Using hybrid latent class model for city-HUBs´users behaviour analysis

Data from an attitudinal survey and stated preference ranking experiment conducted in two urban European interchanges (i.e. City-HUBs) in Madrid (Spain) and Thessaloniki (Greece) show that the importance that City-HUBs users attach to the intermodal infrastructure varies strongly as a function of their perceptions of time spent in the interchange (i.e.intermodal transfer and waiting time). A principal components analysis allocates respondents (i.e. city-HUB users) to two classes with substantially different perceptions of time saving when they make a transfer and of time using during their waiting time.

Modelling the Impact of Built Environment, Geographical Scales and Latent Constructs On Individual Travel Behaviour

La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.

Multiple solutions and numerical analysis to the dynamic and stationary models coupling a delayed energy balance model involving latent heat and discontinuous albedo with a deep ocean

We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge–Kutta total variation diminishing for time integration.

Podredumbre parda del melocotonero (Monilinia spp.) : detección, identificación de especies y contribución a la epidemiología de la enfermedad

Monilinia spp. (M. laxa, M. fructigena y M. fructicola) causa marchitez en brotes y flores, chancros en ramas y podredumbre de la fruta de hueso provocando pérdidas económicas importantes en años con climatología favorable para el desarrollo de la enfermedad, particularmente en variedades tardías de melocotonero y nectarino. En estos huéspedes en España, hasta el momento, la especie predominante es M. laxa y, en menor proporción, M. fructigena. La reciente introducción en Europa de la especie de cuarentena M. fructicola hace necesaria una detección e identificación rápida de cada una de las especies. Además, hay diversos aspectos de la etiología y epidemiología de la enfermedad que no se conocen en las condiciones de cultivo españolas. En un primer objetivo de esta Tesis se ha abordado la detección e identificación de las especies de Monilinia spp. causantes de podredumbre parda. El estudio de las bases epidemiológicas para el control de la enfermedad constituye el fin del segundo objetivo. Para la detección del género Monilinia en material vegetal por PCR, diferenciándolo de otros hongos presentes en la superficie del melocotonero, se diseñaron una pareja de cebadores siguiendo un análisis del ADN ribosomal. La discriminación entre especies de Monilinia se consiguió utilizando marcadores SCAR (región amplificada de secuencia caracterizada), obtenidos después de un estudio de marcadores polimórficos de ADN amplificados al azar (RAPDs). También fue diseñado un control interno de amplificación (CI) basado en la utilización de un plásmido con secuencias de los cebadores diferenciadores del género, para ser utilizado en el protocolo de diagnóstico de la podredumbre parda con el fin de reconocer falsos negativos debidos a la inhibición de PCR por componentes celulares del material vegetal. Se disponía de un kit comercial que permitía distinguir Monilinia de otros géneros y M. fructicola del resto de especies mediante anticuerpos monoclonales utilizando la técnica DAS-ELISA. En esta Tesis se probaron diferentes fuentes de material como micelio ó conidias procedentes de cultivos en APD, o el micelio de la superficie de frutas o de momias frescas, como formas de antígeno. Los resultados obtenidos con ELISA se compararon con la identificación por métodos morfológico-culturales y por PCR con los cebadores desarrollados en esta Tesis. Los resultados demostraron la posibilidad de una detección temprana en frutas frescas por este método, realzando las posibilidades de una diagnosis temprana para una prevención más eficaz de M. fructicola en fruta de hueso. El estudio epidemiológico de la enfermedad comenzó con la determinación de las principales fuentes de inóculo primario y su importancia relativa en melocotoneros y nectarinos del valle del Ebro. Para ello se muestrearon 9 huertos durante los años 2003 a 2005 recogiendo todas las momias, frutos abortados, gomas, chancros, y brotes necróticos en los árboles. También se recogieron brotes aparentemente sanos y muestras de material vegetal situados en el suelo. En estas muestras se determinó la presencia de Monilinia spp. Los resultados mostraron que la fuente principal de inóculo son las momias que se quedan en los árboles en las que la supervivencia del hongo tras el invierno es muy alta. También son fuentes de inóculo las momias del suelo y los brotes necróticos. De aquí se deriva que una recomendación importante para los agricultores es que deben eliminar este material de los huertos. Un aspecto no estudiado en melocotonero o nectarino en España es la posible relación que puede darse entre la incidencia de infecciones latentes en los frutos inmaduros a lo largo del cultivo y la incidencia de podredumbre en los frutos en el momento de la recolección y en postcosecha. Esta relación se había observado previamente en otros frutales de hueso infectados con M. fructicola en diversos países del mundo. Para estudiar esta relación se realizaron ensayos en cinco huertos comerciales de melocotonero y nectarino situados en el Valle del Ebro en cuatro estados fenológicos durante los años 2000-2002. No se observaron infecciones latentes en botón rosa, dándose la máxima incidencia en precosecha, aunque en algunos huertos se daba otro pico en el endurecimiento del embrión. La especie prevaleciente fue M. laxa. Se obtuvo una correlación positiva significativa entre la incidencia de infecciones latentes y la incidencia de podredumbre en postcosecha. Se desarrolló