公交车系统调度模型构建

首先,我们将一天的时间分成了不同的多个时间段。然后,在每个时间段内,我们考虑到公交车公司和乘客两方面的利益,引入了公交车载客的平均满载率、乘客的等待时间和拥挤程度这3个目标函数来衡量公交车公司的利益和乘客的满意度。为求解该目标规划,我们采用了加权系数法,引入了加权因子,使多目标函数转化成单一目标的模型。同时也可以由求得的行车计划得到了公车站交所需的最小车辆数。     

基于kano模型和候车体验的公交站设施需求研究

目的 提升乘客在公交站内的等候体验,优化公交站配套设施的合理性与完备性,提高公交系统服务能力。方法 研究乘客的候车需求,构建乘客行为地图,筛选出25项需求研究样本,并分为6类,分别为对物理空间的需求,以及具有体验附加值的信息需求、附属需求、安全需求、休憩需求和卫生需求。通过kano模型对各个需求进行定性分析和定量统计。结果 构建了乘客的候车需求层级塔,基于用户满意度指数系数,通过敏感度的计算,最终得出各设施需求的重要度排序,并以此为基础提出公交站配套设施的配置策略。结论 通过对乘客候车需求重要度的研究,可根据不同站点的地理位置等特点以及乘客类型结构等具体情况对车站设施进行配置。     

场景化思维下的高铁站候车座椅设计研究

目的 探讨公共座椅在用户候车中的用户体验痛点,提出优化用户候车体验的公共座椅设计方案。方法 首先基于场景化思维对乘客候车这一场景进行分析,提炼出典型场景,其次对场景中乘客行为进行分析挖掘出用户痛点,通过重构乘客候车场景探索候车过程中乘客痛点的解决方法,最后将设计创意映射至高铁站候车座椅的设计方案中,完成高铁站候车座椅的创新方案设计,解决乘客候车过程中遇到的问题,有效满足乘客切实需求,为用户营造一个良好的候车体验。结论 场景化思维引入到高铁站候车座椅设计分析中,能帮助设计师更为全面地剖析乘客行为、明确候车座椅现存的问题、挖掘出乘客的潜在需求,进而创造性地提出解决方案,指导高铁站候车座椅的设计,同时基于场景化思维下的设计方法也为其他产品的创新设计提供了一个可供参考的设计途径。     

关于公交车调度的优化问题

本文主要是研究公交车调度的最优策略问题.我们建立了一个以公交车的利益为目标函数的优化模型,同时保证等车时间超过10分钟(或者超过5分钟)的乘客人数在总的等车乘客数所占的比重小于一个事先给定的较小值α.首先,利用最小二乘法拟合出各站上(下)车人数的非参数分布函数,求解时先用一种简单方法估算出最小配车数43辆.然后依此为参照值,利用Maple优化工具得到一个整体最优解:最小配车数为48辆,并给出了在公交车载客量不同条件下的最优车辆调度方案,使得公司的收益得到最大,并且乘客等车的时间不宜过长,最后对整个模型进行了推广和评价,指出了有效改进方向.     

火车站热舒适性的调查研究

对我国八个城市火车站的候车厅进行调查.通过主观调查与客观测试相结合的方法进行实验.结果表明,不同规模火车站,乘客候车时间长短明显不同;不同规模火车站应该有不同的热舒适标准;大部分火车站候车厅的舒适度得到乘客的认可;非空调火车站乘客满意度较低.     

基于大数据的智慧公交出行云平台

当前,传统的城市公交系统存在候车时间长,服务水平低,管理水平落后等各种问题,乘客整体满意度低。为了解决这些问题,本公司基于大数据及云计算技术,设计了一套智慧公交出行云平台框架。该平台通过对公交车辆海量即时信息和大量用户应用信息进行收集、存储,构建算法模型,为城市公共交通智能化提供大数据建模分析平台,并集信息采集、智能调度、信息发布等多种功能于一体。该平台的实际运营,将大大提高公交系统运营效率,给乘客更好的公交出行体验。本文将对该平台的设计思路和各项功能进行介绍。     

基于移动4G的车载视频系统的实现

为有效解决公交车内治安监控、乘客逃票以及司乘人员窃取票款行为的取证问题,采用基于移动4G的车载视频技术,以实现监控中心对公交车的有效监督和调度管理。经研究表明,基于移动4G的车载视频,运行稳定、可靠、实用性强。     

科技支撑为上海“智能公交”护航

<正>乘客用手机扫描站亭上的二维码,就可查询下一班公交车离站距离;电脑调度逐渐取代人工调度,可自动调整均衡车辆间隔;车厢里覆盖4G网络信号,让乘客上网更为便捷……     

