Competition and Ownership in Land Passenger Transport: The Sixth International Conference,Cape Town,South Africa,September 1999 - Part 2

This paper presents an overview of some recent developments in and policy issues relating to integrated transport systems in the European Union (EU). Both goods and passenger transport systems are considered in the context of actions recently undertaken and supported by the EU. The paper considers the very general background of these systems at the EU scale and offers insights into some recent successful and promising policy, real-life, and research attainments. In addition, it attempts to identify some directions for future actions in fields such as transport policy, transport technology, transport economics and transport scenarios.     

A Review of Pseudo Panel Data Approach in Estimating Short-run and Long-run Public Transport Demand Elasticities

Abstract

The distinctions between short-run and long-run public transport demand elasticities have been highlighted in the literature, but the identification of long-run travel demand has been constrained by existing research methodology and the unavailability of longitudinal travel survey data. The pseudo panel data approach using repeated cross-sectional data has been suggested as an alternative to conducting a longitudinal travel demand analysis when genuine panel data are not available. This paper comprehensively reviews the background and the current practices of pseudo panel data research, and introduces the challenges in applied research that need further investigation, particularly for public transport. A case study using the Sydney Household Travel Survey data is presented to demonstrate pseudo panel data construction and to identify the short-run and long-run public transport demand elasticities using a pseudo panel data approach. The research findings suggest that the public transport demand elasticity of price in Sydney is ?0.22 in the short run and ?0.29 in the long run.     

Towards a dynamic discrete-choice model of household automobile fleet size and composition

The emphasis on energy consumption in studies of traveller behaviour has led to increased interest in the development of policy sensitive models of automobile demand. In recognition of the fuller dimensions of automobile demand, a number of studies have considered choice amongst types of automobiles as well as number of automobiles. With rare exception, existing studies have concentrated on either type choice or number choice. In all instances the approach has been static. This paper develops a series of linked discrete-choice models to explain household automobile holdings (type and number) and adjustments in the holdings over time. The empirical study is part of an initial data effort leading up to the development of a full scale longitudinal panel of Sydney households. A model system based on a retrospective panel of 354 households, interviewed in 1980, is reported herein. The model is dynamic in the sense that it allows for prior decisions, brand loyalty and the costs of transacting.     

Household travel surveys: Where are we going?

In this paper, we commence by reviewing the recent history of household travel surveys. We note some of the problems that contemporary surveys are encountering throughout the world. We also review the data demands of current and emerging travel demand models, concluding that there are many new demands being placed on data, both in terms of the extent of the data required and the accuracy and completeness of the data. Noting that the standard method for conducting most household travel surveys is, and has been for some years, a diary, we briefly explore the evolution of the diary survey from the late 1970s to the present. In the next section of the paper, we explore a number of facets of potential future data collection. We include in this the use of GPS devices to measure travel, the potential of panel designs and some of the alternatives within panel designs, the development of continuous household travel surveys, especially in Australia, and the emerging capabilities in data fusion. Using some of these emerging methods for data collection and data simulation, we then propose a new paradigm for data collection that places the emphasis on a paid, national panel that is designed as a rotating, split panel, with the cross-sectional component conducted as a continuing survey. The basis of the panel data collection is proposed as GPS with demographic data, and the continuing national sample would also use GPS at its core. The potential to add in such specialised surveys as stated choice and process surveys is also noted as an advantage of the panel approach. We also explore briefly the notion that a special access panel or panels could be included as part of the design.     

Issues in the pre-analysis of panel data

An important phase of longitudinal data research is the pre-analysis of the data to determine the nature and extent of biases attributable to missing data. Loss of information takes many forms, but can be classified into the broad categories of loss of item data (i.e. a specific variable for some units of observation) and loss of unit data (i.e. the loss of an entire observation due to refusal or movement out of the sampled population). In this paper we discuss various ways of correcting for identified bias. The methods outlined are separated into those statistical procedures which are suitable in testing and correcting at the aggregate level, those relevant at the individual unit level, and nonstatistical procedures such as unit tracing. Since correction at the unit level is especially important for household panel data that is to be used in econometric modelling, we look in detail at the relationship between imputation and weighting methods of correcting for bias due to attrition.     

A framework for urban freight policy analysis

This paper provides an overview of the urban freight process, in the context of the supply and demand aspects of freight. A framework for analysis is developed, and within that framework, particular aspects of the urban freight process are described. Issues of concern from a public policy viewpoint are highlighted.

