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Delay Models at Signalized Intersections Considering Short Right-Turn Lanes and Right Turn on Red.

机译:考虑短右转车道和右转红灯的信号交叉口延迟模型。

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摘要

The most widely used procedures for estimating delay at signalized intersections are provided by the Highway Capacity Manual (HCM). Despite many revisions, the current HCM delay models lack consideration of short turn lanes and vehicles making a right turn on red (RTOR), both of which are commonly seen in real-life situations. Neglecting the delay caused by short-lane blockages and excluding RTOR traffic, the existing models can underestimate the delay for the signalized intersections.;To eliminate these shortcomings of the current HCM, comprehensive delay models were developed by considering the chance of short-lane blockage and right turns proceeding during red. The proposed analytical models were constructed via two different approaches: probabilistic theories and queue accumulation polygons (QAP). They were capable of handling delay estimation given different inputs. The effectiveness and validity of the proposed models were verified by the microscopic simulation model, SimTraffic, which was calibrated based on intersection field data.;The proposed models, developed with two different ideologies, showed their distinct advantages. By following the traditional HCM procedures, the probabilistic model only requires basic information as inputs, including traffic volume, saturation flow rate, signal timing plan, and short-lane length. It enhanced the HCM models by being able to handle delay estimation for short right-turn lane and RTOR. By incorporating the RTOR queuing and discharging information, the QAP model overcomes the shortcoming of HCM models where RTOR are directly removed before the capacity or delay analysis. It is better at modeling vehicular arrival and departure for both through and right-turn traffic under various signal control strategies and blockage scenarios.;Using the probabilistic model, it was found that the length of the short right-turn lane strongly influences the intersection delay. Delay decreases as the length of the right-turn lane increases. RTOR can reduce the over-saturation, thereby reducing the approach delay substantially, especially when the length of the lane is insufficient to accommodate queuing vehicles. Based on the field data studied in this research, both QAP model and probabilistic model yield better estimates for the approach delay than the HCM model. The results also confirmed that the HCM tends to underestimate the approach delay by ignoring the short-lane blockage and delay contributed by RTOR traffic.
机译:高速公路通行能力手册(HCM)提供了估计信号交叉口延误最广泛的程序。尽管进行了许多修订,但当前的HCM延迟模型没有考虑短弯道和车辆右转红灯(RTOR),这两种情况在现实生活中很常见。现有模型忽略了由短车道阻塞造成的延误并将RTOR流量排除在外,因此可以低估信号交叉口的延误。为了消除当前HCM的这些缺点,考虑了短车道阻塞的可能性,开发了综合的延误模型。在红色期间向右转。拟议的分析模型是通过两种不同的方法构建的:概率论和队列累积多边形(QAP)。他们能够处理给定不同输入的延迟估计。微观仿真模型SimTraffic是基于交会现场数据进行校准的,从而验证了所提模型的有效性和有效性。所提出的模型具有两种不同的意识形态,显示出各自的优势。通过遵循传统的HCM程序,概率模型仅需要基本信息作为输入,包括交通量,饱和流量,信号定时计划和短车道长度。它能够处理短的右转车道和RTOR的延迟估计,从而增强了HCM模型。通过合并RTOR排队和释放信息,QAP模型克服了HCM模型的缺点,即在容量或延迟分析之前直接删除RTOR。最好在各种信号控制策略和阻塞情况下对直通和右转交通的车辆到达和离开进行建模。;使用概率模型,发现右转右短车道的长度强烈影响交叉路口延误。延迟随着右转车道长度的增加而减少。 RTOR可以减少过饱和,从而显着减少进近延迟,尤其是在车道长度不足以容纳排队车辆时。根据本研究中研究的现场数据,QAP模型和概率模型均比HCM模型产生了更好的进近时延估计。结果还证实,通过忽略RTOR流量造成的短车道阻塞和延误,HCM往往低估了进近延误。

著录项

  • 作者

    Gao, Hongyan.;

  • 作者单位

    University of Nevada, Reno.;

  • 授予单位 University of Nevada, Reno.;
  • 学科 Engineering Civil.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 119 p.
  • 总页数 119
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:44:05

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