The symmetric intersection design and traffic control optimization

It is well recognized that the left-turning movement reduces the intersection capacity significantly, because exclusive left turn phases are needed to discharge left turn vehicles only. This paper proposes the concept of Left-Hand Traffic (LHT) arterial, on where vehicles follow left-hand traffic rules as in England and India. The unconventional intersection where a LHT arterial intersects with a Right-Hand Traffic (RHT) arterial is named as symmetric intersection. It is only need three basic signal phases to separate all conflicts at symmetric intersection, while it at least need four signal phases at a conventional intersection. So, compared with the conventional intersection, the symmetric intersection can provide longer green time for the left-turning and the through movement, which can increase the capacity significantly. Through-movement waiting areas (TWAs) can be set at the symmetric intersection effectively, which can increase the capacity and short the cycle length furthermore. And the symmetric intersection is Channelized to improve the safety of TWAs. The Binary-Mixed-Integer-Linear-Programming (BMILP) model is employed to formulate the capacity maximization problem and signal cycle length minimization problem of the symmetric intersection. The BMILP model can be solved by standard branch-and-bound algorithms efficiently and outputs the lane allocation, signal timing decisions, and other decisions. Experiments analysis shows that the symmetric intersection with TWAs can increase the capacity and short the signal cycle length.     

五路环形交叉口交通量卡片调查法

为了系统而简便地获取5路环形交叉口分流向的交通量,在分析传统的记录车牌号法和交织断面调查法的基础上,设计了针对5路环形交叉口交通量的卡片调查法。调查方法为利用不同颜色的卡片标记从某一进口流向其他出口的抽样车辆,计算右转交通量的理论比例;记录所有进出口交通量和右转交通量,得到右转交通量的实际比例。根据调查量求解约束方程,可得到各进口分流向的交通量。以南京市新庄立交为例,运用该方法调查,计算底层平面环形交叉口各进口分流向的交通量。结果表明,在抽样率为5％时,右转交通量理论比例与实际比例的最大误差为9．16％。     

不同信号过渡方式对交叉口驾驶行为选择的影响

为掌握黄灯、绿闪和倒计时等不同信号过渡方式对驾驶行为选择的影响,通过对驾驶人黄灯期间交叉口驾驶行为决策过程及其因素的分析,采用现场视频摄录观测方法,对苏锡常地区的若干信号交叉口黄灯期间的机动车驾驶行为选择进行深度调查,对比了闯黄灯车辆行驶速度和初始位置,分析了前3辆机动车的驾驶行为选择.结果表明,信号交叉口采用绿闪和倒计时提示对驾驶行为选择影响较大,其闯黄灯行为发生率明显低于黄灯提示方式,但是倒计时提示会诱发机动车驾驶人加速通过交叉口并增加安全隐患.     

城市道路交叉口当量人群运行特征

基于非机动车和行人通过交叉口时的交通流运行特征, 定义了当量人群的概念来描述非机动车和行人对机动车通行的共同影响。统计了高峰小时的当量人群数据, 考虑样本的稳定性、样本量的大小以及应用的便利性, 以15 min为分析时段, 采用回归分析的方法得到了当量人群的当量人数与当量人群的平均群时距和群个数之间的回归关系模型。分析结果表明: 当量人群的群时距符合移位负指数分布; 当量人群的平均群时距随着当量人数的增加而减小; 当量人群的群个数随着当量人数的增加表现出先增加后减小的趋势。     

信号交叉口行人自行车交通强度状态划分研究

混合交通是造成交叉口拥堵和交通事故的重要原因之一.为了便于有效的研究交叉口混合交通信号控制策略及交叉口交通仿真,提出了信号交叉口人行横道绿灯时间行人自行车交通强度状态划分方法.分析了交叉口人行横道绿灯放行的交通特性,定义了人行横道绿灯放行时刻行人自行车聚集群的概念.从信号交叉口人行横道的"时空资源"利用角度,提出了划分人行横道绿灯时间行人自行车交通强度状态概念及必要性,选取了行人自行车绿灯时间通过流率、绿灯时间利用率以及行人自行车绿灯时间的空间占有率三个指标作为强度划分依据,选取K均值聚类为强度状态划分方法,对人行横道绿灯时刻行人自行车交通强度状态划分为三类,分别为低强度、中等强度和高强度.结合北京市平乐园交叉口为例,进行了行人自行车交通强度状态划分.     