también un modelo de predicción de las infecciones latentes en función de la temperatura (T) y el periodo de humectación (W). Este modelo indicaba que T y W explicaban el 83% de la variación en la incidencia de infecciones latentes causadas por Monilinia spp. Por debajo de 8ºC no se predecían latentes, necesitándose más de 22h de W para predecir la ocurrencia de latentes con T = 8ºC, mientras que solo se necesitaban 5h de W a 25ºC. Se hicieron también ensayos en condiciones controladas para determinar la relación entre la incidencia de las infecciones latentes, las condiciones ambientales (T y W), la concentración de inóculo del patógeno (I) y el estado de desarrollo del huésped (S) y para validar el modelo de predicción desarrollado con los experimentos de campo. Estos ensayos se llevaron cabo con flores y frutos de nectarino procedentes de un huerto comercial en seis estados fenológicos en los años 2004 y 2005, demostrándose que la incidencia de podredumbre en postcosecha y de infecciones latentes estaba afectada por T, W, I y S. En los frutos se producían infecciones latentes cuando la T no era adecuada para el desarrollo de podredumbre. Una vez desarrollado el embrión eran necesarias más de 4-5h de W al día y un inóculo superior a 104 conidias ml-1 para que se desarrollase o podredumbre o infección latente. La ecuación del modelo obtenido con los datos de campo era capaz de predecir los datos observados en estos experimentos. Para evaluar el efecto del inóculo de Monilinia spp. en la incidencia de infecciones latentes y de podredumbre de frutos en postcosecha se hicieron 11 experimentos en huertos comerciales de melocotonero y nectarino del Valle del Ebro durante 2002 a 2005. Se observó una correlación positiva entre los números de conidias de Monilinia spp. en la superficie de los frutos y la incidencia de infecciones latentes De los estudios anteriores se deducen otras dos recomendaciones importantes para los agricultores: las estrategias de control deben tener en cuenta las infecciones latentes y estimar el riesgo potencial de las mismas basándose en la T y W. Deben tener también en cuenta la concentración de esporas de Monilinia spp. en la superficie de los frutos para disminuir el riesgo de podredumbre parda. El conocimiento de la estructura poblacional de los patógenos sienta las bases para establecer métodos más eficaces de manejo de las enfermedades. Por ello en esta Tesis se ha estudiado el grado de diversidad genética entre distintas poblaciones de M. laxa en diferentes localidades españolas utilizando 144 marcadores RAPDs (59 polimórficos y 85 monomórficos) y 21 aislados. El análisis de la estructura de la población reveló que la diversidad genética dentro de las subpoblaciones (huertos) (HS) representaba el 97% de la diversidad genética (HT), mientras que la diversidad genética entre subpoblaciones (DST) sólo representaba un 3% del total de esta diversidad. La magnitud relativa de la diferenciación génica entre subpoblaciones (GST) alcanzaba 0,032 y el número estimado de migrantes por generación (Nm) fue de 15,1. Los resultados obtenidos en los dendrogramas estaban de acuerdo con el análisis de diversidad génica. Las agrupaciones obtenidas eran independientes del huerto de procedencia, año o huésped. En la Tesis se discute la importancia relativa de las diferentes fuentes evolutivas en las poblaciones de M. laxa. Finalmente se realizó un muestreo en distintos huertos de melocotonero y nectarino del Valle del Ebro para determinar la existencia o no de aislados resistentes a los fungicidas del grupo de los benzimidazoles y las dicarboximidas, fungicidas utilizados habitualmente para el control de la podredumbre parda y con alto riesgo de desarrollar resistencia en las poblaciones patógenas. El análisis de 114 aislados de M. laxa con los fungicidas Benomilo (bencimidazol) (1Bg m.a ml-1), e Iprodiona (dicarboximida) (5Bg m.a ml-1), mostró que ninguno era resistente en las dosis ensayadas. Monilinia spp. (M. laxa, M. fructigena and M. fructicola) cause bud and flower wilt, canker in branches and stone fruit rot giving rise important economic losses in years with appropriate environmental conditions, it is particularly important in late varieties of peach and nectarine. Right now, M. laxa is the major species for peach and nectarine in Spain followed by M. fructigena, in a smaller proportion. The recent introduction of the quarantine organism M. fructicola in Europe makes detection and identification of each one of the species necessary. In addition, there are different aspects of disease etiology and epidemiology that are not well known in Spain conditions. The first goal of this Thesis was the detection and identification of Monilinia spp. causing brown rot. Study of the epidemiology basis for disease control was the second objective. A pair of primers for PCR detection was designed based on the ribosomal DNA sequence in order to detect Monilinia spp. in plant material and to discriminate it from other fungi colonizing peach tree surface. Discrimination among Monilinia spp. was successful by SCAR markers (Sequence Characterized Amplified Region), obtained after a random amplified polymorphic DNA markers (RAPDs) study. An internal control for the PCR (CI) based on the use of a mimic plasmid designed on the primers specific for Monilinia was constructed to be used in diagnosis protocol for brown rot in order to avoid false negatives due to the inhibition of PCR as consequence of remained plant material. A commercial kit based on DAS-ELISA and monoclonals antibodies was successfully tested to distinguish Monilinia from other fungus genera and M. fructicola from other Monilinia species. Different materials such as micelium or conidias from APD