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A real-time performance measurement system for arterial traffic signals.

機(jī)譯：實(shí)時(shí)交通流量測(cè)量系統(tǒng)。

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摘要

Performance monitoring for arterial traffic control and management system is an area of emerging focus in the United States. To properly study traffic flow at signalized intersections, both arrival/departure traffic flow data and associated signal status data are required. Although many existing signal control systems are capable of generating data to support performance assessment, most do not make it "easy" for the managing agencies to prioritize improvements and plan for future needs. Indeed, the 2005 Traffic Signal Operation Self Assessment Survey indicated that the majority of agencies involved in the operation and maintenance of traffic signal systems do not monitor or archive traffic system performance data in an effort to improve their operation. Therefore, despite studies having shown that the benefits of investments in improved signal timing outweigh the costs by 40:1 or more, signal retiming is often not repeated frequently enough to account for rapidly changing traffic patterns, largely due to the expense of manual data collection and performance measurements.;The need to address the above problems inspired this research. The goal is to develop a real-time arterial performance measurement system, which can automatically collect and archive high-resolution traffic signal data, and build a rich list of performance measures. The objectives of this doctoral research are two-fold: (1) to develop a system for high-resolution traffic signal data collection, archival, and preprocessing; and (2) to develop a set of methodologies that can measure traffic signal performance, including queue length, delay and level of service (LOS) for individual intersections and travel time and number of stops for an arterial corridor. In this research, a system for high resolution traffic signal data collection is successfully built. The system, named as SMART-SIGNAL (Systematic Monitoring of Arterial Road Traffic and Signals), is an arterial data collection and performance measurement system, which simultaneously collects "event-based" high-resolution traffic data from multiple intersections and generates arterial performance measures in real time. In the SMART-SIGNAL system, a complete history of traffic signal control, including all signal events such as vehicle actuations on detectors and signal phase changes, is archived and stored.;Using the collected "event" data, mathematical models are built to calculate intersection and arterial performance measures. A time-dependent queue length estimation model is proposed that can handle long queues under both under-saturated and over-saturated conditions. The model examines the changes in signal detector's occupancy profile within a cycle, and derives queue length by identifying traffic flow pattern changes during the queue discharging process. A turning movement proportion estimation model is also offered in this thesis. Detector counts from surrounding intersections are used to calculate right turning traffic for the subject intersection.;An innovative algorithm is proposed in this research for arterial performance measurement by tracing virtual probe vehicles from origin to destination. One of three maneuvers: acceleration, deceleration or no-speed-change, is selected based on the current traffic states of the virtual probe. The step-by-step maneuver calculation stops until the virtual probe "arrives" at the destination, and various arterial performance measures, including travel time, can thus be estimated. An