Simulation techniques for design of overhead conductor rail lines for speeds over 140 km/h

In overhead conductor rail lines, aluminium beams are usually mounted with support spacing between 8 and 12 meters, to limit the maximum vertical deflection in the center of the span. This small support spacing limits the use of overhead conductor rail to tunnels, therefore it has been used almost exclusively in metropolitan networks, with operation speeds below 110 km/h. Nevertheless, due to the lower cost of maintenance required for this electrification system, some railway administrations are beginning to install it in some tunnels on long-distance lines, requesting higher operation speeds [1]. Some examples are the Barcelona and Madrid suburban networks (Spain), and recent lines in Turkey and Malaysia. In order to adapt the design of the overhead conductor for higher speeds (V > 160 km/h), particular attention must be paid to the geometry of the conductor rail in critical zones as overlaps, crossings and, especially, transitions between conductor rail and conventional catenary, since the use of overhead conductor rail is limited to tunnels, as already mentioned. This paper describes simulation techniques developed in order to take into account these critical zones. Furthermore, some specific simulations results are presented that have been used to analyze and optimizes the geometry of this special zones to get a better current collection quality, in a real suburban network. This paper presents the work undertaken by the Railways Technology Research Centre (CITEF), having over 10 years of experience in railways research [1-4].

Multi-resolution model-based traffic sign detection and tracking

In this paper we propose an innovative approach to tackle the problem of traffic sign detection using a computer vision algorithm and taking into account real-time operation constraints, trying to establish intelligent strategies to simplify as much as possible the algorithm complexity and to speed up the process. Firstly, a set of candidates is generated according to a color segmentation stage, followed by a region analysis strategy, where spatial characteristic of previously detected objects are taken into account. Finally, temporal coherence is introduced by means of a tracking scheme, performed using a Kalman filter for each potential candidate. Taking into consideration time constraints, efficiency is achieved two-fold: on the one side, a multi-resolution strategy is adopted for segmentation, where global operation will be applied only to low-resolution images, increasing the resolution to the maximum only when a potential road sign is being tracked. On the other side, we take advantage of the expected spacing between traffic signs. Namely, the tracking of objects of interest allows to generate inhibition areas, which are those ones where no new traffic signs are expected to appear due to the existence of a TS in the neighborhood. The proposed solution has been tested with real sequences in both urban areas and highways, and proved to achieve higher computational efficiency, especially as a result of the multi-resolution approach.