城市轨道交通的客流特性分析

结合城市轨道交通的主要客流指标，对客流的时间分布特性、空间分布特性及其敏感性进行了分析，从系统配置适应客流需求、促进客流增长的角度出发，提出了改善服务水平和提高运营效益的思路和方法。     

城市轨道交通客流强度及其基本特征分析

本文结合国内外部分城市轨道交通客流强度数据,分析了不同城市轨道交通线网以及不同类型轨道交通线路客流强度的基本特征,从线路空间与网络演变角度剖析了线路客流强度演变的内涵,提出了改善城市轨道交通客流预测工作的建议。     

网络化运营模式下城市轨道交通客流分布特性

本文从网络化运营角度,以实际运营网络客流数据为基础,对城市轨道交通客流时间和空间分布特性进行了综合分析。时间分布上主要分析了日客流、周客流、月客流和年客流四个层面的客流特性,空间分布上主要采用了全网客流、高峰断面方向、进出站方向等指标来分析客流分布不均衡性。     

基于广义费用的城市轨道交通客流分配

为了更加客观全面地反映城市轨道交通出行者决策行为，提升城市轨道交通客流预测准确性，缓解线路运营面临的高峰时段客流拥挤现象，从出行广义费用角度出发，开展城市轨道交通客流分配研究。综合考虑票价、出行时间、舒适度、准时性等因素，构建了城市轨道交通乘客出行广义费用计算模型；以北京地铁5号线为例，将广义费用作为出行阻抗引入客流分配之中，构建了基于广义费用的随机用户平衡条件下的城市轨道交通客流分配模型，并提出了嵌套Logit模型的迭代加权法用以求解模型；基于分配模型及算法，对不同票价和列车容量条件下的城市轨道交通客流分配结果进行了对比分析。结果表明，基于广义费用的城市轨道交通客流分配模型能够实现对轨道交通流量的有效预测，可对各类缓解高峰时段拥挤措施的实施效果进行评估，辅助城市轨道交通领域相关决策。     

基于改进的BP神经网络探究航空与陆侧客流关系

为提高航空与陆侧交通客流关系分析的效率,本文基于大数据手段统计海量的航空客流和陆侧交通客流数据,利用改进的BP神经网络算法对航空客流和陆侧交通客流的关系进行了研究。首先,通过遍历隐含层神经元个数并增加算法运行次数的方法探寻隐含层最佳神经元个数。其次,保持航空客流数据不变,在时间轴上偏移陆侧交通客流数据,基于拟合系数设定评价函数,衡量航空客流和陆侧交通客流数据的匹配程度。其三,基于首都国际机场的实际数据进行实例分析,得到航空旅客乘坐陆侧交通方式提前到达和滞后离开机场的时间,并获得了航空客流和陆侧交通客流之间定量关系表达式,为机场陆侧交通设施的建设和改善提供了参考依据。     

基于注意力机制和时空卷积网络的客流预测方法

客流预测方法可以帮助城市轨道交通运营部门根据客流动态变化调配列车资源,是实现精准列车动态控制的基础。研究提出基于注意力机制和时空卷积网络模型的客流预测方法,融合不同功能的网络单元,使得网络可同时捕获客流数据的时间相关性、空间相关性和时空相关性,并采用注意力机制以提高模型预测的准确性,能够同时实现城市轨道交通多站客流的动态预测。基于北京地铁的实际客流数据对该方法和模型进行数值试验,结果表明该模型性能优于其他基线模型。     

城市轨道交通客流高峰传播影响研究

本文在总结城市轨道交通客流高峰特点的基础上,首次对城市轨道交通客流高峰传播的概念进行了定义,通过对城市轨道客流高峰传播机理的探讨,详细分析了城市轨道交通客流高峰传播造成的影响,并给出了度量客流高峰传播影响的主要内容。     

基于地铁建设的地下空间施工交通组织研究

城市点状地下空间是城市地下空间形态的基本构成因素,南宁地铁建设为大规模的城市地下空间开发提供了机遇。文章以南宁市朝阳路区域地下空间开发利用为例,根据项目建设施工计划、所在区域现状交通运行基本特征,现有地铁一号线火车站站点、朝阳广场站的施工进度,研究项目施工期间对区域交通环境所造成的影响以及其影响的程度;分析项目区域路段和交叉口的服务水平、交通设施容量等约束条件,并提出交通疏解的具体方案,以确保周边单位和商业区域进出交通的顺畅,把施工的交通影响尽量减至最低。     

