Disaggregated Approaches to Freight Analysis: A Feasibility Study.

Forecasting the demand for freight transport is notoriously difficult. Although ever more advanced modelling techniques are becoming available, there is little data available for calibration. Compared to passenger travel, there are many fewer decision makers in freight, especially for the main bulk commodities, so the decisions of a relatively small number of principal players greatly influence the outcome. Moreover, freight comes in various shapes, sizes and physical states, which require different handling methods and suit the various modes (and sub-modes) of transport differently. In the face of these difficulties, present DTp practice is to forecast Britain's freight traffic using a very simple aggregate approach which assumes that tonne kilometres will rise in proportion to GDP. Although this simple model fits historical data quite well, there is a clear danger that this relationship will not hold good in the future. The relationship between tonne kilometres and GDP depends on the mix of products produced, their value to weight ratios, number of times lifted and lengths of haul. In the past, a declining ratio of tonnes to GDP has been offset by increasing lengths of haul. This has come about through a complicated set of changes in product mix, industrial structure and distribution systems. A more disaggregate approach which studies changes in all these factors by industrial sector seems likely to provide a better understanding of the relationship between tonne kilometres and GDP. However, there are also problems with disaggregation. As we disaggregate we get more understanding of what might change in the future, but are less able to project trends forward. This can be seen if we consider the future amounts of coal movements. Theoretically there is clearly scope for better forecasting by allowing for past trends to be overturned by a movement towards gas powered electricity generation and more imports of coal direct to coastal power stations. However, making such a sectoral forecast is extremely difficult, and inaccuracy here may more than offset the theoretical gain referred to earlier. This is because it is usually easier to forecast to a given percentage accuracy an aggregate rather than its components. For example, the percentage error on sales forecasts of Hotpoint washing machines will be greater than that for the sales of all washing machines taken together. This occurs because different makes of washing machines are substitutes for each other, so forecasts for Hotpoint washing machines must take into account uncertainty over Hotpoint's market share as well as uncertainty over the future total sales of washing machines. Nevertheless, a disaggregate investigation of the market could spot trends which were `buried' in the aggregate figures. For example, rapidly declining sales for one manufacturer might indicate their leaving the market, which with less competition would then price up and so reduce the total future sales. We have assumed above that the use of the term disaggregate in the brief refers to disaggregation by industrial sector. An alternative usage of the word disaggregate in this context is when referring to modelling at the level of the individual decision making unit. Disaggregate freight modelling in this sense would involve analysing decisions in order to determine the utility weight attached to different attributes of available transport options. Because data on suitable decisions is not readily available in this country, due to commercial confidentiality, we have recently undertaken research in which we have presented decision makers with hypothetical choices, and obtained the necessary utility weights from their responses. Whilst initial scepticism is understandable, this method has produced results acceptable for use in major projects. ITS itself has provided algorithms (known as Leeds Adaptive Stated Preference) which have been used to derive utility weights for use by British Rail in forecasting cross-channel freight, by DTp in evaluating the reaction of commercial vehicles to toll roads, and by the Dutch Ministry of Transport in modelling freight in the Netherlands. In the light of the above, the following objectives were set for the feasibility study: (1)To determine if a forecasting approach disaggregated by industrial sectors, as under the first definition above, can be used to explain recent trends in freight transport; (2)To test the feasibility of the disaggregated approach for improving the understanding of likely future developments in freight markets, this being informed by current best understanding of the disaggregate decision-making process as under the second definition above

Air freight demand models: An overview

A survey is presented of some of the approaches which have been considered in freight demand estimation. The few existing continuous time computer simulations of aviation systems are reviewed, with a view toward the assessment of this approach as a tool for structuring air freight studies and for relating the different components of the air freight system. The variety of available data types and sources, without which the calibration, validation and the testing of both modal split and simulation models would be impossible are also reviewed

Energy demand models for policy formulation : a comparative study of energy demand models

This paper critically reviews existing energy demand forecasting methodologies highlighting the methodological diversities and developments over the past four decades in order to investigate whether the existing energy demand models are appropriate for capturing the specific features of developing countries. The study finds that two types of approaches, econometric and end-use accounting, are used in the existing energy demand models. Although energy demand models have greatly evolved since the early 1970s, key issues such as the poor-rich and urban-rural divides, traditional energy resources, and differentiation between commercial and non-commercial energy commodities are often poorly reflected in these models. While the end-use energy accounting models with detailed sector representations produce more realistic projections compared with the econometric models, they still suffer from huge data deficiencies especially in developing countries. Development and maintenance of more detailed energy databases, further development of models to better reflect developing country context, and institutionalizing the modeling capacity in developing countries are the key requirements for energy demand modeling to deliver richer and more reliable input to policy formulation in developing countries.Energy Production and Transportation,Energy Demand,Environment and Energy Efficiency,Energy and Environment,Economic Theory&Research

Assessing the future of air freight

The role of air cargo in the current transportation system in the United States is explored. Methods for assessing the future role of this mode of transportation include the use of continuous-time recursive systems modeling for the simulation of different components of the air freight system, as well as for the development of alternative future scenarios which may result from different policy actions. A basic conceptual framework for conducting such a dynamic simulation is presented within the context of the air freight industry. Some research needs are identified and recommended for further research. The benefits, limitations, pitfalls, and problems usually associated with large scale systems models are examined

