Forecasting the demand for privatized transport - What economic regulators should know, and why

Forecasting has long been a challenge, and will remain so for the foreseeable future. But the analytical instruments and data processing capabilities available through the latest technology, and software, should allow much better forecasting than transport ministries, or regulatory agencies typically observe. Privatization brings new needs for demand forecasting. More attention is paid to risk under privatization, than when investments are publicly financed. And regulators must be able to judge traffic studies done by operators, and to learn what strategic behavior influenced these studies. Many governments, and regulators avoid good demand, modeling out of lack of conviction that theory, and models can do better than the"old hands"of the sector. This is dangerous when privatization changes the nature of business. For projects amounting to investments of $100-200 million, a cost of$ 100,000-200,000 is not a reason to reject a reasonable modeling effort. And some private forecasting firms are willing to sell guarantees, or insurance with their forecasts, to cover significant gaps between forecasts, and reality.Markets and Market Access,Environmental Economics&Policies,Economic Theory&Research,Decentralization,Banks&Banking Reform,Markets and Market Access,Economic Theory&Research,Banks&Banking Reform,Access to Markets,Environmental Economics&Policies

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

Towards a real-time microscopic emissions model

This article presents a new approach to microscopic road traffic exhaust emission modelling. The model described uses data from the SCOOT demand-responsive traffic control system implemented in over 170 cities across the world. Estimates of vehicle speed and classification are made using data from inductive detector loops located on every SCOOT link. This data feeds into a microscopic traffic model to enable enhanced modelling of the driving modes of vehicles (acceleration, deceleration, idling and cruising). Estimates of carbon monoxide emissions are made by applying emission factors from an extensive literature review. A critical appraisal of the development and validation of the model is given before the model is applied to a study of the impact of high emitting vehicles. The article concludes with a discussion of the requirements for the future development and benefits of the application of such a model

Beyond multimedia adaptation: Quality of experience-aware multi-sensorial media delivery

Multiple sensorial media (mulsemedia) combines multiple media elements which engage three or more of human senses, and as most other media content, requires support for delivery over the existing networks. This paper proposes an adaptive mulsemedia framework (ADAMS) for delivering scalable video and sensorial data to users. Unlike existing two-dimensional joint source-channel adaptation solutions for video streaming, the ADAMS framework includes three joint adaptation dimensions: video source, sensorial source, and network optimization. Using an MPEG-7 description scheme, ADAMS recommends the integration of multiple sensorial effects (i.e., haptic, olfaction, air motion, etc.) as metadata into multimedia streams. ADAMS design includes both coarse- and fine-grained adaptation modules on the server side: mulsemedia flow adaptation and packet priority scheduling. Feedback from subjective quality evaluation and network conditions is used to develop the two modules. Subjective evaluation investigated users' enjoyment levels when exposed to mulsemedia and multimedia sequences, respectively and to study users' preference levels of some sensorial effects in the context of mulsemedia sequences with video components at different quality levels. Results of the subjective study inform guidelines for an adaptive strategy that selects the optimal combination for video segments and sensorial data for a given bandwidth constraint and user requirement. User perceptual tests show how ADAMS outperforms existing multimedia delivery solutions in terms of both user perceived quality and user enjoyment during adaptive streaming of various mulsemedia content. In doing so, it highlights the case for tailored, adaptive mulsemedia delivery over traditional multimedia adaptive transport mechanisms