Seismic Data from MSM21/4 to Knipovich Ridge on the western Svalbard margin

The seismic data were acquired north of the Knipovich Ridge on the western Svalbard margin during cruise MSM21/4. They were recorded using a Geometrics GeoEel streamer of either 120 channels (profiles p100-p208) or 88 channels (profiles p300-p805) with a group spacing of 1.56 m and a sampling rate of 2 kHz. A GI-Gun (2×1.7 l) with a main frequency of ~150 Hz was used as a source and operated at a shot interval of 6-8 s. Processing of profiles p100-p208 and p600-p805: Positions for each channel were calculated by backtracking along the profiles from the GI-Gun GPS positions. The shot gathers were analyzed for abnormal amplitudes below the seafloor reflection by comparing neighboring traces in different frequency bands within sliding time windows. To suppress surface-generated water noise, a tau-p filter was applied in the shot gather domain. Common mid-point (CMP) profiles were then generated through crooked-line binning with a CMP spacing of 1.5625 m. A zero-phase band-pass filter with corner frequencies of 60 Hz and 360 Hz was applied to the data. Based on regional velocity information from MCS data [Sarkar, 2012], an interpolated and extrapolated 3D interval velocity model was created below the digitized seafloor reflection of the high-resolution streamer data. This velocity model was used to apply a CMP stack and an amplitude-preserving Kirchhoff post-stack time migration. Processing of profiles p400-p500: Data were sampled at 0.5 ms and sorted into common midpoint (CMP) domain with a bin spacing of 5 m. Normal move out correction was carried out with a velocity of 1500 m s-1 and an Ormsby bandpass filter with corner frequencies at 40, 80, 600 and 1000 Hz was applied. The data were time migrated using the water velocity.

Table 1: Station data for the entire survey, including coordinates and description of BPBASE

During GANOVEX VI new gravity data were collected along an east-west profile in North Victoria Land south of the Drygalski Ice Tongue, extending 150 km across the Transantarctic Mountains, and comprising 21 data points. Thirty five additional data points were collected over a small area near Brimstone Peak, near the western end of the regional profile. The survey south of the Drygalski has been connected to northern gravity data (GANOVEX V) by a survey line of 12 points. All data have been terrain corrected, and are further constrained by satellite elevation (GPS) and radar ice-thickness measurements. A pronounced regional Bouguer gravity gradient decreasing to the west by approximately 3 mgal/km is superimposed over a coast-parallel belt of granitoid basement rock. West of this belt the local gravity fields become mote variable. Over Beta Peak (Ferrar dolerite) a 50 mgal spike is obser- ved. Within this area, the Ferrar sills are exposed at the surface. West of Brimstone Peak (Ferrar/Kirk patrick sequences), a smooth regional gradient appears to reassert itself. We interpret the initial gradient east (oceanward) of the break-in-slope to be representative of the crust/mantle boundary within the study area. We interpret the initial break-in-slope and the apparent flattening of the regional gradient to be an effect of the N-S trending zone of dense Ferrar sills and associated deep crusttil fractionate replacing less dense basement. We attribute the variability of the local field to be the product of sub-glacial density contrasts that cannot be removed. The regional gravity gradient of the profile is steeper than that observed to the north (Mt. Melbourne quadrangle) and shallower than that reported to the south (McMurdo Sound). The absolute values of the coastal points of origin south of the Drygalski and within the Mt. Melbourne quadrangle differ by 60 to 100 mgal. In addition, topographic relief within the regional transect area is subdued relative to the Transantarctic Mountains to the north and south. We speculate that the root structure of the Transantarctic Mountains undergoes a change somewhere between the Mt. Melbourne quadrangle and the region south of the Drygalski Ice Tongue.

Airport Taxi Planning: Lagrangian Decomposition

The airport taxi planning (TP) module is a decision tool intended to guide airport surface management operations. TP is defined by a flow network optimization model that represents flight ground movements and improves aircraft taxiing routes and schedules during periods of aircraft congestion. TP is not intended to operate as a stand‐alone tool for airport operations management: on the contrary, it must be used in conjunction with existing departing and arriving traffic tools and overseen by the taxi planner of the airport, also known as the aircraft ground controller. TP must be flexible in order to accommodate changing inputs while maintaining consistent routes and schedules already delivered from past executions. Within this dynamic environment, the execution time of TP may not exceed a few minutes. Classic methods for solving binary multi‐commodity flow networks with side constraints are not efficient enough; therefore, a Lagrangian decomposition methodology has been adapted to solve it. We demonstrate TP Lagrangian decomposition using actual data from the Madrid‐Barajas Airport

A GPS analysis for urban freight distribution

Daily life in urban centers has led to increasing and more demanding freight requirements. Manufacturers, retailers and other urban agents have thus tended towards more frequent and smaller deliveries, resulting in a growing use of light freight vehicles (<3.5 ton). This paper characterizes and analyzes urban freight distribution in order to generate new ways of understanding the phenomenon. Based on a case study of two different-sized Spanish cities using data from GPS, a vehicle observation survey and complementary driver's interviews, the authors propose a categorization of urban freight distribution. The results confirm GPS as a useful tool that allows the integration of dynamic traffic assignment data and diverse traffic operation patterns during different day periods, thereby improving delivery performance.

