A Survey on Privacy in Human Mobility

In the last years we have witnessed a pervasive use of location-aware technologies such as vehicular GPS-enabled devices, RFID based tools, mobile phones, etc which generate collection and storing of a large amount of human mobility data. The powerful of this data has been recognized by both the scientific community and the industrial worlds. Human mobility data can be used for different scopes such as urban traffic management, urban planning, urban pollution estimation, etc. Unfortunately, data describing human mobility is sensitive, because people’s whereabouts may allow re-identification of individuals in a de-identified database and the access to the places visited by individuals may enable the inference of sensitive information such as religious belief, sexual preferences, health conditions, and so on. The literature reports many approaches aimed at overcoming privacy issues in mobility data, thus in this survey we discuss the advancements on privacy-preserving mobility data publishing. We first describe the adversarial attack and privacy models typically taken into consideration for mobility data, then we present frameworks for the privacy risk assessment and finally, we discuss three main categories of privacy-preserving strategies: methods based on anonymization of mobility data, methods based on the differential privacy models and methods which protect privacy by exploiting generative models for synthetic trajectory generation

A survey on privacy in human mobility

In the last years we have witnessed a pervasive use of location-aware technologies such as vehicular GPS-enabled devices, RFID based tools, mobile phones, etc which generate collection and storing of a large amount of human mobility data. The powerful of this data has been recognized by both the scientific community and the industrial worlds. Human mobility data can be used for different scopes such as urban traffic management, urban planning, urban pollution estimation, etc. Unfortunately, data describing human mobility is sensitive, because people's whereabouts may allow re-identification of individuals in a de-identified database and the access to the places visited by indi-viduals may enable the inference of sensitive information such as religious belief, sexual preferences, health conditions, and so on. The literature reports many approaches aimed at overcoming privacy issues in mobility data, thus in this survey we discuss the advancements on privacy-preserving mo-bility data publishing. We first describe the adversarial attack and privacy models typically taken into consideration for mobility data, then we present frameworks for the privacy risk assessment and finally, we discuss three main categories of privacy-preserving strategies: methods based on anonymization of mobility data, methods based on the differential privacy models and methods which protect privacy by exploiting generative models for synthetic trajectory generation

An Agent Based Model for the Simulation of Transport Demand and Land Use

Agent based modelling has emerged as a promising tool to provide planners with insights on social behaviour and the interdependencies characterising urban system, particularly with respect to transport and infrastructure planning. This paper presents an agent based model for the simulation of land use and transport demand of an urban area of Sydney, Australia. Each individual in the model has a travel diary which comprises a sequence of trips the person makes in a representative day as well as trip attributes such as travel mode, trip purpose, and departure time. Individuals are associated with each other by their household relationship, which helps define the interdependencies of their travel diary and constrains their mode choice. This allows the model to not only realistically reproduce how the current population uses existing transport infrastructure but more importantly provide comprehensive insight into future transport demands. The router of the traffic micro-simulator TRANSIMS is incorporated in the model to inform the actual travel time of each trip and changes of traffic density on the road network. Simulation results show very good agreement with survey data in terms of the distribution of trips done by transport modes and by trip purposes, as well as the traffic density along the main road in the study area

PS-Sim: A Framework for Scalable Simulation of Participatory Sensing Data

Emergence of smartphone and the participatory sensing (PS) paradigm have paved the way for a new variant of pervasive computing. In PS, human user performs sensing tasks and generates notifications, typically in lieu of incentives. These notifications are real-time, large-volume, and multi-modal, which are eventually fused by the PS platform to generate a summary. One major limitation with PS is the sparsity of notifications owing to lack of active participation, thus inhibiting large scale real-life experiments for the research community. On the flip side, research community always needs ground truth to validate the efficacy of the proposed models and algorithms. Most of the PS applications involve human mobility and report generation following sensing of any event of interest in the adjacent environment. This work is an attempt to study and empirically model human participation behavior and event occurrence distributions through development of a location-sensitive data simulation framework, called PS-Sim. From extensive experiments it has been observed that the synthetic data generated by PS-Sim replicates real participation and event occurrence behaviors in PS applications, which may be considered for validation purpose in absence of the groundtruth. As a proof-of-concept, we have used real-life dataset from a vehicular traffic management application to train the models in PS-Sim and cross-validated the simulated data with other parts of the same dataset.Comment: Published and Appeared in Proceedings of IEEE International Conference on Smart Computing (SMARTCOMP-2018

