城市快速路實(shí)時(shí)交通狀態(tài)估計(jì)方法研究
發(fā)布時(shí)間：2018-07-13 10:33
【摘要】：城市快速路的實(shí)時(shí)交通狀態(tài)估計(jì)是實(shí)施有效交通控制和誘導(dǎo)的前提與基礎(chǔ)。智能交通系統(tǒng)的發(fā)展，尤其是AVI（Advanced Vehicle Information）信息技術(shù)的進(jìn)步，，使得城市道路交通信息獲取更加準(zhǔn)確全面�；谝苿�(dòng)傳感技術(shù)（如浮動(dòng)檢測(cè)車、智能手機(jī)），實(shí)時(shí)估計(jì)道路交通狀況就是其中一個(gè)很有意義的研究方向。與傳統(tǒng)固定式交通檢測(cè)技術(shù)相比，移動(dòng)式、便攜式交通檢測(cè)方法在大范圍城市道路信息獲取的實(shí)時(shí)性、準(zhǔn)確性、覆蓋面更廣等方面都具有明顯優(yōu)勢(shì)。 本文研究了基于便攜式速度檢測(cè)器網(wǎng)絡(luò)的城市快速路實(shí)時(shí)道路交通狀態(tài)估計(jì)問題。利用路網(wǎng)車輛速度信息估計(jì)城市快速路的交通密度、流量等交通參數(shù)。單個(gè)簡單的車輛速度檢測(cè)裝置，如交警使用的便攜式測(cè)速槍，通過結(jié)合移動(dòng)通訊技術(shù)，構(gòu)成了用于大范圍路網(wǎng)平均速度檢測(cè)的無線傳感器網(wǎng)絡(luò)。與既往交通狀態(tài)估計(jì)研究相比較，檢測(cè)方法的兩個(gè)特色在于：第一、可以采集到城市快速路任意時(shí)空位置、同一時(shí)刻不同路段上的車輛平均速度信息用于交通估計(jì)，檢測(cè)器網(wǎng)絡(luò)具有自組織特征，同時(shí)對(duì)路網(wǎng)交通的正常運(yùn)行不造成干擾。第二、城市快速路交通流處于自由、擁堵等不同交通模式時(shí)，系統(tǒng)的可觀測(cè)性各不相同。這樣就會(huì)造成原本有效的交通檢測(cè)信息，當(dāng)?shù)缆方煌Ｊ桨l(fā)生改變后，對(duì)當(dāng)前系統(tǒng)狀態(tài)的估計(jì)不再起作用。為了有效應(yīng)對(duì)交通大數(shù)據(jù)，發(fā)揮移動(dòng)式交通檢測(cè)技術(shù)的優(yōu)勢(shì)，采集關(guān)鍵時(shí)空位置處的交通流信息用于狀態(tài)估計(jì)，也是文本探討的一個(gè)問題。 事實(shí)上，城市快速路交通流作為一類時(shí)空分布式參數(shù)系統(tǒng)，系統(tǒng)演化趨勢(shì)由當(dāng)前道路交通狀態(tài)與路網(wǎng)邊界（上下游、出入口匝道）交通流量共同確定。為了能夠?qū)崿F(xiàn)交通狀態(tài)與邊界流量的同步估計(jì)，本文在交通狀態(tài)估計(jì)方法上主要進(jìn)行了三方面問題的研究： 首先，為了探究城市快速路交通流在不同交通模式下的可觀測(cè)性，基于路段間的流量傳輸關(guān)系建立了一種狀態(tài)切換的交通多模態(tài)切換模型，并且對(duì)模型的可觀性進(jìn)行了分析。通過對(duì)模型的可觀測(cè)行分析發(fā)現(xiàn)，當(dāng)城市快速路交通流在不同交通狀態(tài)切換時(shí)，交通檢測(cè)信息的有效性也隨之改變。根據(jù)交通檢測(cè)信息的有效性，可以合理布設(shè)交通檢測(cè)器資源，同時(shí)降低檢測(cè)器數(shù)據(jù)傳輸時(shí)間，有效應(yīng)對(duì)交通大數(shù)據(jù)問題。 其次，傳統(tǒng)估計(jì)方法主要集中于對(duì)主線路段的研究，而且是在邊界條件已知的情況下進(jìn)行的。這樣，交通估計(jì)問題就受限于檢測(cè)器的時(shí)空位置。針對(duì)以上問題，在本文中提出了一種以城市快速路為研究對(duì)象的交通流模型，該模型中不僅含有狀態(tài)變量（密度），還含有未知輸入（邊界流量）。為了實(shí)現(xiàn)交通狀態(tài)和邊界流量的同步估計(jì)，本文設(shè)計(jì)了一種循環(huán)遞歸濾波器，該濾波器在對(duì)交通狀態(tài)進(jìn)行估計(jì)的同時(shí)，還可以同步對(duì)交通流量進(jìn)行估計(jì)。同時(shí)，由于系統(tǒng)方程不在受邊界流量的限制，選取速度作為觀測(cè)變量，通過便攜式速度檢測(cè)設(shè)備，結(jié)合移動(dòng)通訊技術(shù)，構(gòu)造交通路網(wǎng)速度檢測(cè)的無線傳感器網(wǎng)絡(luò)。根據(jù)路網(wǎng)速度檢測(cè)信息，對(duì)交通狀態(tài)進(jìn)行估計(jì)，使交通狀態(tài)估計(jì)不在受檢測(cè)器位置的約束，交通模型和濾波方法具有更高的適用性。 最后，研究了大尺度的快速路網(wǎng)交通估計(jì)問題。大尺度交通路網(wǎng)的模型階次高，算法復(fù)雜，且運(yùn)行時(shí)間那以滿足交通控制對(duì)實(shí)時(shí)性的要求。在本文提出的交通狀態(tài)和邊界流量同步估計(jì)的基礎(chǔ)上，將大尺度的交通路網(wǎng)分割成若干個(gè)子路段，然后對(duì)每個(gè)子路段交通狀態(tài)和邊界流量進(jìn)行估計(jì)，結(jié)合信息融合技術(shù)，對(duì)相鄰兩個(gè)子路段的邊界流量（或重合的元胞密度）進(jìn)行融合，從而得到交通路網(wǎng)的交通狀態(tài)。這種分布式的交通狀態(tài)估計(jì)方法，大大降低了模型階次，提高了估計(jì)算法效率。
[Abstract]:The real-time traffic state estimation of urban expressway is the prerequisite and basis for implementing effective traffic control and induction. The development of intelligent transportation system, especially the progress of AVI (Advanced Vehicle Information) information technology, makes urban road traffic information get more accurate and comprehensive. Based on mobile sensing technology (such as floating detection car, smart hand) The real-time estimation of road traffic conditions is a very meaningful research direction. Compared with the traditional fixed traffic detection technology, mobile and portable traffic detection methods have obvious advantages in the real-time, accuracy and wide coverage of large urban road information acquisition.
