Nationwide impact and vehicle to grid application of electric vehicles mobility using an activity based model

This paper describes the impact of electric mobility on the transmission grid in Flanders region (Belgium), using a micro-simulation activity based models. These models are used to provide temporal and spatial estimation of energy and power demanded by electric vehicles (EVs) in different mobility zones. The increment in the load demand due to electric mobility is added to the background load demand in these mobility areas and the effects over the transmission substations are analyzed. From this information, the total storage capacity per zone is evaluated and some strategies for EV aggregator are proposed, allowing the aggregator to fulfill bids on the electricity markets.

Sensitivity analysis to assess the influence of the inertial properties of railway vehicle bodies on the vehicle’s dynamic behaviour

A sensitivity analysis has been performed to assess the influence of the inertial properties of railway vehicles on their dynamic behaviour. To do this, 216 dynamic simulations were performed modifying, one at a time, the masses, moments of inertia and heights of the centre of gravity of the carbody, the bogie and the wheelset. Three values were assigned to each parameter, corresponding to the percentiles 10, 50 and 90 of a data set stored in a database of railway vehicles. After processing the results of these simulations, the analyzed parameters were sorted by increasing influence. It was also found which of these parameters could be estimated with a lesser degree of accuracy for future simulations without appreciably affecting the simulation results. In general terms, it was concluded that the most sensitive inertial properties are the mass and the vertical moment of inertia, and the least sensitive ones the longitudinal and lateral moments of inertia.

Assessment of the influence of the elastic properties of rail vehicle suspensions on safety, ride quality and track fatigue

A sensitivity analysis has been performed to assess the influence of the elastic properties of railway vehicle suspensions on the vehicle dynamic behaviour. To do this, 144 dynamic simulations were performed modifying, one at a time, the stiffness and damping coefficients, of the primary and secondary suspensions. Three values were assigned to each parameter, corresponding to the percentiles 10, 50 and 90 of a data set stored in a database of railway vehicles.After processing the results of these simulations, the analyzed parameters were sorted by increasing influence. It was also found which of these parameters could be estimated with a lesser degree of accuracy in future simulations without appreciably affecting the simulation results. In general terms, it was concluded that the highest influences were found for the longitudinal stiffness and the lateral stiffness of the primary suspension, and the lowest influences for the vertical stiffness and the vertical damping of the primary suspension, with the parameters of the secondary suspension showing intermediate influences between them.

Influence of the track quality and of the properties of the wheel rail rolling contact on vehicle dynamics

This work describes an analytical approach to determine what degree of accuracy is required in the definition of the rail vehicle models used for dynamic simulations. This way it would be possible to know in advance how the results of simulations may be altered due to the existence of errors in the creation of rolling stock models, whilst also identifying their critical parameters. This would make it possible to maximize the time available to enhance dynamic analysis and focus efforts on factors that are strictly necessary.In particular, the parameters related both to the track quality and to the rolling contact were considered in this study. With this aim, a sensitivity analysis was performed to assess their influence on the vehicle dynamic behaviour. To do this, 72 dynamic simulations were performed modifying, one at a time, the track quality, the wheel-rail friction coefficient and the equivalent conicity of both new and worn wheels. Three values were assigned to each parameter, and two wear states were considered for each type of wheel, one for new wheels and another one for reprofiled wheels.After processing the results of these simulations, it was concluded that all the parameters considered show very high influence, though the friction coefficient shows the highest influence. Therefore, it is recommended to undertake any future simulation job with measured track geometry and track irregularities, measured wheel profiles and normative values of wheel-rail friction coefficient.

HOG-Like gradient-based descriptor for visual vehicle detection

One of the main challenges for intelligent vehicles is the capability of detecting other vehicles in their environment, which constitute the main source of accidents. Specifically, many methods have been proposed in the literature for video-based vehicle detection. Most of them perform supervised classification using some appearance-related feature, in particular, symmetry has been extensively utilized. However, an in-depth analysis of the classification power of this feature is missing. As a first contribution of this paper, a thorough study of the classification performance of symmetry is presented within a Bayesian decision framework. This study reveals that the performance of symmetry-based classification is very limited. Therefore, as a second contribution, a new gradient-based descriptor is proposed for vehicle detection. This descriptor exploits the known rectangular structure of vehicle rears within a Histogram of Gradients (HOG)-based framework. Experiments show that the proposed descriptor outperforms largely symmetry as a feature for vehicle verification, achieving classification rates over 90%.

