Forecasting vs. observed outturn: Studying choice in faster inter-island connections

Passenger demand and, in particular, mode choice between the islands of Gran Canaria and Tenerife has experienced important changes in the last decade. In 2005 the jetfoil, which had been the dominant mode for many years, was replaced by a slower but cheaper fast ferry service. This induced important changes in the market shares of all competing modes (airplane, slow ferry and another fast ferry with a shorter in-sea time, but needing a bus connection in land). We estimated several discrete choice models, with data collected two years before, with the aim to test their forecasting performance in relation with observed behaviour. Interestingly, we found that an easy to interpret multinomial logit model allowing for systematic taste variations performed best in forecasting. We also discuss some model assumptions related to forecasting that allow replicating the effects of introducing a new mode more accurately. We finally show how the model can be used to examine the social benefits of a related infrastructure improvement project in the island of Gran Canaria.     

A comparison of rail liberalisation levels across four European countries

This paper presents the results of a research into railway regulation and liberalisation in Italy, France, Germany and Spain. The analysis covers the relationship between the State and the rail companies, network access conditions by operators, slot allocating and pricing schemes and how public service obligations are defined, financed and regulated.     

Uncertainty in traffic forecasts: literature review and new results for The Netherlands

This paper provides a review of transport model applications that not only provide a central traffic forecast (or forecasts for a few scenarios), but also quantify the uncertainty in the traffic forecasts in the form of a confidence interval or related measures. Both uncertainty that results from using uncertain inputs (e.g. on income) and uncertainty in the model itself are treated. The paper goes on to describe the methods used and the results obtained for a case study in quantifying uncertainty in traffic forecasts in The Netherlands.

Using the Ecopath with Ecosim Modeling Approach to Understand the Effects of Watershed-based Management Actions in Coastal Ecosystems

Resource managers are often tasked with identifying and assessing the potential impacts of management actions on the biotic communities under their care. When the management activities directly influence a single species of interest, managers can turn to a variety of models to aid in their understanding of potential changes to that population. However, as ecosystem-based management becomes more widely accepted, managers will have to understand how proposed actions will impact entire biotic communities, through both direct and indirect mechanisms. Thus, there is a need for ecosystem models that account for both trophic and non-trophic interactions, and that can be relatively easily used to assess a variety of management scenarios. We reviewed the available literature regarding incorporation of eutrophication and other anthropogenic impacts into Ecopath with Ecosim (EwE), one of the more widely used trophic ecosystem modeling frameworks. We found that a number of mechanisms of varying complexity have been used to include these stressors in models, providing managers with a suite of options that can be used to complement their existing management options as they seek to understand the impacts of human interactions on the natural environment.     

The multi-objective network design problem using minimizing externalities as objectives: comparison of a genetic algorithm and simulated annealing framework

Incorporation of externalities in the Multi-Objective Network Design Problem (MO NDP) as objectives is an important step in designing sustainable networks. In this research the problem is defined as a bi-level optimization problem in which minimizing externalities are the objectives and link types which are associated with certain link characteristics are the discrete decision variables. Two distinct solution approaches for this multi-objective optimization problem are compared. The first heuristic is the non-dominated sorting genetic algorithm II (NSGA-II) and the second heuristic is the dominance based multi objective simulated annealing (DBMO-SA). Both heuristics have been applied on a small hypothetical test network as well as a realistic case of the city of Almelo in the Netherlands. The results show that both heuristics are capable of solving the MO NDP. However, the NSGA-II outperforms DBMO-SA, because it is more efficient in finding more non-dominated optimal solutions within the same computation time and maximum number of assessed solutions.     

A NEW ESTIMATION METHOD OF SPATIAL PEAK TEMPORAL AVERAGE INTENSITY AND SPATIAL PEAK PULSE AVERAGE INTENSITY IN HIFU FIELD

High intensity focused ultrasound( HIFU) inmedicine has been developed rapidly for more thanten years.It changes the situation of slowly ad-vancing in ultrasonic therapy. HIFU has become anew character of ultrasound in medicine.The ex-tracorporal lithotriptor,the pyrothrapy,the HIFUsurgery,the HIFU hemostasis,and the HIFUabortion are the most important progresses.Theyshow that the applications of ultrasound in therapywill have greater project than that in diagnosis[1] .China has made m…     

Using BDI agents to improve driver modelling in a commuter scenario

The use of multi-agent systems to model and to simulate real systems consisting of intelligent entities capable of autonomously co-operating with each other has emerged as an important field of research. This has been applied to a variety of areas, such as social sciences, engineering, and mathematical and physical theories. In this work, we address the complex task of modelling drivers’ behaviour through the use of agent-based techniques. Contemporary traffic systems have experienced considerable changes in the last few years, and the rapid growth of urban areas has challenged scientific and technical communities. Influencing drivers’ behaviour appears as an alternative to traditional approaches to cope with the potential problem of traffic congestion, such as the physical modification of road infrastructures and the improvement of control systems. It arises as one of the underlying ideas of intelligent transportation systems. In order to offer a good means to evaluate the impact that exogenous information may exert on drivers’ decision making, we propose an extension to an existing microscopic simulation model called Dynamic Route Assignment Combining User Learning and microsimulAtion (DRACULA). In this extension, the traffic domain is viewed as a multi-agent world and drivers are endowed with mental attitudes, which allow rational decisions about route choice and departure time. This work is divided into two main parts. The first part describes the original DRACULA framework and the extension proposed to support our agent-based traffic model. The second part is concerned with the reasoning mechanism of drivers modelled by means of a Beliefs, Desires, and Intentions (BDI) architecture. In this part, we use AgentSpeak(L) to specify commuter scenarios and special emphasis is given to departure time and route choices. This paper contributes in that respect by showing a practical way of representing and assessing drivers’ behaviour and the adequacy of using AgentSpeak(L) as a modelling language, as it provides clear and elegant specifications of BDI agents.     

Rural speed limit changes and safety

There is little information in the literature on the relation between rural speed and safety. The wide variation in rural speed limits that are applied in different countries tends to confirm that this relation is poorly understood. The changes in fatal, injury and all accidents that followed a change in the rural speed limit in seven countries were regressed against the change in vehicle mean speed. The results showed that speed significantly affects safety and that within certain limits the relation is linear. The regressions indicated that a 1 km/h reduction in speed will reduce all severities of accidents by between 4 and 5%. It is suggested that part of this reduction is due to a change in economic factors.     

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.