interesting property of the proposed model is that travel time estimation errors can be self-corrected with the signal status data, because the differences between a virtual probe vehicle and a real probe can be reduced when both of them meet the red signal phase. The virtual probe mimics regular travel behaviors of arterial drivers and thus can be treated as a representative vehicle traversing the arterial.;The SMART-SIGNAL data collection system has been installed on an 11-intersections arterial corridor along France Avenue in Hennepin County, Minnesota since February 2007. Event-based signal data are being collected in a 24/7 mode and then immediately archived in the SMART-SIGNAL system, thus yielding a tremendous amount of field data available for research. The field study shows that the proposed mathematical models can generate accurate time-dependent queue lengths, travel times, numbers of stops, and other performance measures under various traffic conditions.
機(jī)譯：在美國(guó)，動(dòng)脈交通控制和管理系統(tǒng)的性能監(jiān)視是一個(gè)新興的領(lǐng)域。為了正確研究信號(hào)交叉口的交通流量，既需要到達(dá)/出發(fā)交通流量數(shù)據(jù)，也需要相關(guān)的信號(hào)狀態(tài)數(shù)據(jù)。盡管許多現(xiàn)有的信號(hào)控制系統(tǒng)都能夠生成數(shù)據(jù)來(lái)支持性能評(píng)估，但是大多數(shù)管理機(jī)構(gòu)并沒有“輕松”地將改進(jìn)的優(yōu)先級(jí)和為未來(lái)的需求進(jìn)行計(jì)劃。實(shí)際上，2005年交通信號(hào)燈運(yùn)行自我評(píng)估調(diào)查表明，參與交通信號(hào)燈系統(tǒng)運(yùn)行和維護(hù)的大多數(shù)機(jī)構(gòu)都沒有監(jiān)視或歸檔交通系統(tǒng)性能數(shù)據(jù)，以改善其運(yùn)行狀況。因此，盡管研究表明投資改善信號(hào)定時(shí)的好處超過成本40：1或更多，但信號(hào)重定時(shí)通常沒有足夠頻繁地重復(fù)以說明快速變化的流量模式，這主要是由于手動(dòng)數(shù)據(jù)收集的費(fèi)用解決上述問題的需要啟發(fā)了這項(xiàng)研究。目標(biāo)是開發(fā)一個(gè)實(shí)時(shí)動(dòng)脈性能測(cè)量系統(tǒng)，該系統(tǒng)可以自動(dòng)收集和存檔高分辨率交通信號(hào)數(shù)據(jù)，并建立豐富的性能測(cè)量列表。這項(xiàng)博士研究的目標(biāo)有兩個(gè)：（1）開發(fā)用于高分辨率交通信號(hào)數(shù)據(jù)收集，存檔和預(yù)處理的系統(tǒng)； （2）開發(fā)一套可測(cè)量交通信號(hào)性能的方法，包括隊(duì)列長(zhǎng)度，單個(gè)交叉路口的延誤和服務(wù)水平（LOS）以及動(dòng)脈走廊的行進(jìn)時(shí)間和停靠點(diǎn)數(shù)量。在這項(xiàng)研究中，成功??建立了高分辨率交通信號(hào)數(shù)據(jù)收集系統(tǒng)。該系統(tǒng)名為SMART-SIGNAL（動(dòng)脈道路交通和信號(hào)的系統(tǒng)監(jiān)視），是一種動(dòng)脈數(shù)據(jù)收集和性能測(cè)量系統(tǒng)，可同時(shí)從多個(gè)路口收集“基于事件”的高分辨率交通數(shù)據(jù)，并生成動(dòng)脈性能度量實(shí)時(shí)。在SMART-SIGNAL系統(tǒng)中，交通信號(hào)燈控制的完整歷史記錄，包括所有信號(hào)事件，例如檢測(cè)器上的車輛致動(dòng)和信號(hào)相位變化，都將被存儲(chǔ)。；使用收集的“事件”數(shù)據(jù)，建立數(shù)學(xué)模型來(lái)計(jì)算交叉和動(dòng)脈性能指標(biāo)。提出了一種與時(shí)間有關(guān)的隊(duì)列長(zhǎng)度估計(jì)模型，該模型可以在飽和不足和過度飽和條件下處理長(zhǎng)隊(duì)列。該模型檢查一個(gè)周期內(nèi)信號(hào)檢測(cè)器占用情況的變化，并通過識(shí)別隊(duì)列釋放過程中的業(yè)務(wù)流模式變化來(lái)得出隊(duì)列長(zhǎng)度。本文還提供了轉(zhuǎn)彎運(yùn)動(dòng)比例估計(jì)模型。使用來(lái)自周圍交叉路口的檢測(cè)器計(jì)數(shù)來(lái)計(jì)算主題交叉路口的右轉(zhuǎn)交通量。；本研究中提出了一種創(chuàng)新的算法，通過跟蹤虛擬探測(cè)車從始發(fā)地到目的地來(lái)進(jìn)行動(dòng)脈性能測(cè)量。根據(jù)虛擬探測(cè)器的當(dāng)前交通狀況，選擇以下三種操作之一：加速，減速或無(wú)速度變化。逐步操作計(jì)算將停止，直到虛擬探測(cè)器“到達(dá)”目的地為止，從而可以估算各種動(dòng)脈性能指標(biāo)，包括行駛時(shí)間。所提出的模型的一個(gè)有趣的特性是，可以用信號(hào)狀態(tài)數(shù)據(jù)對(duì)行進(jìn)時(shí)間估計(jì)誤差進(jìn)行自我校正，因?yàn)楫?dāng)虛擬探測(cè)車和真實(shí)探測(cè)車都滿足紅色信號(hào)相位時(shí)，它們的差異就可以減小。虛擬探頭模擬了動(dòng)脈駕駛員的正常行駛行為，因此可以看作是橫穿動(dòng)脈的代表車輛。SMART-SIGNAL數(shù)據(jù)收集系統(tǒng)已安裝在明尼蘇達(dá)州亨內(nèi)平縣法國(guó)大道沿11個(gè)十字路口的走廊上2007年2月?；谑录男盘?hào)數(shù)據(jù)將以24/7模式收集，然后立即存儲(chǔ)在SMART-SIGNAL系統(tǒng)中，從而產(chǎn)生了大量可用于研究的現(xiàn)場(chǎng)數(shù)據(jù)?，F(xiàn)場(chǎng)研究表明，所提出的數(shù)學(xué)模型可以在各種交通狀況下生成準(zhǔn)確的與時(shí)間相關(guān)的隊(duì)列長(zhǎng)度，行進(jìn)時(shí)間，?？奎c(diǎn)數(shù)以及其他性能指標(biāo)。

著錄項(xiàng)

  • 作者

    Ma, Wenteng.;

  • 作者單位

    University of Minnesota.;

  • 授予單位 University of Minnesota.;
  • 學(xué)科 Engineering Civil.;Transportation.
  • 學(xué)位 Ph.D.
  • 年度 2008
  • 頁(yè)碼 175 p.
  • 總頁(yè)數(shù) 175
  • 原文格式 PDF
  • 正文語(yǔ)種 eng
  • 中圖分類 建筑科學(xué);綜合運(yùn)輸;
  • 關(guān)鍵詞

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