Region-dependent vehicle classification using PCA features

Video-based vehicle detection is the focus of increasing interest due to its potential towards collision avoidance. In particular, vehicle verification is especially challenging due to the enormous variability of vehicles in size, color, pose, etc. In this paper, a new approach based on supervised learning using Principal Component Analysis (PCA) is proposed that addresses the main limitations of existing methods. Namely, in contrast to classical approaches which train a single classifier regardless of the relative position of the candidate (thus ignoring valuable pose information), a region-dependent analysis is performed by considering four different areas. In addition, a study on the evolution of the classification performance according to the dimensionality of the principal subspace is carried out using PCA features within a SVM-based classification scheme. Indeed, the experiments performed on a publicly available database prove that PCA dimensionality requirements are region-dependent. Hence, in this work, the optimal configuration is adapted to each of them, rendering very good vehicle verification results.

On-road visual vehicle tracking using Markov chain Monte Carlo with metropolis sampling

In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The method exploits the removed perspective domain given by inverse perspective mapping (IPM) to define a fast and efficient likelihood model. Additionally, the method encompasses an interaction model using Markov Random Fields (MRF) that allows treatment of dependencies between the motions of targets. The proposed method is tested in highway sequences and compared to state-of-the-art methods for vehicle tracking, i.e., independent target tracking with Kalman filtering (KF) and joint tracking with particle filtering. The results showed fewer tracking failures using the proposed method.

On-line learning of a fuzzy controller for a precise vehicle cruise control system

Usually, vehicle applications require the use of artificial intelligent techniques to implement control methods, due to noise provided by sensors or the impossibility of full knowledge about dynamics of the vehicle (engine state, wheel pressure or occupiers weight). This work presents a method to on-line evolve a fuzzy controller for commanding vehicles? pedals at low speeds; in this scenario, the slightest alteration in the vehicle or road conditions can vary controller?s behavior in a non predictable way. The proposal adapts singletons positions in real time, and trapezoids used to codify the input variables are modified according with historical data. Experimentation in both simulated and real vehicles are provided to show how fast and precise the method is, even compared with a human driver or using different vehicles.