Seven main instruments related to public policy are introduced and their application described — taxes and subsidies, regulations, investment, operational instruments, planning, public ownership and research.

It is concluded that the importance of urban freight to the community and its relevance to urban transport justifies a higher level of attention in transport planning and policy formulation, and that there are a wide range of policy instruments available to enable this to be done. The objective of such planning and policy making needs to be specified in each specific context.     

Telecommuting and travel: state of the practice,state of the art

This paper provides an overview of the status of telecommuting in the United States, especially as it relates to changes in travel behavior. Regarding the state of the practice, the paper discusses some refinements to the definition of telecommuting that have developed through increased operational experience. It reports several policy statements involving telecommuting, and explores the appeal of telecommuting as a public policy instrument. It highlights some trends in the implementation of home-based and work center-based telecommuting, and suggests that visible public-sector involvement has been crucial to the increased activity in this area.In sketching the state of the art, the paper outlines some frequently-stated hypotheses on telecommuting and travel behavior, and summarizes current empirical findings relating to those hypotheses. Finally, it suggests a variety of topics suitable for further research. These include studying factors influencing the ultimate adoption levels of telecommuting; impacts on energy/air quality, mode choice, and location/urban form; interactions with other transportation demand management strategies; relationships to the traditional urban travel demand forecasting process; cost/benefit tradeoffs; and telecommuting centers.     

Addressing transport policy challenges through Policy-Packaging

Policy packaging is not a new concept and hardly anyone would dispute the merit of strategically considering and deploying several policy measures in combination to address transport policy issues. Yet the concept of policy packaging remains largely vague, and how to ‘package’ policies is not really considered or suggested. Policy packaging in most cases remains just a term. The Optimal Policies for Transport in Combination (OPTIC) project aimed to start advancing state-of-the-art in the design of policy packages. The project objective was to turn policy packaging into a well-established approach to policy making, with solid theoretical and methodological foundations that can also be practically applied in the field. This editorial to the special issue on Policy Packaging serves to first define and explain the main principles of policy packaging and the goals it strives to achieve: increasing effectiveness, implementability and thus efficiency. It then describes the main contribution of each of the papers in the special issue to research and practice of policy packaging and it outlines some avenues for further research. The paper concludes by setting a few criteria to distinguish a policy package from a ‘list’ of policies and by arguing that only through case studies and application in practice that state-of-the-art policy packaging can be really advanced.     

成品油管道穿越滑坡地段应力分析

成品油管道穿越山区滑坡地段时,受到滑坡推力的作用,易使管道产生过大变形而破坏。为探究此类管道安全问题并提出解决方案,使用应力分析软件CAESAR Ⅱ对某穿越滑坡地段的成品油管道进行应力及位移分析,得出其应力、位移分布,并分析纵向滑坡和横向滑坡对输油管道的影响。通过分析得出常规地段与滑坡地段的交界位置为输油管道的危险截面,且纵向滑坡对输油管道的应力及横向位移、纵向位移影响较大。     

The endogeneity of OECD gasoline taxes: Evidence from pair-wise,heterogeneous panel long-run causality tests

Despite the current interest in using fuel taxes as an instrument for climate policy, there has been little study of current automotive fuel tax regimes. We expand on two earlier cross-sectional studies on why fuel taxes differ across countries by using OECD panel data and employing heterogeneous panel cointegration and long-run panel Granger-causality techniques. We confirm some of those earlier studies’ conclusions. Further, we find that governments that rely on consumption-based taxes for revenues will have higher gasoline tax rates (than governments that rely on income and wealth/property-based taxes). But more significantly, we determine that higher gasoline demand among consumers “causes” democratic governments to set lower gasoline taxes—a finding with important implications for today’s climate/energy policy debate.     

The <Emphasis Type="Italic">Santiago Panel</Emphasis>: measuring the effects of implementing Transantiago

Although panels offer significant advantages over cross sectional data especially in terms of evaluating the effects of significant policy changes, there are precious few examples of panels built around an important change to an urban transport system. For this reason we took the opportunity of the introduction of Transantiago, a radically new public transport system for Santiago de Chile in February 2007, to form a panel, the first wave of which was taken in December 2006. The final objective was to use this Santiago Panel to estimate mode choice models considering both inertia and policy effects. This document describes both the design and construction of the panel, and presents some results based on an analysis of its four waves; for example, we registered a high percentage of mode change (55.1%) attributable to the introduction of the new system. The panel can claim the highest response rate (or lowest attrition) reported in the literature (95% in the second wave, 92% in the third one, and 85% in the forth one). This hints at the possibility of developing sophisticated models to evaluate the effects of a system shock in the presence of inertia in decision making.     

