Exploring the potential of phone call data to characterize the relationship between social network and travel behavior

[EN] Social network contacts have significant influence on individual travel behavior. However, transport models rarely consider social interaction. One of the reasons is the difficulty to properly model social influence based on the limited data available. Non-conventional, passively collected data sources, such as Twitter, Facebook or mobile phones, provide large amounts of data containing both social interaction and spatiotemporal information. The analysis of such data opens an opportunity to better understand the influence of social networks on travel behavior. The main objective of this paper is to examine the relationship between travel behavior and social networks using mobile phone data. A huge dataset containing billions of registers has been used for this study. The paper analyzes the nature of co-location events and frequent locations shared by social network contacts, aiming not only to provide understanding on why users share certain locations, but also to quantify the degree in which the different types of locations are shared. Locations have been classified as frequent (home, work and other) and non-frequent. A novel approach to identify co-location events based on the intersection of users' mobility models has been proposed. Results show that other locations different from home and work are frequently associated to social interaction. Additionally, the importance of non-frequent locations in co-location events is shown. Finally, the potential application of the data analysis results to improve activity-based transport models and assess transport policies is discussed.The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no 318367 (EUNOIA project) and no 611307 (INSIGHT project). The work of ML has been funded under the PD/004/2013 project, from the Conselleria de Educacion, Cultura y Universidades of the Government of the Balearic Islands and from the European Social Fund through the Balearic Islands ESF operational program for 2013-2017.Picornell Tronch, M.; Ruiz Sánchez, T.; Lenormand, M.; Ramasco, JJ.; Dubernet, T.; Frías-Martínez, E. (2015). Exploring the potential of phone call data to characterize the relationship between social network and travel behavior. Transportation. 42(4):647-668. https://doi.org/10.1007/s11116-015-9594-1S647668424Ahas, R., Aasa, A., Silm, S., Tiru, M.: Daily rhythms of suburban commuters’ movements in the tallinn metropolitan area: case study with mobile positioning data. Transp. Res. 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TABSAOND: A technique for developing agent-based simulation apps and online tools with nondeterministic decisions

Agent-based simulators (ABSs) have successfully allowed practitioners to estimate the outcomes of certain input circumstances in several domains. Although some techniques and processes provide hints about the construction of these systems, some aspects have not been discussed yet in the literature. In this context, the current approach presents a technique for developing ABSs. Its focus is to guide practitioners in designing and implementing the decision-making processes of agents in nondeterministic scenarios. As an additional technological innovation, the ABSs are deployed as both mobile apps and online tools. This work illustrates the current approach with two case studies in the fields of (a) health and welfare and (b) tourism. These case studies have also been developed with the most similar technique from the literature for comparing both techniques. The presented technique improved the simulated outcomes in terms of their similarity with the real ones. The obtained ABSs were more efficient and reliable for large amounts of agents (e.g. 10,000 – 400,000 agents). The development time was lower. Both the framework and the implementation of a case study are freely distributed as open-source to facilitate the reproducibility of the experiments and to assist practitioners in applying the current approach

Modeling the Evolution of Agent Capabilities and Specialization

A social system is a patterned network of interrelationships that exist between individuals, institutions, and groups forming a coherent whole. Understanding the varying system outcomes for different decision-making processes selected under varying environment constraints in advance will aid in the realization the of best decision towards an effective outcome. One of the ways to increase system productivity is ‘Agent Specialization’. Also, the agents (individuals) who operate as generalists are most vulnerable to being replaced. Therefore, there is a need to focus on agent specialization to enhance the ability of an agent along with the evolution of an agent. Multi-Agent Based Simulation, a subfield of distributed AI, provides a technique to naturally describe a social system. To help improve decision-making intricacies of the agents to evolve and specialize, there is an increasing need to formulate an enhanced model of MABS. This thesis proposes a novel framework that exploits the benefits of social networks providing a decision support system for agent (individual) specialization by integrating the concept of ‘Positive Social Influence’ exerted by experts in the system. Consequently, the proposed framework assists the growth of agents by enabling the evolution of agent capabilities with the identification of suitable producer-agents using an evolutionary component (cultural algorithms). Enabling agent specialization and assisting the ability of the agents through capability evolution is anticipated to increase the productivity of the system. Evaluation of results shows the successful evolution of agent capabilities with the identification of suitable producer-agents in an optimized aspect (reduced operational cost and reduced distance cost) in comparison with exhaustive search, random search, and genetic algorithms and the improved degree of specialization of agents (increased dol values with a minimum of 3% increase to a maximum of 16.7% increase in comparison with standard genetic threshold model for varying agents and task number) in a given dynamic environment