Diseño acústico y electroacústico de Waipahu Transit Center en Honolulú, Hawái

El objetivo de este Proyecto Fin de Grado es el diseño de megafonía y PAGA (Public Address /General Alarm) de la estación de tren Waipahu Transit Center en la ciudad de Honolulú, Hawái. Esta estación forma parte de una nueva línea de tren que está en proceso de construcción actualmente llamada Honolulu Rail Transit. Inicialmente la línea de tren constará de 21 estaciones, en las que prácticamente todas están diseñadas como pasos elevados usando como referencia las autopistas que cruzan la isla. Se tiene prevista su fecha de finalización en el año 2019, aunque las primeras estaciones se inaugurarán en 2017. Se trata en primer lugar un estudio acústico del recinto a sonorizar, eligiendo los equipos necesarios: conmutadores, altavoces, amplificadores, procesador, equipo de control y micrófonos. Este primer estudio sirve para obtener una aproximación de equipos necesarios, así como la posible situación de estos dentro de la estación. Tras esto, se procede a la simulación de la estación mediante el programa de simulación acústica y electroacústica EASE 4.4. Para ello, se diseña la estación en un modelo 3D, en el que cada superficie se asocia a su material correspondiente. Para facilitar el diseño y el cómputo de las simulaciones se divide la estación en 3 partes por separado. Cada una corresponde a un nivel de la estación: Ground level, el nivel inferior que contiene la entrada; Concourse Level, pasillo que comunica los dos andenes; y Platform Level, en el que realizarán las paradas los trenes. Una vez realizado el diseño se procede al posicionamiento de altavoces en los diferentes niveles de la estación. Debido al clima existente en la isla, el cual ronda los 20°C a lo largo de todo el año, no es necesaria la instalación de sistemas de aire acondicionado o calefacción, por lo que la estación no está totalmente cerrada. Esto supone un problema al realizar las simulaciones en EASE, ya que al tratarse de un recinto abierto se deberán hallar parámetros como el tiempo de reverberación o el volumen equivalente por otros medios. Para ello, se utilizará el método Ray Tracing, mediante el cual se halla el tiempo de reverberación por la respuesta al impulso de la sala; y a continuación se calcula un volumen equivalente del recinto mediante la fórmula de Eyring. Con estos datos, se puede proceder a calcular los parámetros necesarios: nivel de presión sonora directo, nivel de presión sonora total y STI (Speech Transmission Index). Para obtener este último será necesario ecualizar antes en cada uno de los niveles de la estación. Una vez hechas las simulaciones, se comprueba que el nivel de presión sonora y los valores de inteligibilidad son acordes con los requisitos dados por el cliente. Tras esto, se procede a realizar los bucles de altavoces y el cálculo de amplificadores necesarios. Se estudia la situación de los micrófonos, que servirán para poder variar la potencia emitida por los altavoces dependiendo del nivel de ruido en la estación. Una vez obtenidos todos los equipos necesarios en la estación, se hace el conexionado entre éstos, tanto de una forma simplificada en la que se pueden ver los bucles de altavoces en cada nivel de la estación, como de una forma más detallada en la que se muestran las conexiones entre cada equipo del rack. Finalmente, se realiza el etiquetado de los equipos y un presupuesto estimado con los costes del diseño del sistema PAGA. ABSTRACT. The aim of this Final Degree Project is the design of the PAGA (Public Address / General Alarm) system in the train station Waipahu Transit Center in the city of Honolulu, Hawaii. This station is part of a new rail line that is currently under construction, called Honolulu Rail Transit. Initially, the rail line will have 21 stations, in which almost all are designed elevated using the highways that cross the island as reference. At first, it is treated an acoustic study in the areas to cover, choosing the equipment needed: switches, loudspeakers, amplifiers, DPS, control station and microphones. This first study helps to obtain an approximation of the equipments needed, as well as their placement inside the station. Thereafter, it is proceeded to do the simulation of the station through the acoustics and electroacoustics simulation software EASE 4.4. In order to do that, it is made the 3D design of the station, in which each surface is associated with its material. In order to ease the design and calculation of the simulations, the station has been divided in 3 zones. Each one corresponds with one level of the station: Ground Level, the lower level that has the entrance; Concourse Level, a corridor that links the two platforms; and Platform Level, where the trains will stop. Once the design is made, it is proceeded to place the speakers in the different levels of the station. Due to the weather in the island, which is about 20°C throughout the year, it is not necessary the installation of air conditioning or heating systems, so the station is not totally closed. This cause a problem when making the simulations in EASE, as the project is open, and it will be necessary to calculate parameters like the reverberation time or the equivalent volume by other methods. In order to do that, it will be used the Ray Tracing method, by which the reverberation time is calculated by the impulse response; and then it is calculated the equivalent volume of the area with the Eyring equation. With this information, it can be proceeded to calculate the parameters needed: direct sound pressure level, total sound pressure level and STI (Speech Transmission Index). In order to obtain the STI, it will be needed to equalize before in each of the station’s levels. Once the simulations are done, it is checked that the sound pressure level and the intelligibility values agree with the requirements given by the client. After that, it is proceeded to perform the speaker’s loops and the calculation of the amplifiers needed. It is studied the placement of the microphones, which will help to vary the power emitted by the speakers depending on the background noise level in the station. Once obtained all the necessary equipment in the station, it is done the connection diagram, both a simplified diagram in which there can be seen the speaker’s loops in each level of the station, or a more detailed diagram in which it is shown the wiring between each equipment of the rack. At last, it is done the labeling of the equipments and an estimated budget with the expenses for the PAGA design.

A model for setting services on auxiliary bus lines under congestion

In this paper, a mathematical programming model and a heuristically derived solution is described to assist with the efficient planning of services for a set of auxiliary bus lines (a bus-bridging system) during disruptions of metro and rapid transit lines. The model can be considered static and takes into account the average flows of passengers over a given period of time (i.e., the peak morning traffic hour) Auxiliary bus services must accommodate very high demand levels, and the model presented is able to take into account the operation of a bus-bridging system under congested conditions. A general analysis of the congestion in public transportation lines is presented, and the results are applied to the design of a bus-bridging system. A nonlinear integer mathematical programming model and a suitable approximation of this model are then formulated. This approximated model can be solved by a heuristic procedure that has been shown to be computationally viable. The output of the model is as follows: (a) the number of bus units to assign to each of the candidate lines of the bus-bridging system; (b) the routes to be followed by users passengers of each of the origin–destination pairs; (c) the operational conditions of the components of the bus-bridging system, including the passenger load of each of the line segments, the degree of saturation of the bus stops relative to their bus input flows, the bus service times at bus stops and the passenger waiting times at bus stops. The model is able to take into account bounds with regard to the maximum number of passengers waiting at bus stops and the space available at bus stops for the queueing of bus units. This paper demonstrates the applicability of the model with two realistic test cases: a railway corridor in Madrid and a metro line in Barcelona Planificación de los servicios de lineas auxiliares de autobuses durante las incidencias de las redes de metro y cercanías. El modelo estudia el problema bajo condiciones de alta demanda y condiciones de congestión. El modelo no lineal resultante es resuelto mediante heurísticas que demuestran su utilidad. Se demuestran los resultados en dos corredores de las ciudades de Barcelona y Madrid.