Managing the complexity: decision making process on sustainable mobility

Starting from the literature on decision processes in public choices, aim of the paper is to suggest an integrated methodology to get a choice as much as possible shared and participated joining two different approaches. On one hand there is the “classic†or top-down approach based on statistical data analysis and handling, having as target the definition of some synthetic indicators. On the other hand there is a bottom-up approach based on the Strategic Environment Assessment (SEA) logical framework and on citizens participation. Particularly the paper will apply the above mentioned methodology to face the theme of sustainable mobility showing at the end the results obtained in the analysis of the 13th District of the Municipality of Rome. The choice of sustainable mobility as a target of decision process lies on the fact that actually it is included with a high priority in the agenda of European institutions and (local and national) administrative governments. The proposed model does not provide a solution, but rather defines a process that is able to recognize the particularities of different territorial contexts to yield appropriate, case specific solutions.

Multiscale mobility networks and the large scale spreading of infectious diseases

Among the realistic ingredients to be considered in the computational modeling of infectious diseases, human mobility represents a crucial challenge both on the theoretical side and in view of the limited availability of empirical data. In order to study the interplay between small-scale commuting flows and long-range airline traffic in shaping the spatio-temporal pattern of a global epidemic we i) analyze mobility data from 29 countries around the world and find a gravity model able to provide a global description of commuting patterns up to 300 kms; ii) integrate in a worldwide structured metapopulation epidemic model a time-scale separation technique for evaluating the force of infection due to multiscale mobility processes in the disease dynamics. Commuting flows are found, on average, to be one order of magnitude larger than airline flows. However, their introduction into the worldwide model shows that the large scale pattern of the simulated epidemic exhibits only small variations with respect to the baseline case where only airline traffic is considered. The presence of short range mobility increases however the synchronization of subpopulations in close proximity and affects the epidemic behavior at the periphery of the airline transportation infrastructure. The present approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multi-scale framework.Comment: 10 pages, 4 figures, 1 tabl

Microsimulation of urban land use

The project ILUMASS (Integrated Land-Use Modelling and Transportation System Simulation) aims at embedding a microscopic dynamic simulation model of urban traffic flows into a comprehensive model system incorporating both changes of land use and the resulting changes in transport demand. The land-use component of ILUMASS will be based on the land-use parts of an existing urban simulation model, but is to be microscopic like the transport parts of ILUMASS. Microsimulation modules will include models of demographic development, household formation, firm lifecycles, residential and non-residential construction, labour mobility on the regional labour market and household mobility on the regional housing market. These modules will be closely linked with the models of daily activity patterns and travel and goods movements modelled in the transport parts of ILUMASS developed by other partners of the project team. The design of the land use model takes into account that the collection of individual micro data (i.e. data which because of their micro location can be associated with individual buildings or small groups of buildings) or the retrieval of individual micro data from administrative registers for planning purposes is neither possible nor, for privacy reasons, desirable. The land use model therefore works with synthetic micro data which can be retrieved from generally accessible public data. ILUMASS is a group project of institutes of the universities of Aachen, Bamberg, Dortmund, Cologne and Wuppertal under the co-ordination of the Transport Research Institute of the German Aerospace Centre (DLR). Study region for tests and first applications of the model is the urban region of Dortmund. The common database will be compiled in co-operation with the City of Dortmund. After its completion the integrated model is to be used for assessing the impacts of potential transport and land use policies for the new land use plan of the city. The paper will focus on the land-use parts of the ILUMASS model. It will present the underlying behavioural theories and how they are made operational in the model design, explain how the synthetic population is generated, show first model results and demonstrate the potential usefulness of the model for the planning process.