In this paper, the real time road traffic state estimation problem of Urban Expressway Based on the portable speed detector network is studied. The traffic density and traffic parameters of urban expressway are estimated using the speed information of road network. A single simple vehicle speed detection device, such as the portable speed gun used by traffic police, is combined with the mobile communication technology. In comparison with previous traffic state estimation studies, the two features of the detection method are: first, the location of the urban expressway can be collected at any time and space, and the vehicle average speed information on the different sections of the same time is used for traffic estimation, and the detector network is used. The collaterals have self organization characteristics and do not interfere with the normal operation of road network traffic. Second, when the traffic flow in the urban expressway is in the free, congestion and other different traffic modes, the observability of the system is different. This will result in the original effective traffic detection information. After the road traffic pattern changes, the current system state will be changed. In order to effectively cope with large traffic data and give full play to the advantages of mobile traffic detection technology, it is also a problem for text discussion to collect traffic flow information at the key space and time position for state estimation.
In fact, urban expressway traffic flow is a kind of space-time distributed parameter system. The evolution trend of the system is determined by the traffic flow of the current road traffic state and the road network boundary (upper and lower reaches, the exit ramp). In order to realize the synchronous estimation of the traffic state and the boundary flow, this paper is mainly carried out in the traffic state estimation method. Three aspects of the study:
First, in order to explore the observability of urban expressway traffic flow under different traffic modes, a traffic multimodal switching model with state switching is established based on the flow transmission relationship between sections, and the observability of the model is analyzed. The traffic flow in urban expressway is found to be different by the observable line analysis of the model. The effectiveness of traffic detection information is also changed when the traffic state is switched. According to the effectiveness of traffic detection information, the traffic detector resources can be set up reasonably, and the data transmission time of the detector can be reduced, and the problem of traffic data can be effectively dealt with.
Secondly, the traditional estimation method is mainly focused on the study of the main line section, and is carried out in the case of known boundary conditions. In this way, the traffic estimation problem is limited to the space-time position of the detector. In this paper, a traffic flow model based on the urban expressway is proposed in this paper, which contains not only the model of the traffic flow, but also the traffic flow model in this paper. There is a state variable (density) and an unknown input (boundary flow). In order to realize the synchronous estimation of traffic state and boundary flow, a cyclic recursive filter is designed in this paper. The filter can estimate the traffic flow synchronously while the traffic state is estimated. Meanwhile, the system equation is not subject to the boundary flow. According to the speed detection information of the road network, the traffic state is estimated, and the traffic state estimation is not constrained by the detector position, the traffic model and the filtering method are made, and the traffic state estimation is not constrained by the detector position. There is a higher applicability.
