Reference : High-Precision Design of Pedestrian Mobility for Smart City Simulators
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/34432
High-Precision Design of Pedestrian Mobility for Smart City Simulators
English
Vitello, Piergiorgio [Politecnico di Torino > Dip. di Elettronica e Telecomunicazioni]
Capponi, Andrea mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)]
Fiandrino, Claudio [IMDEA Networks Institute]
Giaccone, Paolo [Politecnico di Torino > Dip. di Elettronica e Telecomunicazioni]
Kliazovich, Dzmitry [ExaMotive]
Bouvry, Pascal [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
May-2018
IEEE International Conference on Communications (ICC), Kansas City, MO, USA, 2018
Yes
International
IEEE International Conference on Communications (ICC)
May 2018
Kansas City
Missouri, USA
[en] Mobile Crowdsensing ; Smart Cities ; Pedestrian Mobility
[en] The unprecedented growth of the population living in urban environments calls for a rational and sustainable urban development. Smart cities can fill this gap by providing the citizens with high-quality services through efficient use of Information and Communication Technology (ICT). To this end, active citizen participation with mobile crowdsensing (MCS) techniques is a becoming common practice. As MCS systems require wide participation, the development of large scale real testbeds is often not feasible and simulations are the only alternative solution. Modeling the urban environment with high precision is a key ingredient to obtain effective results. However, currently existing tools like OpenStreetMap (OSM) fail to provide sufficient levels of details.
In this paper, we apply a procedure to augment the precision (AOP) of the graph describing the street network provided by OSM. Additionally, we compare different mobility models that are synthetic and based on a realistic dataset originated from a well known MCS data collection campaign (ParticipAct). For the dataset, we propose two arrival models that determine the users’ arrivals and match the experimental contact distribution. Finally, we assess the scalability of AOP for different cities, verify popular metrics for human mobility and the precision of different arrival models.
http://hdl.handle.net/10993/34432

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