Multi-criteria analysis of optimal signal plans using microscopic traffic models

Increasing concerns on environment and natural resources, coupled with increasing demand for transport, put lots of pressure for improved efficiency and performance on transport systems worldwide. New technology nowadays enables fast innovation in transport, but it is the policy for deployment and operation with a systems perspective that often determines success. Smart traffic management has played important roles for continuous development of traffic systems especially in urban areas. There is, however, still lack of effort in current traffic management and planning practice prioritizing policy goals in environment and energy. This paper presents an application of a model-based framework to quantify environmental impacts and fuel efficiency of road traffic, and to evaluate optimal signal plans with respect not only to traffic mobility performance but also other important measures for sustainability. Microscopic traffic simulator is integrated with micro-scale emission model for estimation of emissions and fuel consumption at high resolution. A stochastic optimization engine is implemented to facilitate optimal signal planning for different policy goals, including delay, stop-and-goes, fuel economy etc. In order to enhance the validity of the modeling framework, both traffic and emission models are fine-tuned using data collected in a Chinese city. In addition, two microscopic traffic models are applied, and lead to consistent results for signal optimization. Two control schemes, fixed time and vehicle actuated, are optimized while multiple performance indexes are analyzed and compared for corresponding objectives. Solutions, representing compromise between different policies, are also obtained in the case study by optimizing an integrated performance index.     

A planning tool for evaluating vehicles miles travelled and traffic safety forecasts of growth management scenarios: A case study of Baton Rouge and New Orleans

This study describes an adaptable planning tool that examines potential change in vehicle miles travelled (VMT) growth and corresponding traffic safety outcomes in two urbanized areas, Baton Rouge and New Orleans, based on built environment, economic and demographic variables. This model is employed to demonstrate one aspect of the potential benefits of growth management policy implementation aimed at curbing VMT growth, and to establish targets with which to measure the effectiveness of those policies through a forecasting approach. The primary objective of this research is to demonstrate the need to break with current trends in order to achieve future goals, and to identify specific policy targets for fuel prices, population density, and transit service within the two study regions. Models indicate based on medium growth scenarios, Baton Rouge will experience a 9 percent increase in VMTs and New Orleans will experience 10 percent growth. This translates to corresponding increases in crashes, injuries and fatalities. The paper provides forecasts for planners and engineers to consider an alternative future, based on desired goals to reduce VMTs and therefore improve safety outcomes. A constrained-forecast model shows a cap on VMTs and crash rates is achievable through policy that increases fuel prices, population density and annual transit passenger miles per capita at reasonable levels through a growth management approach.     

Fundamentals of discrete multimodal choice modelling

Abstract

In this paper an overview is given of the most relevant issues relating to the application of multimodal choice models, with particular emphasis on disaggregate modal split models. The paper considers questions of data, such as type of data, alternative sampling strategies and problems of measurement; and modelling issues, such as model specification and estimation, including a good presentation of the statistical techniques'available. The paper also addresses the aggregation problem, which lies at the heart of one of today's most hotly contested debates: whether to use aggregate or disaggregate models for policy analysis, and in which circumstances.     

The optimal dual-pricing policy of mall parking service

In studies of parking policy, the role of parking pricing has been addressed. Most researches have focused on the determination of a proper price for city parking spaces that are open to the public and it is now evident that price is used by authorities as a tool to manage transport demand. However, studies of parking pricing that pertain to privately-owned parking resources are few and in particular, the problem of setting a proper price for physical market parking has rarely been studied, such as a mall’s ‘dual-pricing portfolio’ decision for the simultaneous determination of a parking fee and the consumer spending required for free parking (i.e., the ‘threshold’). This is a common problem for most malls, but the different agents involved (e.g., the visitors, the mall, the marketplace and the parking lot departments) usually have diverse goals, so the decision must take account of a multiplicity of criteria and subtle relationships. In order to systematically support this type of inter-departmental decision process, a decision model that includes an analytical decision-aid process and the relevant programming models is established. A numerical example verifies the proposed model by taking the data for a mall in Taiwan and the implications, in terms of management, are given. This systematic computational model can be generalized to any type of commercial market that requires a (new) parking pricing policy.     