Finally, the large scale road network traffic estimation problem is studied. The large scale traffic network model order is high, the algorithm is complex, and the operation time is to meet the real-time requirements of traffic control. On the basis of the proposed traffic state and boundary flow synchronization estimation, the large scale traffic network is divided into several sub sections. Then, the traffic state and boundary flow of each sub section are estimated, combined with the information fusion technology, the boundary flow (or the coincidence cell density) of the adjacent two sub sections is fused, thus the traffic state of the traffic network is obtained. This distributed traffic state estimation method greatly reduces the order of the model and improves the estimation algorithm. Efficiency.
【學(xué)位授予單位】：北京工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U491
本文編號(hào)：2119057
[Abstract]:The real-time traffic state estimation of urban expressway is the prerequisite and basis for implementing effective traffic control and induction. The development of intelligent transportation system, especially the progress of AVI (Advanced Vehicle Information) information technology, makes urban road traffic information get more accurate and comprehensive. Based on mobile sensing technology (such as floating detection car, smart hand) The real-time estimation of road traffic conditions is a very meaningful research direction. Compared with the traditional fixed traffic detection technology, mobile and portable traffic detection methods have obvious advantages in the real-time, accuracy and wide coverage of large urban road information acquisition.
In this paper, the real time road traffic state estimation problem of Urban Expressway Based on the portable speed detector network is studied. The traffic density and traffic parameters of urban expressway are estimated using the speed information of road network. A single simple vehicle speed detection device, such as the portable speed gun used by traffic police, is combined with the mobile communication technology. In comparison with previous traffic state estimation studies, the two features of the detection method are: first, the location of the urban expressway can be collected at any time and space, and the vehicle average speed information on the different sections of the same time is used for traffic estimation, and the detector network is used. The collaterals have self organization characteristics and do not interfere with the normal operation of road network traffic. Second, when the traffic flow in the urban expressway is in the free, congestion and other different traffic modes, the observability of the system is different. This will result in the original effective traffic detection information. After the road traffic pattern changes, the current system state will be changed. In order to effectively cope with large traffic data and give full play to the advantages of mobile traffic detection technology, it is also a problem for text discussion to collect traffic flow information at the key space and time position for state estimation.
In fact, urban expressway traffic flow is a kind of space-time distributed parameter system. The evolution trend of the system is determined by the traffic flow of the current road traffic state and the road network boundary (upper and lower reaches, the exit ramp). In order to realize the synchronous estimation of the traffic state and the boundary flow, this paper is mainly carried out in the traffic state estimation method. Three aspects of the study:
First, in order to explore the observability of urban expressway traffic flow under different traffic modes, a traffic multimodal switching model with state switching is established based on the flow transmission relationship between sections, and the observability of the model is analyzed. The traffic flow in urban expressway is found to be different by the observable line analysis of the model. The effectiveness of traffic detection information is also changed when the traffic state is switched. According to the effectiveness of traffic detection information, the traffic detector resources can be set up reasonably, and the data transmission time of the detector can be reduced, and the problem of traffic data can be effectively dealt with.
Secondly, the traditional estimation method is mainly focused on the study of the main line section, and is carried out in the case of known boundary conditions. In this way, the traffic estimation problem is limited to the space-time position of the detector. In this paper, a traffic flow model based on the urban expressway is proposed in this paper, which contains not only the model of the traffic flow, but also the traffic flow model in this paper. There is a state variable (density) and an unknown input (boundary flow). In order to realize the synchronous estimation of traffic state and boundary flow, a cyclic recursive filter is designed in this paper. The filter can estimate the traffic flow synchronously while the traffic state is estimated. Meanwhile, the system equation is not subject to the boundary flow. According to the speed detection information of the road network, the traffic state is estimated, and the traffic state estimation is not constrained by the detector position, the traffic model and the filtering method are made, and the traffic state estimation is not constrained by the detector position. There is a higher applicability.
Finally, the large scale road network traffic estimation problem is studied. The large scale traffic network model order is high, the algorithm is complex, and the operation time is to meet the real-time requirements of traffic control. On the basis of the proposed traffic state and boundary flow synchronization estimation, the large scale traffic network is divided into several sub sections. Then, the traffic state and boundary flow of each sub section are estimated, combined with the information fusion technology, the boundary flow (or the coincidence cell density) of the adjacent two sub sections is fused, thus the traffic state of the traffic network is obtained. This distributed traffic state estimation method greatly reduces the order of the model and improves the estimation algorithm. Efficiency.
【學(xué)位授予單位】：北京工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U491
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