Estimating the agglomeration benefits of transport investments: some tests for stability

The case for including agglomeration benefits within transport appraisal rests on an assumed causality between access to economic mass and productivity. Such causality is justified by the theory of agglomeration, but is difficult to establish empirically because estimates may be subject to sources of bias from endogeneity and confounding. The paper shows that conventional panel methods used to address these problems are unreliable due to the highly persistent nature of accessibility measures. Adopting an alternative approach, by applying semiparametric techniques to restricted sub-samples of the data, we find considerable nonlinearity in the relationship between accessibility and productivity with no positive effect to be discerned over broad ranges of the data. A key conclusion is that we are unable to distinguish the role of accessibility from other potential explanations for productivity increases. For transport appraisal, this implies that the use of conventional point elasticity estimates could be highly misleading.     

A genetic algorithm-based method for improving quality of travel time prediction intervals

The transportation literature is rich in the application of neural networks for travel time prediction. The uncertainty prevailing in operation of transportation systems, however, highly degrades prediction performance of neural networks. Prediction intervals for neural network outcomes can properly represent the uncertainty associated with the predictions. This paper studies an application of the delta technique for the construction of prediction intervals for bus and freeway travel times. The quality of these intervals strongly depends on the neural network structure and a training hyperparameter. A genetic algorithm–based method is developed that automates the neural network model selection and adjustment of the hyperparameter. Model selection and parameter adjustment is carried out through minimization of a prediction interval-based cost function, which depends on the width and coverage probability of constructed prediction intervals. Experiments conducted using the bus and freeway travel time datasets demonstrate the suitability of the proposed method for improving the quality of constructed prediction intervals in terms of their length and coverage probability.     

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.     

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.     

Refined parameter and uncertainty estimation when both variables are subject to error. Case study: estimation of Si consumption and regeneration rates in a marine environment

The problem of estimating parameters and their uncertainty from experimental measurements in marine ecosystems is a common task and often necessitates solving nonlinear equations. If the measurements are subject to individually varying errors (i.e., heteroscedastic data), the parameters are often estimated using a Weighted Least Squares (WLS) method. For estimating the parameter uncertainties, a linearized expression for the covariance matrix exists. Yet, both methods assume that the errors on the independent variable, also called “input”, is negligible, which is often not true. For instance, in order to determine uptake and regeneration rates of silicic acid by phytoplankton, concentration and isotopic abundance measurements are performed at the beginning (input) and at the end (output) of an incubation experiment. Here, the so-called input and output are measurements of the same quantities, i.e., determined in exactly the same way, only differing by the time at which the measurements were performed. Clearly, there is no reason to assume that the input measurements are subject to less error than the output measurements. We propose a refinement of the two abovementioned estimation methods which enlarges their applicability to cases where input noise is not negligible. The refined methods are evaluated on the uptake and regeneration processes of silicic acid and compared to the original procedures using Monte-Carlo simulations. The results reveal a smaller bias for the refined WLS estimator compared with the original one. An additional advantage of using the refined WLS cost function is that its residual value can be interpreted as a sample from a χ² distribution. This property is especially useful because it enables an internal quality control of the results. In addition, the parameter uncertainty estimation is significantly improved. By neglecting the effect of the input noise, a (potentially) important origin of the parameter variation is simply ignored. Therefore, without the refinement, the parameter uncertainties are systematically underestimated. Using the refined method, this systematic error disappears and on the whole, the parameter standard deviations are accurately estimated.     

Transportation mode choice and city-suburban public transportation service

A model is presented to describe the dynamics of transportation mode choice in which the interaction between transportation users and a public transportation authority results in self-organization. The model illustrates that a sufficient number of connections between a central city and its suburbs are required for self-organization to occur whereby public transportation use and service will grow.     

Mixed RP/SP models incorporating interaction effects

In order to analyse the impact of a new train service in Cagliari (Italy) a databank including information from a revealed preference (RP) and a stated preference (SP) survey was set up. The RP data concern choice between car, bus and train; the SP data consider the binary choice between a new train service (quicker, more frequent, with a lower fare and more stations than the current one) and the alternative currently chosen by car and bus users. Logit models allowing for correlation among RP alternatives were estimated for this mixed RP/SP data set using the artificial tree structure method. The analysis included level-of-service variables measured with an unusually high level of precision, latent or second order variables (such as comfort), inertia and interaction variables. Different specifications of the utility function were tested, including the expenditure rate model, and the effects of these specifications on modelling results are highlighted. Our results show that for a population mainly composed of fixed income workers, the expenditure rate model is superior to the traditional wage rate model, yielding lower and more significant subjective values of time. Moreover, we found that the non-linear specifications appear to be more suitable as not only better model results were obtained, but also the real distribution of the error terms was revealed (i.e. highlighting correlation among public transport options).     

Coastal Crisis: The Failure of Coastal Management in the Spanish Mediterranean Region

It is a fact that coastal zones in the Mediterranean are becoming progressively more seriously degraded. Instrumental to the phenomenon in Spain is the evident failure of the coastal management that the institutions have pursued for over three decades, both under the old, state-centralized model, and the new organizational model with the political division of land into autonomous regions. This failure can in part be explained not only by the inadequate tools the administration possesses to address the dynamism and complexity of the new economic activities that have sprung up along the coast, but also by incoherent sectoral policies. Finally, there has been no all-encompassing political strategy capable of dealing with coastal communities' demands for development and the need for the protection of ecosystems and their natural resources. All this has resulted not only in a deterioration of the area, but also in the discrediting of actions implemented by the institutions, and their plans and programs being perceived as an obstacle to economic development.     

A decision analysis framework for intermodal transport: Comparing fuel price increases and the internalisation of external costs

This paper presents the impact of fuel price increases on the market area of intermodal transport terminals. Aim of this research is to determine whether an increase in fuel prices is sufficient enough to raise the market area of intermodal transport to the same degree that would be accomplished by stimulating intermodal transport through policy instruments. Therefore, several fuel price scenarios are analysed in order to verify the impact of different fuel price evolutions on the market area of unimodal road transport compared to intermodal transport in Belgium. The LAMBIT-model (Location Analysis for Belgian Intermodal Terminals), which is a GIS-based model (Macharis and Pekin, 2008), is used to analyse the different fuel price increases and enables a visualisation of the impact on the market area. The LAMBIT model incorporates the different network layers for each transport mode by setting up a GIS network that includes four different layers: the road network, the rail network, the inland waterways network and the final haulage network. The geographic locations of the intermodal terminals and the port of Antwerp are added as nodes in the network and the Belgian municipality centres are defined and connected to the different network layers. Based on the different fuel price scenarios representing respectively a fuel price increase with 10% (low price case), 50% (business as usual case) and 90% (high price case), the results of the LAMBIT model show that the market areas rise in favour of intermodal barge/road and intermodal rail/road. Depending on the scenario, the degree of modal shift however differs. Additionally, in order to compare policy measures with the effect of a fuel price increase, the internalisation of the external costs is analysed with the LAMBIT model. For some years, the European Commission is supporting the idea that transportation costs should reflect the true impacts on environment and society, and is relentlessly pushing towards the so called ‘internalisation of external costs’ as a policy instrument in order to establish fair and efficient pricing of different transport modes. This requires monetarizing the external effects of transport and adding them to the already internalized costs in order to give the correct price signals. Results of this comparative analysis performed with the LAMBIT model are also presented in this paper.