基于TransCAD平台的OD矩阵反推的关键问题及实例分析

本文在介绍基于TransCAD软件平台下OD矩阵反推方法基础上,系统总结了OD反推理论在项目实践过程中遇到的关键问题,如观测路段、种子OD、交通分配方法等。以福州市高速公路网为例,用TransCAD软件进行多次OD反推,并对反推精度进行检验,为OD反推在工可中的广泛应用提供了可行的方案。     

TransCAD中OD矩阵反推方法在道路交通量预测中的应用研究

利用TransCAD软件OD矩阵反推功能,结合实践经验及国外相关资料,介绍了在城市新建项目交通影响评价过程中周边道路交通量预测方法。     

区域OD流预测的新方法

主要内容是①建立由现状网络流生成的OD矩阵,否定现状OD调查的必要性.②按经济为交通的"源需求"思路,建立由经济变量为主导的趋势型OD矩阵预测模型.③为发挥"交通反馈效应"的思路,建立了诱增型OD矩阵预测模型.④依配流理论,完成网络流的趋势预测和诱增预测.     

一种基于客流量调查的公交线路运营指标合理性检验方法

为进一步实现公交高效化运营与资源合理化配置,合理安排车辆运力与确定发车时间间隔至关重要。文章针对现有城市公交线路发车时刻表及运力安排一般方法存在的不足,提出了一种基于客流量调查的公交线路运营指标合理性检验方法,通过建立数学模型计算出线路单向最大日断面客流量,进而运用客流需求法计算得出线路日发车周转数、平均发车时间间隔和线路日运营需求车辆数,并结合实例分析,通过与实际线路运营指标对比,证明该方法具有较高的实用价值,可指导实际线路运营的合理优化。     

公交信息化:有“大脑”更智慧

<正>"随着移动互联网技术的不断深入发展,大数据技术的应用,将大大提高公交客流量及客流分布预测的准确性,使公交运力、运量配置更加有效,公交线路规划更加合理。"——中兴通讯股份有限公司移动事业部开发部工程师刘淑霞2011年,全国公交线路查询系统在PC端发布,如今,爱帮公交、熊猫公交、车来了、8684公交、彩虹公交、北京实时公交、苏州行、交通‘杭州、济南公交、武汉智能公交……从全国到地方,越来越多的手机APP遍行应用商店。     

接驳定制公交便捷返乡路

<正>近日,交通运输部等国家五部委联合发出通知,要求在春运期间开展"情满旅途"活动,为旅客春运出行提供"七心"服务,要发挥不同运输方式的比较优势方便旅客中转、换乘和出行。尤其是城市公交企业要加强公交线路与铁路列车和民航航班时刻的衔接。连日来,青岛各个交通枢纽站点客流量逐日增加,为方便乘     

农村公交推广“公车公营”正当时——河南开通城际公交线路看客运发展趋势

最近，笔者对河南已成功开通的部分城际公交线路进行了调查研究发现，     

泉州中心城区公交客流现状调查及分析

泉州是闽东南重要的港口城市,是福建省三大中心城市之一,海峡西岸经济区重要的制造业基地,在福建省的核心地位非常突出,发挥着侨乡工贸中心城市的先导作用。随着泉州城市化进程的加快,其城市人口不断增加、城市规模不断扩大,城区公交服务如何满足人民群众日益增加的出行需求,已经迫在眉睫。泉州中心城区公交客流调查公交线路跟车调查。公交线路跟车调查一般选取周二至周四时间段,同时要注意避开重大的社会活动。     

北京地铁高峰期涨价能否解决拥挤问题

本课题就北京市地铁高峰期涨价能否解决高峰期拥挤这一问题做出调查,应用SP-RP调查方法调查了北京市高峰期地铁中乘客的人群构成、乘车特点以及对涨价后交通方式的选择,用Logit回归模型进行数据分析,结果表明高峰期地铁涨价能够解决拥挤问题,分散的客流量与涨价幅度有关,分析得出的回归函数可以在政策出台后预测相应的分散客流量。     

中小城市的公交线网优化方法探讨——以重庆万盛经开区为例

为保障群众基本出行需求,保持公交行业稳定和持续发展,使群众能持续享受公共交通的便利,同时尽可能减少财政补贴支出费用和提高公交的运营效率,本文选择重庆万盛经开区为实例,结合实地调研、跟车调查、部门座谈会以及智慧万盛公交客流计数系统,剖析公交现状出行特征和线路存在的问题,分别从线路站点、车辆配置以及发车调度三个方面,提出具体的优化措施：保留重复率低、客流量有保证的线路;整合线路重复率高、客流量小的线路;优化非直线系数大的线路。优化后,公交线路减少了5条,配车数减少了49辆,日发车减少了851班次,日运营里程减少了10055.6 km,同时平均满载率提升0.15,优化后的公共交通资源可提供12.7万人次/天(约4635万人次/年)的公交运力,满足现状3600万人次/年的需求,不仅保证了市民群众的公交出行,还提升了公交运营效率,缩减了运营成本,为同类型城市的公交线网优化提供参考和借鉴。     