Assessment of innovative measures implemented in European bus systems using key performance indicators

This paper reports the results of the assessment of a range of measures implemented in bus systems in five European cities to improve the use of public transport by increasing its attractiveness and enhancing its image in urban areas. This research was conducted as part of the EBSF project (European Bus System of the Future) from 2008 to 2012. New buses (prototypes), new vehicle and infrastructure technologies, and operational best practices were introduced, all of which were combined in a system approach. The measures were assessed using multicriteria analysis to simultaneously evaluate a certain number of criteria that need to be aggregated. Each criterion is measured by one or more key performance indicators (KPI) calculated in two scenarios (reference scenario, with no measure implemented; and project scenario, with the implementation of some measures), in order to evaluate the difference in the KPI performance between the reference and project scenario. The results indicate that the measures produce a greater benefit in issues related to bus system productivity and customer satisfaction, with the greatest impact on aspects of perceptions of comfort, cleanliness and quality of service, information to passengers and environmental issues. The study also reveals that the implementation of several measures has greater social utility than very specific and isolated measures.

The relationship between young people's transit use and their perceptions of equity concepts in transit service provision

This study investigates the effect of price and travel mode fairness and spatial equity in transit provision on the perceived transit service quality, willingness to pay, and habitual frequency of use. Based on the theory of planned behavior, we developed a web-based questionnaire for revealed preferences data collection. The survey was administered among young people in Copenhagen and Lisbon to explore the transit perceptions and use under different economic and transit provision conditions. The survey yielded 499 questionnaires, analyzed by means of structural equation models. Results show that higher perceived fairness relates positively to higher perceived quality of transit service and higher perceived ease of paying for transit use. Higher perceived spatial equity in service provision is associated with higher perceived service quality. Higher perceived service quality relates to higher perceived ease of payment, which links to higher frequency of transit use.

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.

Explaining light vehicle demand evolution in interurban toll roads: a dynamic panel data analysis in Spain

Tolls have increasingly become a common mechanism to fund road projects in recent decades. Therefore, improving knowledge of demand behavior constitutes a key aspect for stakeholders dealing with the management of toll roads. However, the literature concerning demand elasticity estimates for interurban toll roads is still limited due to their relatively scarce number in the international context. Furthermore, existing research has left some aspects to be investigated, among others, the choice of GDP as the most common socioeconomic variable to explain traffic growth over time. This paper intends to determine the variables that better explain the evolution of light vehicle demand in toll roads throughout the years. To that end, we establish a dynamic panel data methodology aimed at identifying the key socioeconomic variables explaining changes in light vehicle demand over time. The results show that, despite some usefulness, GDP does not constitute the most appropriate explanatory variable, while other parameters such as employment or GDP per capita lead to more stable and consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period, which constitutes a very interesting case on variations in toll road use, as road demand has experienced a significant decrease since the beginning of the economic crisis in 2008.

Real-time incidents detection in the highways of the future

Due to ever increasing transportation of people and goods, automatic traffic surveillance is becoming a key issue for both providing safety to road users and improving traffic control in an efficient way. In this paper, we propose a new system that, exploiting the capabilities that both computer vision and machine learning offer, is able to detect and track different types of real incidents on a highway. Specifically, it is able to accurately detect not only stopped vehicles, but also drivers and passengers leaving the stopped vehicle, and other pedestrians present in the roadway. Additionally, a theoretical approach for detecting vehicles which may leave the road in an unexpected way is also presented. The system works in real-time and it has been optimized for working outdoor, being thus appropriate for its deployment in a real-world environment like a highway. First experimental results on a dataset created with videos provided by two Spanish highway operators demonstrate the effectiveness of the proposed system and its robustness against noise and low-quality videos.