On the distribution of urban road space for multimodal congested networks

Transport systems in real cities are complex with many modes of transport sharing and competing for limited road space. This work intends to understand how space distributions for modes and interactions among modes affect network traffic performance. While the connection between performance of transport systems and general land allocation is the subject of extensive research, space allocation for interacting modes of transport is an open research question. Quantifying the impact of road space distribution on the performance of a congested multimodal transport system with a dynamic aggregated model remains a challenge. In this paper, a multimodal macroscopic fundamental diagram (MFD) is developed to represent the traffic dynamics of a multimodal transport system. Optimization is performed with the objective of minimizing the total passenger hours traveled (PHT) to serve the total demand by redistributing road space among modes. Pricing strategies are also investigated to provide a higher demand shift to more efficient modes. We find by an application to a bi-modal two-region city that (i) the proposed model captures the operational characteristics of each mode, and (ii) optimal dynamic space distribution strategies can be developed. In practice, the approach can serve as a physical dynamic model to inform space distribution strategies for policy makers with different goals of mobility.     

The Intermittent Bus Lane signals setting within an area

Intermittent Bus Lane (IBL) used for bus priority is a lane in which the status of a given section changes according to the presence or not of a bus in its spatial domain: when a bus is approaching such a section, the status of that lane is changed to BUS lane, and after the bus moves out of the section, it becomes a normal lane again, open to general traffic. Therefore when bus services are not so frequent, general traffic will not suffer much, and bus priority can still be obtained. This measure can be operating at a single city block, but if all related control parameters along bus lines are considered together, more time gains can be obtained. In this paper, the basic structure and operation of IBL around a single intersection are briefly introduced, then the construction of an objective function and its relationships with the related priority control parameters along one bus line and their simplifications are described. Finally the calculations of the priority control parameters when there are several connected bus lines within an area and some simulation results are discussed.     

Variation of households<Emphasis Type="Bold">’</Emphasis> car ownership across time: application of a panel data model

For economic and environmental policy formulation and with the effort of creating less car dependent societies, it is important to study the changing characteristics of car ownership in a household through time as well as factors responsible of these variations. There is a vast body of literature on empirical studies of car ownership and use. These studies have investigated the socio-economic background of the decision maker, the built environment and the perception associated with owning a car as determinant factors of car ownership and use. In most cases, these analyses have been carried out using cross-sectional data sets. However, the analysis of factors determining changes in travel behavior of an individual or household requires information on their behavior over time (longitudinal data set). In this study, the German Mobility Panel (1996–2006) is used to examine variation of car ownership through time and across households. The panel data modeling results showed that there are variations of car ownership between households whereas changes in car ownership of a given household over time (within household variations) are insignificant. The influence of other factors such as the households’ socio-economic background, the availability of public transportation and shopping/leisure facilities, perception on parking difficulties and satisfaction with existing public transportation services on the car owning characteristics of households is also presented and discussed in this paper.

The case for heterodoxy in longitudinal analysis

Longitudinal analysis should be developed with the prime objective of discovering the characteristics of dynamic, disequilibrium processes. This will require a range of different research methods, including qualitative social research, repeated cross-section surveys, panel surveys, aggregate time series analysis, and simulation models. In each case it is essential that models should be formulated in a dynamic way (e.g. with lags, inertia and asymmetry). Examples are given of work using each of these methods, applied to the analysis of habit, aging, market volatility, turnover, long-term demand elasticities, and forecasting using demographic information.     

Development of control models for the planning of sustainable transportation systems

Planning of sustainable transportation systems requires integration of multiple systems while considering a holistic approach. A limited amount of research has been conducted that simultaneously considers all the transportation, economic activity, environmental and social effects. The proposed research envisages incorporating considerations related to sustainability and providing solutions to stakeholders in policy making. In this paper, a dynamic model for planning and development of sustainable transportation systems is presented. This is given by a system of three nonlinear differential equations representing the dynamics of the three independent states, namely, transportation, activity, and environmental systems. A policy scenario considering investment in energy efficient technologies and its effects on the states is discussed to assist making investment decisions. Optimal control techniques are used to design the controls. The results show that it is possible to formulate an optimal control to achieve the desired target. Numerical results, based on actual parameters, are presented to illustrate the long-term trends of the states. The methodology discussed in this paper will be helpful to decision makers in making optimal decisions. The contribution of this research work is the introduction of a systems and controls methodology to develop optimal policies for the design of sustainable systems.