Modelagem comportamental da escolha do modo de viagem sob influência da interação social

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2019.Pauta recorrente na pesquisa internacional, a temática que relaciona comportamento de viagem e rede de interação social de um indivíduo é o escopo deste trabalho. A incorporação da dimenção social na pesquisa em comportamento de viagem permite verificar como o meio social influencia as escolhas de viagens que um indivíduo realiza e adiciona uma nova perspectiva junto a aspectos tradicionalmente considerados, como as características do ambiente urbano e o contexto pessoal do indivíduo. Dessa forma, busca-se definir um modelo comportamental para verificar a existência da influência social na escolha do modo de viagem no contexto brasileiro. Para alcance de tal objetivo, realizou-se uma pesquisa no campus Darcy Ribeiro da Universidade de Brasília, com a aplicação de um método de três etapas: i) delimitação da pesquisa; ii) coleta de dados, a partir da definição das variáveis, da estruturação do questionário e da definição da forma de coleta de dados sociais, feita pela abordagem egocentrada; iii) análise dos dados por meio da sua caracterização e análise exploratória, da definição de hipóteses de modelagem e da modelagem dos dados através de um modelo logit multinomial. Verificou-se, como resultado, a existência da influência social por conformidade na escolha do modo de viagem para a universidade quando se consideram os modos sustentáveis (bicicleta e caminhada) e a carona. A probabilidade de um indivíduo usar um modo sustentável em relação ao carro é 76% maior quando a quantidade de contatos sociais que utilizam modos sustentáveis aumenta em 10%. A probabilidade de uso da carona em relação ao carro aumenta 27% junto ao aumento de 10% no total de contatos sociais adeptos à carona. Foi possível verificar ainda que, além da influência social, o uso do transporte público, da carona e de modos sustentáveis, em detrimento do automóvel, tem probabilidades maiores quando são considerados indivíduos jovens, de domicílios com menores taxas de motorização e localizados em áreas urbanas mais adensadas. A consideração da influência social permite a percepção mais abrangente dos fatores relevantes no processo decisório individual, sendo referência para a formulação de políticas públicas de mobilidade, com destaque para aquelas que buscam promover alternativas sustentáveis e compartilhadas.This dissertation comprehends the travel behavior and social network interaction theme, which has been an international research interest. The incorporation of the social view into travel behavior research allows us to establish a method of identifying and analyzing the social influence on travel choices, thus, adding a new perspective combined with traditional features such as built environment and personal characteristics. This research aims to define a behavioral model to verify whether there is a social influence on the travel mode choices in the Brazilian context. To achieve this goal, the research was carried out on the Darcy Ribeiro campus of the University of Brasília taking into account a three steps method: a) research delimitation; b) data collection, that consists of variables definition, a survey design, and a definition of social data collection, which was made by the egocentric approach; c) data analysis with the characterization and exploratory analysis, the definition of the hypotheses and a data modeling through a multinomial logit model. The results of the research reveal that there is social influence in the travel mode choice among students commuting to the University of Brasília, especially when considering sustainable modes (biking and walking) and carpooling. The odds of an ego using a sustainable mode are 76% higher if there is an increment of 10% in the proportion of alters that also use sustainable modes. The odds of an ego to carpool are 27% higher when their alter carpooling proportion increases 10%. Taking into account social influence, the odds of using public transportation, carpooling, and sustainable mode are higher when an ego is young, belongs to a household with lower motorization rates, and lives in denser neighborhood. The knowledge of social influence allows better perception of relevant factors of the decision-making process. Urban mobility policies must consider this perspective, especially those policies that aim to promote sustainable and shared travel modes as alternatives to great automobile use

METODOLOGÍA PARA LA EXTRACCIÓN DE PATRONES DE MOVILIDAD URBANA MEDIANTE EL ANÁLISIS DE REGISTROS DE ACTIVIDAD TELEFÓNICA (CALL DETAIL RECORD)