cultures, or micelium from fresh fruit surfaces or mummies were tested in this Thesis, as antigens. Results obtained by ELISA were compared to classical identification by morphologic methods and PCR with the primers developed in this Thesis. Results demonstrated the possibility of an early detection in fresh fruits by this method for a more effective prevention of M. fructicola in stone fruit. The epidemiology study of the disease started with the determination of the main sources of primary inoculum and its relative importance in peach trees and nectarines in the Ebro valley. Nine orchards were evaluated during years 2003 to 2005 collecting all mummies, aborted fruits, rubbers, cankers, and necrotic buds from the trees. Apparently healthy buds and plant material located in the ground were also collected. In these samples presence of Monilinia spp. was determined. Results showed that the main inoculum sources are mummies that stay in the trees and where fungus survival after the winter is very high. Mummies on the ground and the necrotics buds are also sources of inoculum. As consequence of this an important recommendation for the growers is the removal of this material of the orchards. An important issue not well studied in peach or nectarine in Spain is the possible relationship between the incidence of latent infections in the immature fruits and the incidence of fruit rot at harvesting and postharvesting. This relationship had been previously shown in other stone fruit trees infected with M. fructicola in different countries over the world. In order to study this relationship experiments were run in five commercial peach and nectarine orchards located in the Ebro Valley in four phenologic states from 2000 to 2002. Latent infections were not observed in pink button, the maxima incidence arise in preharvest, although in some orchards another increase occurred in the embryo hardening. The most prevalence species was M. laxa. A significant positive correlation between the incidence of latent infections and the incidence of rot in postharvest was obtained. A prediction model of the latent infections based on the temperature (T) and the wetness duration (W) was also developed. This model showed that T and W explained 83% of the variation in latent infection incidence caused by Monilinia spp. Below 8ºC latent infection was not predicted, more than 22h of W with T = 8ºC were needed to predict latent infection occurrence of, whereas at 25ºC just 5h of W were enough. Tests under controlled conditions were also made to determine the relationship among latent infections incidence, environmental conditions (T and W), inoculum concentration of the pathogen (I) and development state of the host (S) to validate the prediction model developed on the field experiments. These tests were made with flowers and fruits of nectarine coming from a commercial orchard, in six phenologic states in 2004 and 2005, showing that incidence of rot in postharvest and latent infections were affected by T, W, I and S. In fruits latent infections took place when the T was not suitable for rot development. Once developed the embryo, more than 4-5h of W per day and higher inoculums (104 conidia ml-1) were necessary for rot or latent infection development. The equation of the model obtained with the field data was able to predict the data observed in these experiments. In order to evaluate the effect of inoculum of Monilinia spp. in the incidence of latent infections and of rot of fruits in postharvest, 11 experiments in commercial orchards of peach and nectarine of the Ebro Valley were performed from 2002 to 2005. A positive correlation between the conidial numbers of Monilinia spp. in the surface of the fruits and the incidence of latent infections was observed. Based on those studies other two important recommendations for the agriculturists are deduced: control strategies must consider the latent infections and potential risk based on the T and W. Spores concentration of Monilinia spp. in the surface of fruits must be also taken in concern to reduce the brown rot risk. The knowledge of the population structure of the pathogens determines the bases to establish more effective methods of diseases handling. For that reason in this Thesis the degree of genetic diversity among different M. laxa populations has been studied in different Spanish locations using 144 RAPDs markers (59 polymorphic and 85 monomorphics) on 21 fungal isolates. The analysis of the structure of the population revealed that the genetic diversity within the subpopulations (orchards) (HS) represented 97% of the genetic diversity (HT), whereas the genetic diversity between subpopulations (DST) only represented a 3% of the total of this diversity. The relative magnitude of the genic differentiation between subpopulations (GST) reached 0.032 and the considered number of migrantes by generation (Nm) was of 15.1. The results obtained in dendrograms were in agreement with the analysis of genic diversity. The obtained groupings were independent of the orchard of origin, year or host. In the Thesis the relative importance of the different evolutionary sources in the populations from M. laxa is discussed. Finally a sampling of resistant isolates in different orchards from peach and nectarine of Ebro Valley was made to determine the existence of fungicide resistance of the group of benzimidazoles and the dicarboximidas, fungicides used habitually for the control of rot brown and with high risk of resistance developing in the pathogenic populations. The analysis of 114 isolated ones of M. laxa with the fungicides Benomilo (bencimidazol) (1Bg m.a ml-1), and Iprodiona (dicarboximida) (5Bg m.a ml-1), showed no resistant in the doses evaluated.