Statistical inference on transit route‐level origin–destination flows using automatic passenger counter data

We consider inferring transit route‐level origin–destination (OD) flows using large amounts of automatic passenger counter (APC) boarding and alighting data based on a statistical formulation. One critical problem is that we need to enumerate the OD flow matrices that are consistent with the APC data for each bus trip to evaluate the model likelihood function. The OD enumeration problem has not been addressed satisfactorily in the literature. Thus, we propose a novel sampler to avoid the need to enumerate OD flow matrices by generating them recursively from the first alighting stop to the last stop of the bus route of interest. A Markov chain Monte Carlo (MCMC) method that incorporates the proposed sampler is developed to simulate the posterior distributions of the OD flows. Numerical investigations on an operational bus route under a realistic OD structure demonstrate the superiority of the proposed MCMC method over an existing MCMC method and a state‐of‐the‐practice method. Copyright © 2015 John Wiley & Sons, Ltd.     

Estimation of population origin–interchange–destination flows on multimodal transit networks

Previous research has combined automated fare-collection (AFC) and automated vehicle-location (AVL) data to infer the times and locations of passenger origins, interchanges (transfers), and destinations on multimodal transit networks. The resultant origin–interchange–destination flows (and the origin–destination (OD) matrices that comprise those flows), however, represent only a sample of total ridership, as they contain only those journeys made using the AFC payment method that have been successfully recorded or inferred. This paper presents a method for scaling passenger-journey flows (i.e., linked-trip flows) using additional information from passenger counts at each station gate and bus farebox, thereby estimating the flows of non-AFC passengers and of AFC passengers whose journeys were not successfully inferred.The proposed method is applied to a hypothetical test network and to AFC and AVL data from London’s multimodal public transit network. Because London requires AFC transactions upon both entry and exit for rail trips, a rail-only OD matrix is extracted from the estimated multimodal linked-trip flows, and is compared to a rail OD matrix generated using the iterative proportional fitting method.     

Evaluation of a public transportation level of service concept

The level of service of a bus line is evaluated by its operational characteristics, particularly by the ratio between average bus travel time on a given route and the average passenger car travel time on the shortest distance between the origin and the destination of the bus in question. It is shown that the level-of-service measure may be predicted by such independent variables as route length, average distance between bus stations, number of signalized and unsignalized intersections, and the ratio between such intersections. It is hypothesized that use of other independent variables such as boarding and alighting passengers, or volume to capacity ratio on the route concerned, could improve the predictive power of the suggested models. Further research is recommended on the effect of these latter variables and other operational variables which might influence bus level of service, and also on the comparison between direct bus lines and lines which use transfer points.     

Fine-grained OD estimation with automated zoning and sparsity regularisation

Given a road network, a fundamental object of interest is the matrix of origin destination (OD) flows. Estimation of this matrix involves at least three sub-problems: (i) determining a suitable set of traffic analysis zones, (ii) the formulation of an optimisation problem to determine the OD matrix, and (iii) a means of evaluating a candidate estimate of the OD matrix. This paper describes a means of addressing each of these concerns. We propose to automatically uncover a suitable set of traffic analysis zones based on observed link flows. We then employ regularisation to encourage the estimation of a sparse OD matrix. We finally propose to evaluate a candidate OD matrix based on its predictive power on held out link flows. Analysis of our approach on a real-world transport network reveals that it discovers automated zones that accurately capture regions of interest in the network, and a corresponding OD matrix that accurately predicts observed link flows.     

A theoretical foundation for the relationship between generalized origin–destination matrix and flow matrix based on ordinal graph trajectories

This paper shows the relationship between flow, generalized origin–destination (OD), and alternative route flow from a set of ordinal graph trajectories. In contrast to traffic assignment methods that employ OD matrix to produce flow matrix, we use ordinal trajectory on a network graph as input and produce both the generalized OD matrix and the flow matrix, with the alternative and substitute route flow matrices as additional outputs. By using linear algebra‐like operations on matrix sets, the relationship between network utilization (in terms of flow, generalized OD, alternative route flow, and desire line) and network structure (in terms of distance matrix and adjacency matrix) are derived. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluation of an existing bus network using a transit network optimisation model: a case study of the Hiroshima City Bus network

This study evaluates an existing bus network from the perspectives of passengers, operators, and overall system efficiency using the output of a previously developed transportation network optimisation model. This model is formulated as a bi-level optimisation problem with a transit assignment model as the lower problem. The upper problem is also formulated as bi-level optimisation problem to minimise costs for both passengers and operators, making it possible to evaluate the effects of reducing operator cost against passenger cost. A case study based on demand data for Hiroshima City confirms that the current bus network is close to the Pareto front, if the total costs to both passengers and operators are adopted as objective functions. However, the sensitivity analysis with regard to the OD pattern fluctuation indicates that passenger and operator costs in the current network are not always close to the Pareto front. Finally, the results suggests that, regardless of OD pattern fluctuation, reducing operator costs will increase passenger cost and increase inequity in service levels among passengers.     