右转车与行人冲突问题的解决方法探讨

本文通过分析深圳市城市交通存在的右转车辆与行人的冲突现象，提出了解决二者冲突的方法。尤其是针对设置了右转专用车道情况下，通过设计右转车辆与行人相位分开设置情况下的流量临界模型，提出了设置二者的相位分开设置的临界值的计算方法。实践表明，该方法有效地解决了行人与右转车辆的冲突问题，具有良好的运用前景。     

多Agent强化学习下的城市路网自适应交通信号协调配时决策研究综述

相对于传统的交通信号配时决策方法,多Agent 强化学习及其协调方法能更好地适应城市 路网交通环境的变化。为探讨其在城市路网自适应交通信号配时决策中的应用,系统地总结了多 Agent 强化学习及协调机制的研究方法,详细地分析了国内外研究现状,并指出现有研究中存在 的问题,在此基础上对未来研究进行了展望。研究结果表明,既有研究主要针对规模较小的路 网,存在维数灾难问题,强化学习与协调机制结合研究还不够深入,相关学习参数分析不够细 致,仿真环境和情景现实性不强。未来研究可以引入马尔科夫博弈提高决策协调性,嵌入混合交 通流、公交优先等交通管理思想增强决策实用性,引入先验知识及其他学习技术加快学习速度, 融入物联网、主动管理、大数据等先进理念和前沿技术增加决策的实时性,与交通诱导等集成提 升决策的系统性。     

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混合交通是我国城市交通的主要特征，特别是在平面信号交叉口。同相位不同方向行驶的机动车和自行车之间产生大量的干扰，严重影响了交叉口的通行能力，增加了安全隐患，给交通管理带来了难以治理的问题。微观行为模型是研究机非混合交通的有效工具，本文基于三相位信号控制交叉口处的机非混合交通问题，分析了影响机动车右转弯通过交叉口的主要因素，建立了右转机动车在信号交叉口内穿越直行自行车的微观行为模型和自由行驶模型，并利用实测数据对模型参数进行了标定，验证了模型的有效性。该模型揭示了信号交叉口处的机非干扰机理，为进一步研究混合交通条件下机动车的微观行为模型提供了一种方便、高效的仿真分析手段。     

Severity of pedestrian injuries due to traffic crashes at signalized intersections in Hong Kong: a Bayesian spatial logit model

The present study intended to (1) investigate the injury risk of pedestrian casualties involved in traffic crashes at signalized intersections in Hong Kong; (2) determine the effect of pedestrian volumes on the severity levels of pedestrian injuries; and (3) explore the role of spatial correlation in econometric crash‐severity models. The data from 1889 pedestrian‐related crashes at 318 signalized intersections between 2008 and 2012 were elaborately collected from the Traffic Accident Database System maintained by the Hong Kong Transport Department. To account for the cross‐intersection heterogeneity, a Bayesian hierarchical logit model with uncorrelated and spatially correlated random effects was developed. An intrinsic conditional autoregressive prior was specified for the spatial correlation term. Results revealed that (1) signalized intersections with greater pedestrian volumes generally exhibited a lower injury risk; (2) ignoring the spatial correlation potentially results in reduced model goodness‐of‐fit, an underestimation of variability and standard error of parameter estimates, as well as inconsistent, biased, and erroneous inference; (3) special attention should be paid to the following factors, which led to a significantly higher probability of pedestrians being killed or sustaining severe injury: pedestrian age greater than 65 years, casualties with head injuries, crashes that occurred on footpaths that were not obstructed/overcrowded, heedless or inattentive crossing, crashes on the two‐way carriageway, and those that occurred near tram or light‐rail transit stops. Copyright © 2017 John Wiley & Sons, Ltd.