基于XGBoost的城市轨道交通短时客流预测

城市轨道交通短时客流量具有随机性、周期性、相关性的特征,而短时客流预测作为城市轨道交通运营组织优化的关键技术,其预测数据的准确性将直接影响城市轨道交通运营组织的合理性。本文在分析城市轨道交通客流时间分布特征的基础上,提出了使用随机森林和XGBoost预测模型,对工作日和周末的客流分别进行预测,并以杭州地铁日均客流量最大的火车东站地铁站的进站客流为例进行实例分析,得到的预测数据与真实数据误差较小,验证了模型的有效性。最后将两种模型的预测误差进行对比分析,结果表明XGBoost预测模型对城市轨道交通客流的短时预测有着更高的精度和准确度。     

城市轨道交通车站客流承载力研究

在城市轨道交通近期建设规划工作中，需要对重点枢纽或片区近期所需的轨道交通线路和车站数量开展研究并决策线路是否纳入近期建设，为此有必要对城市轨道交通车站客流的合理承载力进行研究。本文首先研究全国已运营的客流量排名靠前的换乘枢纽车站以及已经达到饱和状态而采取限流措施的非换乘车站的实际客流数据，给出各类车站实际运营的承载能力，分析乘客进站各个步骤的理论通行能力以及限制车站客流承载力的瓶颈点。据此提出非换乘站和换乘车站合理的客流承载力的建议值，并提出提升车站客流承载力的建议措施。     

站城融合理念下高铁客运枢纽区域步行交通布置研究

本文对高铁客运枢纽区域内步行交通的影响范围和功能定位进行分析,提出在站城融合理念下,步行交通是高铁客运枢纽最重要的交通方式。利用开源数据,对比我国京沪高铁沿线与日本东海道新干线,以及北京南站、上海虹桥站、东京站、名古屋站,分析枢纽步行交通的影响因素,并提出站城融合背景下枢纽步行交通系统的规划建设重点和指标体系,为高铁客运枢纽实现站城融合、建立完善的步行交通系统提供参考。     

上海轨道交通6号线上南路站建筑设计回顾

对原上海轨道交通6、8号线上南路站总体布置以及地下一、二、三层车站建筑设计的难点作了介绍和分析，在此基础上，对车站功能布局、换乘方式、空间形式、资源共享等方面的设计作了新的探索。     

上海市东西通道工程与轨道交通14号线一体化布置方案探讨

上海市东西通道工程与轨道交通14号线共用一个走廊,均布设在沿线条件十分复杂的浦东大道下。如何进行合理的一体化布置是做好本工程的关键。结合两工程特点,从交通功能、结构合理性、对环境及交通的影响、工程量、车站布置以及分期实施情况等方面对一体化布置方案进行了研究和探讨,并提出了推荐意见。     

城市地下空间开发与轨道交通施工新技术

针对上海地区地下空间开发、轨道交通网络化发展以及城市密集区域工程建设的发展需求,对多线换乘地铁枢纽站改扩建、深层地基加固、地下深层障碍物清除、盖板逆筑、既有地下空间利用加层等多项施工新技术进行了研究和开发,并通过实际工程应用证实了各项技术的有效性,可为今后城市密集地区和复杂建设环境下的地下空间开发和施工建设提供借鉴。     

Evaluating the effects of bus design on passenger flow: Is agent-based simulation a feasible approach?

In this paper, we propose an agent-based simulation approach that is capable of simulating the flow of passengers on board buses and at bus stops. The intention is that it will be applied during vehicle development to analyze how vehicle design affects passenger flow, and thus also how it affects system performance such as dwell time. In turn, this could aid the developers in making design decisions early in the development process. Besides introducing the simulation tool itself, the paper explores the realism of the data generated by the tool. A number of passenger flow experiments featuring a full-scale bus mockup and 50 participants were carried out. The setup of these experiments mirrored a number of ‘bus journeys’ (regarding vehicle design, number of passengers boarding/alighting at each stop and so on) that had previously been simulated using the simulation tool. When the data from the simulations were compared with the data from the passenger flow experiments, it could be concluded that the tool is indeed able to generate realistic passenger flows, although with some errors when a large number of passengers board/alight. The simulated dwell times were rationally affected by the tested bus layout aspects. It was concluded that the tool makes it possible to evaluate how variations in bus layouts affect passenger flow, providing data of sufficiently high quality to be useful in early phases of vehicle design.     

A study on adjustment factors for U-turns in left-turn lanes at signalized intersections

U-turns are treated as left-turns in the current procedures for estimating saturation flow rates at signalized intersections. While U-turning vehicles are usually mixed with left-turning vehicles in inside or left-turn lanes and conflict with opposing through traffic as left-turning vehicles, the vehicle operating characteristics are different. The objective of this paper is to investigate the effects of U-turns on the traffic flow in left-turn lanes. Field data of 600 headways of left-turning passenger cars and 160 headways of U-turning passenger cars are recorded. The average headways of U-turning passenger cars are found to be significantly larger than those of left-turning passenger cars. The effects of U-turning vehicles depend upon the percent of U-turning vehicles in the left-turn lane, as well as the order of formation in the traffic stream. Adjustment factors for varying percents of U-turning vehicles in left-turn lanes are established.     

