GIS-based transit trip allocation methods converting stop-level boarding and alighting trips into TAZ trips

ABSTRACT

This study introduces a framework to improve the utilization of new data sources such as automated vehicle location (AVL) and automated passenger counting (APC) systems in transit ridership forecasting models. The direct application of AVL/APC data to travel forecasting requires an important intermediary step that links stops and activities – boarding and alighting – to the actual locations (at the traffic analysis zone (TAZ) level) that generated/attracted these trips. GIS-based transit trip allocation methods are developed with a focus on considering the case when the access shed spans multiple TAZs. The proposed methods improve practical applicability with easily obtained data. The performance of the proposed allocation methods is further evaluated using transit on-board survey data. The results show that the methods can effectively handle various conditions, particularly for major activity generators. The average errors between observed data and the proposed method are about 8% for alighting trips and 18% for boarding trips.     

钱塘江下游断面水位预报

钱塘江潮位受众多因素影响,预报方法非常复杂。该文分析了钱塘江下游澉浦、乍浦潮和芦潮港各站潮位主要影响因素与变化特征,分别建立了各断面高潮位预报模型,分析检验了各预报模型结构的合理性与效果。结果表明,所用方法结构合理、使用方便、效果满意。     

A GIS‐based traffic analysis zone design: technique

The main purpose of this paper is to develop an efficient method to design traffic analysis zones (TAZs), which is necessary for implementing a planning process with Geographic Information System (GIS) for Transportation (GIS‐T), using statistical spatial data analyses and GIS technology. The major roles of GIS in this method are: (1) to produce basic spatial units (BSUs) with topological data structure; (2) to integrate various procedures during the TAZ generation including computer program routines; and (3) to visualize the output of each TAZ generation. One of the most significant reasons for obtaining well‐defined TAZs is the fact that they are defined at the outset of transportation demand modeling, used from trip generation to trip assignment, and will ultimately affect transportation policy decisions.

Toward obtaining well‐defined TAZs, this paper concentrates on two important constraints: homogeneity and contiguity. Iterative partitioning technique is adopted to promote the optimum homogeneity of generated TAZs, while a contiguity checking algorithm is developed to ensure contiguous TAZs are generated by the iterative partitioning technique.     

The future of trucking technology in Brazil: results of a technology forecasting model

Abstract

The aim of this article is to identify a set of technological events related to the Brazilian truck fleet that are well placed hierarchically regarding their possibility of occurrence and pertinence for the horizon year of 2021. For this we propose and apply a Technology Forecasting Model for trucks (called TFM/Trucks) based on the Delphi technique, considering 28 technological events associated with six internal forecasting dimensions: safety, efficient use of energy and alternative fuels, materials technology, operational schemes, comfort and environment. The ranking of the technological events, considering hypothetical situations for analysis, indicate significant concern over the safety dimension, with four of the five events (passive safety and active safety) classified among the 10 events with the greatest chance of occurring and pertinence, irrespective of the panelists' degree of specialization. The environmental dimension, with respect to the predominance of electric powered trucks with lower level of atmospheric pollutants, was always in one of the first two positions, regardless of the situation studied. In the final ranking, the five best-classified events represented the dimensions of safety, environment, materials technology and comfort, with environment and passive safety predominating.     

基于UML的质量监督管理信息系统需求分析

依托辽宁省交通工程质量监督综合信息系统的开发实际,介绍了质量监督管理信息系统的业务流程和基本功能,利用UML对部分功能进行需求分析,为同类系统的需求分析工作提供了参考实例。     

Complementarity formulations for the cell transmission model based dynamic user equilibrium with departure time choice, elastic demand and user heterogeneity

In this paper we formulate the dynamic user equilibrium problem with an embedded cell transmission model on a network with a single OD pair, multiple parallel paths, multiple user classes with elastic demand. The formulation is based on ideas from complementarity theory. The travel time is estimated based on two methods which have different transportation applications: (1) maximum travel time and (2) average travel time. These travel time functions result in linear and non-linear complementarity formulations respectively. Solution existence and the properties of the formulations are rigorously analyzed. Extensive computational experiments are conducted to demonstrate the benefits of the proposed formulations on various test networks.     

A model to assess public transport demand stability

Transport authorities, especially those in developing countries where rising income stimulate increased car ownership rates, are often concerned with maintaining or increasing levels of public transport use. Therefore, the ability to identify clients at risk of abandoning the system can be valuable for remedial measures, allowing for more focused quality improvements. We present and apply a model that determines the probability of migrating from public to private transport at both aggregated and disaggregated levels. In application, the model predicted migration with 60% accuracy in the first preference recovery measure. The proposed model can improve the understanding of the behavior of public transport users, the analysis of demand stability and the factors influencing migration. This, in turn, can help to focus policy and management measures and increase the efficiency of public investment.     

一种基于核函数法的步行需求预测方法

步行需求预测对于步行系统的发展及规划非常重要，在概略规划方法的基础上，通过分析步行出行的相关特征，引入核密度函数法表达步行出行特征，形成基于核密度函数的步行需求预测方法，通过对中山市主城区的实际应用，方法具有较好的可操作性。     

Forecasting petrol demand and assessing the impact of selective strategies to reduce fuel consumption

Abstract

The use of fossil fuels in transportation is an important topic as a result of growing concerns over global warming. Automobile petrol demand has been of particular interest to researchers and policy-makers, given that the automobile is a major contributor to the enhanced greenhouse effect. This paper forecasts Australia's automobile petrol demand up to the year 2020 based on the best performing forecasting model selected out of eight models. In order to establish ways to reduce the demand for petrol, and the consequent by-product of reducing the amount of greenhouse gas emissions, we have estimated the impact on CO₂ for several potential policy instruments, using Transportation and Environment Strategy Impact Simulator (an integrated transport, land use and environmental strategy impact simulation programme). We find that a carbon tax of AU$0.50/kg can reduce automobile kilometres by 5.9%, resulting in reduced demand for petrol and a reduction in CO₂ of 1.5%.     

Generating synthetic baseline populations from register data

The paper presents a population synthesiser based on the method of Iterative Proportional Fitting (IPF) algorithm developed for the new Danish national transport model system. The synthesiser is designed for large population matrices and allows target variables to be represented in several target constraints. As a result, constraints for the IPF are cross-linked, which makes it difficult to ensure consistency of targets in a forecast perspective. The paper proposes a new solution strategy to ensure internal consistency of the population targets in order to guarantee proper convergence of the IPF algorithm. The solution strategy consists in establishing a harmonisation process for the population targets, which combined with a linear programming approach, is applied to generate a consistent target representation. The model approach is implemented and tested on Danish administrative register data. A test on historical census data shows that a 2006 population could be predicted by a 1994 population with an overall percentage deviation of 5-6% given that targets were known. It is also indicated that the deviation is approximately a linear function of the length of the forecast period.