基于人机工程学的城市公交车环境的调查与分析

1.公交车的研究背景及目的 随着时代的发展,公共交通工具越来越多,公交是最方便的一种形式,具有站点多、时间短、车次多等优势的同时,当然也存在很多的问题.社会在解决了人们"乘车难"的矛盾之后,公交车内环境的安全、舒适、健康、高效等的人性化需求矛盾就突显出来了.因此有必要探讨基于人机工程学的公交车内环境设计理论与方法,改进设计以满足人们对现代公交车的新需求[1-2].根据有关报道,高峰期车内每平方米可达11人之多;高度较低的车厢,使乘客站在车厢里感觉到压抑、空气不流通;玻璃车窗较小,乘客的视野受到影响;车辆行驶时的振动、噪音更是影响乘客的舒适;偏高的车内地板也是非常不符合人体工程学设计原理,给城市里的老年人、残疾人、孕妇、儿童的行动上带来一些不方便.公交车上的问题有很多,但毋庸置疑给我们生活带来了很多的便利.以前是单纯的乘坐公交车到达目的地,现在有很多城市都推出游览公交车,公交车的外貌发生了变化,变得更智能,美观、公交线路是根据当地的城市特色景观来规划.     

虚拟候车环境内视觉线索目视管理对乘客寻路行为的影响

在虚拟候车环境中,研究视觉线索所提供的信息与乘客视觉信息需求的一致性对其登乘行为的影响,通过调整候车环境中提供寻路信息的两种视觉线索(候车信息屏和车站检票口布局结构)与乘客所需信息的目视统一性,以完成任务的总时间、看屏时间及行动时间等作为乘客寻路表现的指标来评价不同形式的两种视觉线索的功能,为车站目视化管理提供科学依据。实验结果表明:候车信息屏上信息呈现的顺序在与使用者的目视编码需求保持一致时,乘客有较好的寻路表现;与顺序型和奇偶型布局相比,AB型布局能使乘客在较短的时间内形成空间认知,是一种对布局结构进行目视管理的理想类型。     

公交车调度优化模型

本文主要研究了一条公交线路在其每时段内各个车站点的客流统计数据为已知情况下的车辆运行计划时刻表的制定问题.一般情况下,公交公司在调查研究取得一定数据的基础上都是按"接连开出"的方法安排工作日的车辆行车调度表,使得在运行期内,一组车辆"鱼贯而出,再鱼贯而入",而我们主要研究了随着时间和空间上客流不均衡性的变化,车辆应如何调度的规律,建立了目标规划模型.实现了"有早出,有晚出",车辆有多有少的调度计划.在保证一定效益和顾客满意的情况下,使在岗车辆的总运行时间最短.所有的计算都在计算机上实现,得出了调度时刻表,且最少的车辆数为42,顾客与公交公司的满意程度比为:0.68:0.46.     

Probability-based bus headway regularity measure

In frequently serviced bus routes passengers are more concerned about bus headway regularity than actual punctuality of bus arrival to the schedule. Buses arriving within very small (bus bunching) or very large headways are of particular concern and much less desirable. In this study, a time-point (stop) level probability-based headway regularity metric to measure bus service reliability is first formulated as a function of bus dwell time, number of stops into the trip, passenger activities (i.e. arrival, boarding and alighting) and expectation (or tolerance) of bus headways. The proposed metric is then applied to evaluate a Chicago Transit Authority bus route by using automatic vehicle location (AVL) data. It is found that headway regularity during a bus trip is closely impacted by dispatching headway. Furthermore, the time-point level service reliability declines as passenger activity levels increase or as the maximum passenger anticipated headway decreases (i.e. passengers become more demanding of frequent bus services). The case study demonstrates that the proposed probability-based headway regularity measure provides an operationable metric to transit agencies in terms of improving the transit service to meet passengers? expectation and thus increase ridership. Lastly, this study demonstrates another important application of the AVL/APC data.     

公交车调度问题的研究

本题为带软时间窗的单线路单车型的公交调度问题,针对其多目标、多变量的动态特点,我们为满足不同的实际需求建立两个多目标规划模型:双车场模型和单车场模型.双车场模型的主要目标是使运客能力与运输需求(实际客运量)达到最优匹配,单车场模型的主要目标是使乘客的平均不方便程度和公交公司的成本达最小,其目的都是为了兼顾乘客与公司双方的利益.两个模型的主体都是采用时间步长法,模拟实际的运营过程,从而得出符合实际要求的调度方案:静态调度和动态调度方案.     