National Multi-Modal Travel Forecasts. Literature Review: Aggregate Models

This paper reviews the current state-of-the-art in the production of National Multi-Modal Travel Forecasts. The review concentrates on the UK travel market and the various attempts to produce a set of accurate, coherent and credible forecasts. The paper starts by a brief introduction to the topic area. The second section gives a description of the background to the process and the problems involved in producing forecasts. Much of the material and terminology in the section, which covers modelling methodologies, is from Ortúzar and Willumsen (1994). The paper then goes on to review the forecasting methodology used by the Department of Transport (DoT) to produce the periodic National Road Traffic Forecasts (NRTF), which are the most significant set of travel forecasts in the UK. A brief explanation of the methodology will be given. The next section contains details of how other individuals and organisations have used, commented on or attempted to enhance the DoT methodology and forecasts. It will be noted that the DoT forecasts are only concerned with road traffic forecasts, with other modes (rail, air and sea) only impacting on these forecasts when there is a transfer to or from the road transport sector. So the following sections explore the attempts to produce explicit travel and transportation forecasts for these other modes. The final section gathers together a set of issues which are raised by this review and might be considered by the project

National Multi-Modal Travel Forecasts. Literature Review: Aggregate Models

This paper reviews the current state-of-the-art in the production of National Multi-Modal Travel Forecasts. The review concentrates on the UK travel market and the various attempts to produce a set of accurate, coherent and credible forecasts. The paper starts by a brief introduction to the topic area. The second section gives a description of the background to the process and the problems involved in producing forecasts. Much of the material and terminology in the section, which covers modelling methodologies, is from Ortúzar and Willumsen (1994). The paper then goes on to review the forecasting methodology used by the Department of Transport (DoT) to produce the periodic National Road Traffic Forecasts (NRTF), which are the most significant set of travel forecasts in the UK. A brief explanation of the methodology will be given. The next section contains details of how other individuals and organisations have used, commented on or attempted to enhance the DoT methodology and forecasts. It will be noted that the DoT forecasts are only concerned with road traffic forecasts, with other modes (rail, air and sea) only impacting on these forecasts when there is a transfer to or from the road transport sector. So the following sections explore the attempts to produce explicit travel and transportation forecasts for these other modes. The final section gathers together a set of issues which are raised by this review and might be considered by the project

If, At First, The Idea is Not Absurd, Then There is No Hope For It: Towards 15 MtC in the UK Transport Sector.

This paper examines the possibilities of reducing transport carbon dioxide emissions in the UK by 60 per cent by 2030 using a modified scenario building and backcasting approach. It examines a range of policy measures (behavioural and technological), assessing how they can be effectively combined to achieve the required level of emissions reduction. The intention is to evaluate whether such an ambitious target is feasible, identify the main problems (including the transition costs), and the main decision points over the 30-year time horizon. This paper outlines the first stages of the research, providing: An introduction to futures studies, including a review of forecasting, scenario building and backcasting approaches; An assessment of the UK transport sector's contribution to climate change and global warming, and; Setting targets for 2030, forecasting the business as usual situation for all forms of transport in the UK, and assessing the scale of change in terms of achieving the emissions reductions. The benefits of scenario building and backcasting are that innovative packages of policy measures can be developed to address emissions reduction targets. It allows trend-breaking analysis, by highlighting the policy and planning choices to be made by identifying those key stakeholders that should be included in the process, and by making an assessment of the main decision points that have to be made (the step changes). It also provides a longer-term background against which more detailed analysis can take place.

Survey of air cargo forecasting techniques

Forecasting techniques currently in use in estimating or predicting the demand for air cargo in various markets are discussed with emphasis on the fundamentals of the different forecasting approaches. References to specific studies are cited when appropriate. The effectiveness of current methods is evaluated and several prospects for future activities or approaches are suggested. Appendices contain summary type analyses of about 50 specific publications on forecasting, and selected bibliographies on air cargo forecasting, air passenger demand forecasting, and general demand and modalsplit modeling

A Review of Rail Research Relevant to the Case for Increased Rail Investment.

The purpose of this paper is to provide a review of rail transport research which has a bearing on the case of increased rail investment. The paper focuses on research which has been conducted on the demand for rail travel, both passenger and freight, rather than the supply side or new technology. The aim is to identify where we believe there to be significant gaps in knowledge and key areas in which further research is required are outlined. The paper deals with the following issues: the investment and funding mechanisms that currently exist for rail; the extent to which changes in the fare and service quality of rail affect the demand for rail travel and also the demand for air and road travel; the environmental and congestion benefits of diverting traffic from road and air to rail; and the links between rail investment and economic development. Where appropriate, the discussion considers inter-urban travel, suburban travel, light rail transit and freight transport separately

A BI-LEVEL SCHEME FOR ASSESSING THE IMPACT OF AIR TRANSPORTATION ON LOCAL DEVELOPMENT

An approach to assess the impact of the creation or expansion of an air transport infrastructure over regional development is proposed in this paper. Effective long term planning of this costly investment requires performing an overall analysis of socio-economic consequences through long term forecasting, scenario generation and risk analysis. One of main aspects of this task is related with the estimation of future demand over the modified transportation network which attends the considered region. The proposed approach makes use of two complementary models: One model is devoted to demand forecasting taking into account the modified accessibility of the multimodal transportation network, the other one defines the global transport supply according to a profit maximization behavior for the involved transport system. The demand forecasting process is based on an entropy maximization approach with flexible origin-destination levels to determine the intensity and the distribution of new origin-destination vectors. A two level solution technique considering vehicle flows at the first level and the payload/passengers flows at the second level is introduced. The proposed solution scheme is composed of an iterative process between the current solution for demand forecasting and the supply optimization problem: the entropy maximizing distribution problem provides the origin-destination matrix given a cost/capacity structure, while the supply optimization problem provides this cost/capacity structure resulting from the accessibility level, given the updated origin-destination vectors. The proposed approach is illustrated in the case of a fast developing rural agro-industrial area in central Brazil, where the consequences of the installation of a medium size airport are assessed.