In the last century, Europe has seen a strong migration from rural to urban areas. Urban mobility is key to the economic and social development of cities, but at the same time it generates a significant number of negative effects such as congestion or air pollution. Understanding urban mobility patterns is essential to evaluate which are the most appropriate policies and measures to achieve sustainable urban development. Most of the empirical studies on urban mobility are based on surveys, since they provide detailed information about population mobility patterns and a large amount of socio-demographic information. However, surveys have several practical limitations (Ortúzar & Willumsen, 2011) such as their high costs and long lead times. The pervasive used of mobile devices opens the opportunity of gather large amounts of anonymised, passively-collected geolocation data overcoming some of the limitations of traditional surveys. Mobile phone data are probably one of the best data sources from which extract population mobility patterns at city scale because of their advantages (large samples, wide spatial coverage, low data collection costs, etc.). The main objective of this research is to contribute to the recent advances in the analysis of mobile phone data by developing and validating a new methodology to extract population activity and mobility patterns in urban areas. The methodology developed present several improvements with respect to previous studies, such as the identification of frequent locations different from home and work, better trip time estimations, sample selection and expansion procedures and improvements on population density estimations. The methodology developed has been tested in three different case studies: (1) estimation of mobility statistics and origin-destination matrices, (2) analysis of the relationship between social network and travel behaviour and (3) evaluation of population exposure to air pollution taking into account population activity and mobility patterns. The results show the potential of mobile phone data to extract information about mobility patterns in urban areas, to better understand the relationship between social network and travel behaviour and to improve population exposure assessment to air pollutants. Despite the potential of mobile phone data to provide rich information about activity and mobility patterns, a number of drawbacks and limitations shall be taken into account. Limitations are mainly related to the spatio-temporal resolution of the data and the limited socio-demographic information available. The results of this research are of great interest for transport planning studies, social network and transport modelling, and population exposure assessments.En el último siglo, Europa ha vivido una fuerte migración del ámbito rural al urbano. La movilidad urbana es fundamental para el desarrollo económico y social de las ciudades pero al mismo tiempo conlleva a una serie de importantes efectos negativos, tales como la congestión o la contaminación del aire. El entendimiento de los patrones de movilidad urbana de los ciudadanos es esencial para que los gestores puedan evaluar cuáles son las políticas y medidas más adecuadas para conseguir un desarrollo urbano sostenible. La mayoría de los estudios empíricos sobre movilidad urbana se apoyan en encuestas. Sin embargo, las encuestas presentan una serie de limitaciones prácticas importantes (Ortúzar & Willumsen, 2011) tales como sus elevados costes económicos o sus largos plazos de ejecución. El uso generalizado de dispositivos móviles por parte de la población proporciona la posibilidad de recoger de manera anónima y pasiva una gran cantidad de información espacio-temporal de una gran muestra de usuarios, superando algunas de las limitaciones de los actuales métodos de recogida de información. En concreto, los datos de la red de telefonía móvil presentan una serie de ventajas que los posicionan como una de las mejores fuentes de datos para el estudio de la movilidad general de grandes núcleos de población (bajos costes de extracción de los datos, gran tamaño de muestra, amplía cobertura espacial, etc.). El objetivo principal de esta investigación es contribuir a los recientes avances en el campo del análisis de los datos de telefonía móvil mediante el desarrollo y validación de una metodología que permita extraer información de patrones de actividad y movilidad de la población en ámbitos urbanos. La metodología desarrollada presenta una serie de mejoras relevantes con respecto a estudios previos, como la estimación de localizaciones frecuentes distintas de casa y trabajo, la mejora en la estimación de la hora del viaje, procedimientos para la selección y expansión de la muestra o la mejora en la estimación del número de personas en un área específica a partir de los patrones de actividad y movilidad de las mismas. Esta metodología ha sido aplicada en tres casos de uso para: (1) la obtención de estadísticas básicas de movilidad y matrices origen-destino en ámbitos urbanos, (2) el análisis de la influencia de la red social en la movilidad y (3) el estudio de la exposición de la población a la contaminación. Los resultados obtenidos demuestran el potencial de los datos de telefonía móvil para extraer información sobre patrones de movilidad en ámbitos urbanos, entender mejor la influencia de la red social en la movilidad y mejorar las estimaciones de exposición de la población a la contaminación. A pesar de las ventajas que proporcionan los datos de telefonía móvil, también se han