Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patternsof this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.

Lateral Dynamic Models for High-Speed Railway Bridges and Vehicles

The analysis of the running safety of railway vehicles on viaducts subject to strong lateral actions such as cross winds requires coupled nonlinear vehicle-bridge interaction models, capable to study extreme events. In this paper original models developed by the authors are described, based on finite elements for the structure, multibody and finite element models for the vehicle, and specially developed interaction elements for the interface between wheel and rail. The models have been implemented within ABAQUS and have full nonlinear capabilities for the structure, the vehicle and the contact interface. An application is developed for the Ulla Viaduct, a 105 m tall arch in the Spanish high-speed railway network. The dynamic analyses allow obtaining critical wind curves, which define the running safety conditions for a given train in terms of speed of circulation and wind speed

Passenger Exposure to Magnetic Fields due to the Batteries of an Electric Vehicle

In electric vehicles, passengers sit very close to an electric system of significant power. The high currents achieved in these vehicles mean that the passengers could be exposed to significant magnetic fields. One of the electric devices present in the power train are the batteries. In this paper, a methodology to evaluate the magnetic field created by these batteries is presented. First, the magnetic field generated by a single battery is analyzed using finite elements simulations. Results are compared to laboratory measurements, taken from a real battery, in order to validate the model. After this, the magnetic field created by a complete battery pack is estimated and results are discussed.