Analysis of real-time control strategies in a corridor with multiple bus services

Control strategies have been widely used in the literature to counteract the effects of bus bunching in passenger‘s waiting times and its variability. These strategies have only been studied for the case of a single bus line in a corridor. However, in many real cases this assumption does not hold. Indeed, there are many transit corridors with multiple bus lines interacting, and this interaction affects the efficiency of the implemented control mechanism.This work develops an optimization model capable of executing a control scheme based on holding strategy for a corridor with multiple bus lines.We analyzed the benefits in the level of service of the public transport system when considering a central operator who wants to maximize the level of service for users of all the bus lines, versus scenarios where each bus line operates independently. A simulation was carried out considering two medium frequency bus lines that serve a set of stops and where these two bus lines coexist in a given subset of stops. In the simulation we compared the existence of a central operator, using the optimization model we developed, against the independent operation of each line.In the simulations the central operator showed a greater reduction in the overall waiting time of the passengers of 55% compared to a no control scenario. It also provided a balanced load of the buses along the corridor, and a lower variability of the bus headways in the subset of stops where the lines coexist, thus obtaining better reliability for all types of passengers present in the public transport system.     

Estimation of mean and covariance of stochastic multi-class OD demands from classified traffic counts

This paper proposes a new model to estimate the mean and covariance of stochastic multi-class (multiple vehicle classes) origin–destination (OD) demands from hourly classified traffic counts throughout the whole year. It is usually assumed in the conventional OD demand estimation models that the OD demand by vehicle class is deterministic. Little attention is given on the estimation of the statistical properties of stochastic OD demands as well as their covariance between different vehicle classes. Also, the interactions between different vehicle classes in OD demand are ignored such as the change of modes between private car and taxi during a particular hourly period over the year. To fill these two gaps, the mean and covariance matrix of stochastic multi-class OD demands for the same hourly period over the year are simultaneously estimated by a modified lasso (least absolute shrinkage and selection operator) method. The estimated covariance matrix of stochastic multi-class OD demands can be used to capture the statistical dependency of traffic demands between different vehicle classes. In this paper, the proposed model is formulated as a non-linear constrained optimization problem. An exterior penalty algorithm is adapted to solve the proposed model. Numerical examples are presented to illustrate the applications of the proposed model together with some insightful findings on the importance of covariance of OD demand between difference vehicle classes.     

Estimation of mean and covariance of peak hour origin–destination demands from day-to-day traffic counts

This paper proposes a generalized model to estimate the peak hour origin–destination (OD) traffic demand variation from day-to-day hourly traffic counts throughout the whole year. Different from the conventional OD estimation methods, the proposed modeling approach aims to estimate not only the mean but also the variation (in terms of covariance matrix) of the OD demands during the same peak hour periods due to day-to-day fluctuation over the whole year. For this purpose, this paper fully considers the first- and second-order statistical properties of the day-to-day hourly traffic count data so as to capture the stochastic characteristics of the OD demands. The proposed model is formulated as a bi-level optimization problem. In the upper-level problem, a weighted least squares method is used to estimate the mean and covariance matrix of the OD demands. In the lower-level problem, a reliability-based traffic assignment model is adopted to take account of travelers’ risk-taking path choice behaviors under OD demand variation. A heuristic iterative estimation-assignment algorithm is proposed for solving the bi-level optimization problem. Numerical examples are presented to illustrate the applications of the proposed model for assessment of network performance over the whole year.     

Simultaneous estimation of an origin–destination matrix and link choice proportions using traffic counts

A procedure for the simultaneous estimation of an origin–destination (OD) matrix and link choice proportions from OD survey data and traffic counts for congested network is proposed in this paper. Recognizing that link choice proportions in a network change with traffic conditions, and that the dispersion parameter of the route choice model should be updated for a current data set, this procedure performs statistical estimation and traffic assignment alternately until convergence in order to obtain the best estimators for both the OD matrix and link choice proportions, which are consistent with the survey data and traffic counts.Results from a numerical study using a hypothetical network have shown that a model allowing θ to be estimated simultaneously with an OD matrix from the observed data performs better than the model with a fixed predetermined θ. The application of the proposed model to the Tuen Mun Corridor network in Hong Kong is also presented in this paper. A reasonable estimate of the dispersion parameter θ for this network is obtained.