Hybrid choice model for propensity to travel and tour complexity

During the last years cities around the world have invested important quantities of money in measures for reducing congestion and car-trips. Investments which are nothing but potential solutions for the well-known urban sprawl phenomenon, also called the “development trap” that leads to further congestion and a higher proportion of our time spent in slow moving cars. Over the path of this searching for solutions, the complex relationship between urban environment and travel behaviour has been studied in a number of cases. The main question on discussion is, how to encourage multi-stop tours? Thus, the objective of this paper is to verify whether unobserved factors influence tour complexity. For this purpose, we use a data-base from a survey conducted in 2006-2007 in Madrid, a suitable case study for analyzing urban sprawl due to new urban developments and substantial changes in mobility patterns in the last years. A total of 943 individuals were interviewed from 3 selected neighbourhoods (CBD, urban and suburban). We study the effect of unobserved factors on trip frequency. This paper present the estimation of an hybrid model where the latent variable is called propensity to travel and the discrete choice model is composed by 5 alternatives of tour type. The results show that characteristics of the neighbourhoods in Madrid are important to explain trip frequency. The influence of land use variables on trip generation is clear and in particular the presence of commercial retails. Through estimation of elasticities and forecasting we determine to what extent land-use policy measures modify travel demand. Comparing aggregate elasticities with percentage variations, it can be seen that percentage variations could lead to inconsistent results. The result shows that hybrid models better explain travel behavior than traditional discrete choice models.