Lane-harmonised passenger car equivalents for heterogeneous expressway traffic

In order to account for variations in traffic composition during traffic analysis, passenger car equivalent (PCE) factors are used to convert flow rates of various vehicle classes into flow rates in terms of passenger car units (PCUs). Earlier studies have developed various methods to estimate PCE values but only a few of them are based on uninterrupted traffic flow, particularly for flow regimes with heterogeneous traffic where differential (lower) speed limits are imposed on commercial vehicles. This paper proposes a lane-harmonisation approach, which leverages on the high variation in traffic composition across the lanes, to estimate PCE factors for urban expressways. Multiple linear regression is used and the PCE factors obtained for motorcycles, light goods vehicles, and heavy goods vehicles are 0.65, 1.53, and 2.75, respectively. The estimated capacity flow rate after the application of the obtained PCE factors is around 2200 PCUs per hour per lane.     

地下车站出入口通道矩形顶管工程的结构设计与探讨

矩形顶管施工工艺因其施工时地下管线搬迁少,对地面道路交通影响小,以及低噪音、无扬尘的特点,在地下工程施工中得到了广泛的应用。详细介绍了矩形顶管的施工工艺及实施地铁车站出入口结构设计的特点,对矩形顶管设计中的防水措施及管节排版等环节进行了分析和探讨,可供其它类似工程借鉴。     

Impact of heavy vehicles on surrounding traffic characteristics

This work examines the impact of heavy vehicle movements on measured traffic characteristics in detail. Although the number of heavy vehicles within the traffic stream is only a small percentage, their impact is prominent. Heavy vehicles impose physical and psychological effects on surrounding traffic flow because of their length and size (physical) and acceleration/deceleration (operational) characteristics. The objective of this work is to investigate the differences in traffic characteristics in the vicinity of heavy vehicles and passenger cars. The analysis focuses on heavy traffic conditions (level of service E) using a trajectory data of highway I‐80 in California. The results show that larger front and rear space gaps exist for heavy vehicles compared with passenger cars. This may be because of the limitations in manoeuvrability of heavy vehicles and the safety concerns of the rear vehicle drivers, respectively. In addition, heavy vehicle drivers mainly keep a constant speed and do not change their speed frequently. This work also examines the impact of heavy vehicles on their surrounding traffic in terms of average travel time and number of lane changing manoeuvres using Advanced Interactive Microscopic Simulator for Urban and Non‐Urban Networks (AIMSUN) microscopic traffic simulation package. According to the results, the average travel time increases when proportion of heavy vehicles rises in each lane. To reflect the impact of heavy vehicles on average travel time, a term related to heavy vehicle percentage is introduced into two different travel time equations, Bureau of Public Roads and Akçelik's travel time equations. The results show that using an exclusive term for heavy vehicles can better estimate the travel times for more than 10%. Finally, number of passenger car lane changing manoeuvres per lane will be more frequent when more heavy vehicles exist in that lane. The influence of heavy vehicles on the number of passenger car lane changing is intensified in higher traffic densities and higher percentage of heavy vehicles. Large numbers of lane changing manoeuvres can increase the number of traffic accidents and potentially reduce traffic safety. The results show an increase of 5% in the likelihood of accidents, when percentage of heavy vehicles increases to 30% of total traffic. Copyright © 2014 John Wiley & Sons, Ltd.     

Heavy commercial vehicles‐following behavior and interactions with different vehicle classes

This work investigates the effect of heavy commercial vehicles on the capacity and overall performance of congested freeway sections. Furthermore, the following behaviors of heavy commercial vehicles and its comparison with passenger cars are presented. Freeways are designed to facilitate the flow of traffic including passenger cars and trucks. The impact of these different vehicle types is not uniform, creating problems in freeway operations and safety particularly under heavy demand with a high proportion of heavy vehicles. There have been very few studies concerned with the traffic behavior and characteristics of heavy vehicles in these situations. This study draws on extensive data collected over a long stretch of freeway using videotaping and surveys at several sites. The collected data were firstly used to study the interaction between heavy vehicles and passenger cars. Through a detailed trajectory analysis, the following behaviors of 120 heavy vehicles were then analyzed to provide a thorough understanding of heavy vehicles‐following behavior mechanism. The results showed a significant difference in the following behavior of heavy vehicles compared with other vehicles. Copyright © 2011 John Wiley & Sons, Ltd.