Models for the schedule optimization problem at a public transit terminal

This work deals with the proposal of some models for the schedule optimization problem for public transit networks. In particular, we consider the case of a transit terminal where passengers are supposed to split among different lines of a service, or even change mode of transportation in case of intermodal systems. Starting from a given schedule for the transit lines arriving at the terminal, the aim is to decide the optimal schedule for the output lines, in such a way to balance the operative costs of the service and the passenger waiting time at the transit terminal. We propose two different models for this problem, which present strong similarities with some well known combinatorial optimization models. Computational results are also presented, showing the suitability of the models to solve real case studies.     

Travel time prediction under heterogeneous traffic conditions using global positioning system data from buses

Travel time information is a vital component of many intelligent transportation systems (ITS) applications. In recent years, the number of vehicles in India has increased tremendously, leading to severe traffic congestion and pollution in urban areas, particularly during peak periods. A desirable strategy to deal with such issues is to shift more people from personal vehicles to public transport by providing better service (comfort, convenience and so on). In this context, advanced public transportation systems (APTS) are one of the most important ITS applications, which can significantly improve the traffic situation in India. One such application will be to provide accurate information about bus arrivals to passengers, leading to reduced waiting times at bus stops. This needs a real-time data collection technique, a quick and reliable prediction technique to calculate the expected travel time based on real-time data and informing the passengers regarding the same. The scope of this study is to use global positioning system data collected from public transportation buses plying on urban roadways in the city of Chennai, India, to predict travel times under heterogeneous traffic conditions using an algorithm based on the Kalman filtering technique. The performance of the proposed algorithm is found to be promising and expected to be valuable in the development of APTS in India. The work presented here is one of the first attempts at real-time short-term prediction of travel time for ITS applications in Indian traffic conditions.     

Passenger train scheduling on a single-track or partially double-track railway with stochastic information

This article investigates a scheduling problem for passenger trains on a single or partially double-track railway in which the total passengers’ trip time with a penalty function is minimized. Owing to the uncertainty of the real traffic system, the number of passengers boarding (leaving) the train at each station is treated as a random variable. Three kinds of criteria are introduced to compute the total passengers’ trip time, including the expected value criterion, the pessimistic value criterion and the optimistic value criterion. A 0-1 mixed integer programming model is constructed for the problem, and a branch-and-bound algorithm is also designed to solve the model, in which two strategies are introduced to resolve the conflicts on tracks. Finally, some numerical experiments are performed to show the performance of the model and the algorithm.     

Time Reliability Measures in bus Transport Services from the Accurate use of Automatic Vehicle Location raw Data

Archived automatic vehicle location (AVL) data are widely used in bus transportation, but typically contain anomalies, such as missing data points and unseen bus overtakings. These anomalies may alter the measurement of time reliability (i.e., headways and schedule time deviations) of buses at stops with respect to passenger experiences. However, in many studies, anomalies are ignored, neglected, or partially addressed. This paper investigates the effect of AVL anomalies on headways and schedule deviations, which are keys for regularity and punctuality evaluations and are well‐practicized among bus operators worldwide. The analysis is carried out on six scenarios, each representing a combination of AVL data anomalies. The outcomes show that addressing anomalies result in more severe regularity measures, which point out criticalities suffered by passengers, whereas it can be skipped for the measurement of punctuality. In addition, an increase of 5% of missing data results in the increase of 5% in the coefficient of variation of the headway, but it does not lead to meaningful variations in punctuality measures. These results are useful for both practitioners interested in passenger‐oriented measurement of time reliability and researchers working on the disclosure of the determinants of unreliability. Copyright © 2016 John Wiley & Sons, Ltd.     

武汉市空调公交车内空气质量的测试调查与改善建议

通过对武汉市具有典型代表性的空调公交车内空气环境质量进行跟踪测试,以及对武汉市百名不同领域的人员进行问卷调查,由测量计算结果、调查结论与相关公共交通工具卫生标准的对比发现:空调公交车内新风量不足、CO2浓度超标等问题是导致车内空气品质不佳的主要原因,这直接导致了大部分乘客在乘坐空调公交车时出现头晕、困倦、胸闷等不适问题。提出了几个投资成本低、便于操作的改进措施与建议,以期达到车内环境与节能最优化的效果。     

北京市公交车站噪声环境特性

为研究北京市公交站台噪声谱特性,对北京公交67路14个站台声学特性进行测量分析。结果显示,对象公交站台等效声级L Aeq处于较高水平,均值达76.5 dB(A),峰值与本底分别为78.5 dB(A)和67.1 dB(A)。频谱分析结果显示,站台噪声具有明显的低频特征;进一步分析存在若干较强的基频成分：低频段约在31.5 Hz与80 Hz附近,高频段则以8 kHz为代表。