observado limitaciones relevantes en los distintos estudios realizados, derivadas principalmente de la resolución espacio-temporal de los datos y de la limitada información socio-demográfica disponible. Los resultados de esta investigación son de gran relevancia para estudios de planificación y gestión del transporte, para el desarrollo de nuevos modelos de transporte que tengan en consideración la influencia de la red social en la movilidad y en estudios de evaluación de la exposición de la población a la contaminación.En l'últim segle, Europa ha viscut una forta migració de l'àmbit rural a l'urbà. La mobilitat urbana és fonamental per al desenvolupament econòmic i social de les ciutats però al mateix temps comporta a una sèrie d'importants efectes negatius, com ara la congestió o la contaminació de l'aire. L'entesa dels patrons de mobilitat urbana dels ciutadans és essencial perquè els gestors puguin avaluar quines són les polítiques i mesures més adequades per aconseguir un desenvolupament urbà sostenible. La majoria dels estudis empírics sobre mobilitat urbana es recolzen en enquestes. No obstant això, les enquestes presenten una sèrie de limitacions pràctiques importants (Ortúzar & Willumsen, 2011) com ara els seus elevats costos econòmics o els seus llargs terminis d'execució. L'ús generalitzat de dispositius mòbils per part de la població proporciona la possibilitat de recollir de manera anònima i passiva una gran quantitat d'informació espai-temporal d'una gran mostra d'usuaris, superant algunes de les limitacions dels actuals mètodes de recollida d'informació. En concret, les dades de la xarxa de telefonia mòbil presenten una sèrie d'avantatges que els posicionen com una de les millors fonts de dades per a l'estudi de la mobilitat general de grans nuclis de població (baixos costos d'extracció de les dades, grans dimensions de mostra, amplia cobertura espacial, etc.). L'objectiu principal d'aquesta investigació és contribuir als recents avenços en el camp de l'anàlisi de les dades de telefonia mòbil mitjançant el desenvolupament i validació d'una metodologia que permeti extreure informació de patrons d'activitat i mobilitat de la població en àmbits urbans. La metodologia desenvolupada presenta una sèrie de millores rellevants pel que fa a estudis previs, com l'estimació de localitzacions freqüents diferents de casa i treball, la millora en l'estimació de l'hora del viatge, procediments per a la selecció i expansió de la mostra o la millora en l'estimació del nombre de persones en una àrea específica a partir dels patrons d'activitat i mobilitat de les mateixes. Aquesta metodologia ha estat aplicada en tres casos d'ús per a: (1) l'obtenció d'estadístiques bàsiques de mobilitat i matrius origen-destinació en àmbits urbans, (2) l'anàlisi de la influència de la xarxa social en la mobilitat i (3) l'estudi de l'exposició de la població a la contaminació. Els resultats obtinguts demostren el potencial de les dades de telefonia mòbil per extreure informació sobre patrons de mobilitat en àmbits urbans, entendre millor la influència de la xarxa social en la mobilitat i millorar les estimacions d'exposició de la població a la contaminació. Tot i els avantatges que proporcionen les dades de telefonia mòbil, també s'han observat limitacions rellevants en els diferents estudis realitzats, derivades principalment de la resolució espai-temporal de les dades i de la limitada informació sociodemogràfica disponible. Els resultats d'aquesta investigació són de gran rellevància per a estudis de planificació i gestió del transport, per al desenvolupament de nous models de transport que tinguin en consideració la influència de la xarxa social en la mobilitat i en estudis d'avaluació de l'exposició de la població a la contaminació.Picornell Tronch, M. (2017). METODOLOGÍA PARA LA EXTRACCIÓN DE PATRONES DE MOVILIDAD URBANA MEDIANTE EL ANÁLISIS DE REGISTROS DE ACTIVIDAD TELEFÓNICA (CALL DETAIL RECORD) [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/88397TESI

On the engineering of agent-based simulations of social activities with social networks

Context Models of how people move around cities play a role in making decisions about urban and land-use planning. Previous models have been based on space and time, and have neglected the social aspect of travel. Recent work on agent-based modelling shows promise as a new approach, especially for models with both social and spatial elements. Objective This paper demonstrates the design and implementation of an agent-based model of social activity generation and scheduling for experimental purposes to explore the effects of social space in addition to physical space. As a side-effect, the paper discusses the need for and requirements on structured design of agent-based models and simulations. Method Model design was based on the MASQ meta-model and implemented in Python. The model was then tested against several hypotheses with several initial networks. Results The model allowed us to investigate the effects of social networks. We found that the model was most sensitive to the pair attributes of the network, rather than the global or personal attributes. Conclusion As demonstrated, a structured approach to model development is important in order to be able to understand and apply the results, and for the model to be extensible in the future. Agent-based modelling approaches allow for inclusion of social elements. For models incorporating social networks, testing the sensitivity to the initial network is important to ensure the model performs as expected