Latent hardening size effect in small-scale plasticity

We aim at understanding the multislip behaviour of metals subject to irreversible deformations at small-scales. By focusing on the simple shear of a constrained single-crystal strip, we show that discrete Dislocation Dynamics (DD) simulations predict a strong latent hardening size effect, with smaller being stronger in the range [1.5 µm, 6 µm] for the strip height. We attempt to represent the DD pseudo-experimental results by developing a flow theory of Strain Gradient Crystal Plasticity (SGCP), involving both energetic and dissipative higher-order terms and, as a main novelty, a strain gradient extension of the conventional latent hardening. In order to discuss the capability of the SGCP theory proposed, we implement it into a Finite Element (FE) code and set its material parameters on the basis of the DD results. The SGCP FE code is specifically developed for the boundary value problem under study so that we can implement a fully implicit (Backward Euler) consistent algorithm. Special emphasis is placed on the discussion of the role of the material length scales involved in the SGCP model, from both the mechanical and numerical points of view.

Latent hardening size effect in small-scale plasticity

We aim at understanding the multislip behaviour of metals subject to irreversible deformations at small-scales. By focusing on the simple shear of a constrained single-crystal strip, we show that discrete Dislocation Dynamics (DD) simulations predict a strong latent hardening size effect, with smaller being stronger in the range [1.5 µm, 6 µm] for the strip height. We attempt to represent the DD pseudo-experimental results by developing a flow theory of Strain Gradient Crystal Plasticity (SGCP), involving both energetic and dissipative higher-order terms and, as a main novelty, a strain gradient extension of the conventional latent hardening. In order to discuss the capability of the SGCP theory proposed, we implement it into a Finite Element (FE) code and set its material parameters on the basis of the DD results. The SGCP FE code is specifically developed for the boundary value problem under study so that we can implement a fully implicit (Backward Euler) consistent algorithm. Special emphasis is placed on the discussion of the role of the material length scales involved in the SGCP model, from both the mechanical and numerical points of view.

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.

A general framework to testing the effect of transport policy measures to achieve a modal shift: a sequental hybrid model

In order to achieve to minimize car-based trips, transport planners have been particularly interested in understanding the factors that explain modal choices. In the transport modelling literature there has been an increasing awareness that socioeconomic attributes and quantitative variables are not sufficient to characterize travelers and forecast their travel behavior. Recent studies have also recognized that users? social interactions and land use patterns influence travel behavior, especially when changes to transport systems are introduced, but links between international and Spanish perspectives are rarely deal. In this paper, factorial and path analyses through a Multiple-Indicator Multiple-Cause (MIMIC) model are used to understand and describe the relationship between the different psychological and environmental constructs with social influence and socioeconomic variables. The MIMIC model generates Latent Variables (LVs) to be incorporated sequentially into Discrete Choice Models (DCM) where the levels of service and cost attributes of travel modes are also included directly to measure the effect of the transport policies that have been introduced in Madrid during the last three years in the context of the economic crisis. The data used for this paper are collected from a two panel smartphone-based survey (n=255 and 190 respondents, respectively) of Madrid.

Linear latent force models using Gaussian Processes

Purely data-driven approaches for machine learning present difficulties when data are scarce relative to the complexity of the model or when the model is forced to extrapolate. On the other hand, purely mechanistic approaches need to identify and specify all the interactions in the problem at hand (which may not be feasible) and still leave the issue of how to parameterize the system. In this paper, we present a hybrid approach using Gaussian processes and differential equations to combine data-driven modeling with a physical model of the system. We show how different, physically inspired, kernel functions can be developed through sensible, simple, mechanistic assumptions about the underlying system. The versatility of our approach is illustrated with three case studies from motion capture, computational biology, and geostatistics.