Teller: telemetría a partir de datos GPS

El avance y desarrollo de las nuevas tecnologías ha GPS sean cada vez más efectivos y precisos. En la actualidad son usados por miles de personas en una gran variedad de aplicaciones, siendo la competición una de ellas.Detrás del funcionamiento de estas pequeñas unidades juega un papel muy importante la telemetría, una tecnología que cada vez es más relevante en el mundo actual, y que gracias a las avances tecnológicos sus aplicaciones son cada vez mayores. En este Trabajo de Fin de Grado se diseñará Teller, un programa realizado en Erlang que mediante la telemetría y la tecnología actual realizará cálculos físicos de recorridos realizados en motocicleta, tales como velocidad o aceleración (tangencial y radial), además de clasificar los trayectos en tramos, dependiendo de si son curvas o rectas. Al mismo tiempo se realizará un estudio de precisión del dispositivo GPS, cotejando sus datos con los obtenidos por Teller. Por último, toda esta información se mostrará en un mapa para que el usuario pueda visualizarlo y que de esta forma sirva como herramienta de información y aprendizaje. The development of new technologies has contributed to the improvement of GPS devices, making them more effective and accurate. Nowadays they are used by thousands of people in a wide variety of applications like competitions. The technology that is behind the functionality of those devices is the telemetry, which is getting more and more important in the real world. In this thesis a new program called Teller will be designed. Made in Erlang, it will use telemetry so as to obtain new and valuable data from a motorcycle track. Examples of this type of data can be speed and acceleration (either tangential and radial) for instance. Besides, Teller will classify the track into segments, depending if it is a curve or a straight. At the same time a study will be carried out in order to know how accurate the GPS device is. This will be achieved by comparing the data retrieved by the device with the data calculated by Teller. Finally, all this information will be shown in a map, so the user can see information about his route in a visual way. xi

Variable Speed Limits. Review and development of an aggregate indicator based on floating car data.

Changing factors (mainly traffic intensity and weather conditions) affecting road conditions require a suitable optimal speed at any time. To solve this problem, variable speed limit systems (VSL) ? as opposed to fixed limits ? have been developed in recent decades. This term has included a number of speed management systems, most notably dynamic speed limits (DSL). In order to avoid the indiscriminate use of both terms in the literature, this paper proposes a simple classification and offers a review of some experiences, how their effects are evaluated and their results This study also presents a key indicator, which measures the speed homogeneity and a methodology to obtain the data based on floating cars and GPS technology applying it to a case study on a section of the M30 urban motorway in Madrid (Spain).

Generating descriptions that summarize geospatial and temporal data

Effective data summarization methods that use AI techniques can help humans understand large sets of data. In this paper, we describe a knowledge-based method for automatically generating summaries of geospatial and temporal data, i.e. data with geographical and temporal references. The method is useful for summarizing data streams, such as GPS traces and traffic information, that are becoming more prevalent with the increasing use of sensors in computing devices. The method presented here is an initial architecture for our ongoing research in this domain. In this paper we describe the data representations we have designed for our method, our implementations of components to perform data abstraction and natural language generation. We also discuss evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.

Teller: telemetría con GPS

En el campo del motociclismo y el automovilismo de competición se debe disponer de tecnología que ayude en la conducción y el aprendizaje del piloto. La telemetría juega un papel que es clave en este aspecto. Gracias a GPS precisos y que ofrecen una gran variedad de información, el piloto puede observar cualquier defecto en su conducción. Sin embargo, la mayor parte de los pilotos que se dedican al motociclismo y el automovilismo de manera amater no puede permitirse la compra de estos dispositivos. A lo largo de este documento se explica el trabajo realizado para crear Teller. Teller es una aplicación que recoge los datos de un GPS de bajo coste, genera información mediante cálculos físicos realizados con Erlang y visualiza dicha información para los pilotos que quierenmejorar. Con esta aplicación se pretende ofrecer una alternativa barata de telemetría sin necesidad de gastarse el dinero en GPS precisos pero demasiado caros. ---ABSTRACT---In the field of motorcycling racing and motorsport technology should be available to assist in driving and learning from the pilot. Telemetry plays a key role in this regard. Thanks to accurate GPS which offer various information, the pilot can see any fault in his driving. However, most of pilots who engage motorcycling racing and motorsport in the amater way can not afford to purchase these devices. Throughout this document the work done to create Teller is explained. Teller is an application that collects data from a low cost GPS, it generates information by physical calculations made in Erlang and it displays this information for pilots who want to improve. This application aims to provide a cheap alternative of telemetry without spending money on accurate but expensive GPS.

Using floating car data to analyse the effects of ITS measures and eco-driving

The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions models are used extensively to assess the potential effects of these measures. However, if the input and calibration data are not sufficiently detailed there is an inherent risk that the results may be inaccurate. This article presents the use of Floating Car Data to derive useful speed and acceleration values in the process of traffic model calibration as a means of ensuring more accurate results when simulating the effects of particular measures. The data acquired includes instantaneous GPS coordinates to track and select the itineraries, and speed and engine performance extracted directly from the on-board diagnostics system. Once the data is processed, the variations in several calibration parameters can be analyzed by comparing the base case model with the measure application scenarios. Depending on the measure, the results show changes of up to 6.4% in maximum speed values, and reductions of nearly 15% in acceleration and braking levels, especially when eco-driving is applied.