensive information car - following model is proposed considering the optimal speed difference and the rear - view effect CI - CF ( a new comprehensive information car - following ) model in ITS environment .
The nonlinear analysis method is used to derive the mDk equation , which is used to describe the traffic flow characteristics of the system in the vicinity of critical stable point . The simulation results show that the optimal speed difference and the rear - view effect of the vehicle start - up process , the stopping process and the evolution process are verified by using the numerical simulation under the periodic boundary condition . The simulation results show that the optimal speed difference and the rear - view effect of the adjacent double - front vehicle are comprehensively considered in comparison with the FVD model and the BLVD model , so that the running behavior of the traffic flow tends to be consistent , and the evolvement rule of the traffic flow is vividly portrayed .

( 2 ) Aiming at the problem of time - varying parameter calibration of the following model , a self - correcting parameter calibration method is proposed , so that the CI - CF model can adapt to the time - varying characteristics of traffic .

In order to make CI - CF model more accurately depict various traffic nonlinear phenomena , it is necessary to use the measured traffic data to calibrate the model . First , the calibration method of model parameters based on least square method is given .
Considering the time - varying characteristics of traffic system , a self - correcting parameter calibration method is proposed to solve the problem of calibration of the time - varying parameters of the following model . The experimental results show that the proposed self - tuning parameter calibration method can accurately depict the evolvement rule of traffic flow according to the change of traffic environment . The parameter calibration method is used to calibrate the FVD model and BLVD model . The experimental results show that the CI - CF model can more accurately depict the evolution law of traffic flow .

( 3 ) Based on CI - CF model , based on CI - CF model , this paper puts forward a control strategy to ensure the smooth running of traffic flow based on CI - CF model . The MSDVE model is formed .

On the basis of Konishi and so on , taking fully into consideration the information of the front multi - car , taking the steady speed expected by the driver as the target , based on the CI - CF model , we design a control strategy for the steady operation of the vehicle flow . The simulation results show that under the same condition , the traffic stability is better than that of the model of KKH ( Konishi K . , et al ) and ZG ( Zhao and Gao ) . The simulation results show that the stability of the traffic system can be enhanced and the traffic flow is more stable than the ITS ( Han X L ) model .

On the basis of the above - mentioned stationarity control strategy , the effect of the back - view effect is further considered , and a steady - state expected speed control strategy based on the comprehensive information of the front and rear vehicles is proposed , and an SDVEPF model is formed .

On the basis of the stability control strategy considering the steady - state expected speed effect of the multi - front vehicle , the influence of the rear - view effect is further considered , and the steady desired velocity effect of the vehicle flow is obtained . The simulation results show that the SDVEPF model considering the comprehensive effect of the steady - state expected speed of the front - rear vehicle is more stable and the vehicle speed is smooth and the amplitude is smaller . Therefore , the model of the SDVEPF considering the comprehensive effect of the steady - state expected speed of the front and rear vehicles is considered , which is more beneficial to control the smooth operation of the traffic flow than the MSDVE model considering the steady - state expected speed effect of the front and rear vehicles .

In conclusion , based on the intelligence of traffic system , this paper puts forward a model which is more consistent with traffic reality and a certain forward - looking model . The linear and nonlinear characteristics of the model , the calibration of time - varying parameters and the stability control of traffic flow are studied , and the theoretical analysis and simulation experiments verify the validity of the above work . The research results provide the theoretical basis and method for the characterization and analysis of traffic flow health in ITS environment .
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：U491.1;U495;TP13

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 ;A Two-Lane Cellular Automata Model with Influence of Next-Nearest Neighbor Vehicle[J];Communications in Theoretical Physics;2006年04期

2 劉巖;王殿海;韓萍;;模擬彈簧車輛跟馳模型參數(shù)的標(biāo)定[J];大連交通大學(xué)學(xué)報(bào);2011年01期

3 莫業(yè)柳;薛郁;時(shí)偉;唐鐵橋;;考慮前方多車輛速度差的優(yōu)化速度模型[J];廣西師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2008年02期

4 周立軍;王殿海;李衛(wèi)青;;人工神經(jīng)網(wǎng)絡(luò)及粒子群優(yōu)化算法在跟馳模型中的應(yīng)用[J];吉林大學(xué)學(xué)報(bào)(工學(xué)版);2009年04期

5 孫舵;汪秉宏;;紅綠燈周期對二維交通流的影響及平均場理論[J];吉林大學(xué)學(xué)報(bào)(工學(xué)版);2009年S2期

6 王殿海;陶鵬飛;金盛;馬東方;;跟馳模型參數(shù)標(biāo)定及驗(yàn)證方法[J];吉林大學(xué)學(xué)報(bào)(工學(xué)版);2011年S1期

7 喬晉;雋志才;高林杰;;CORSIM微觀仿真軟件建模參數(shù)標(biāo)定研究[J];佳木斯大學(xué)學(xué)報(bào)(自然科學(xué)版);2007年05期

8 張鵬,劉儒勛;交通流問題的有限元分析和模擬(Ⅰ)[J];計(jì)算物理;2001年04期

9 孫棣華;張建廠;廖孝勇;田川;李永福;劉衛(wèi)寧;;非鄰近車輛最優(yōu)速度差模型[J];交通運(yùn)輸工程學(xué)報(bào);2011年06期

10 馬國勝;馬萬經(jīng);;兩相位交叉口左轉(zhuǎn)交通流沖突延誤改進(jìn)模型[J];哈爾濱工業(yè)大學(xué)學(xué)報(bào);2012年10期

相關(guān)博士學(xué)位論文 前3條

1 李興莉;交通流的隨機(jī)因素分析和相變研究[D];上海大學(xué);2008年

2 彭光含;交通流復(fù)雜耦合動(dòng)態(tài)特性模擬研究[D];重慶大學(xué);2009年

3 朱明皓;城市交通擁堵的社會經(jīng)濟(jì)影響分析[D];北京交通大學(xué);2013年

本文編號：1955251