This paper presents a data-driven agent-based simulation of individual mobility based on spatio-temporal data from mobile phones. The model developed is embedded within the CityScope framework, a platform used as decision support system for city development. This work analyzes the Andorra visitors’ flow and traffic congestion through an agent-based visualization using different representation, abstraction, and interaction features.
Telecom data coupled with other data sources—such as social media—can help us understand human behavior at spacial, temporal, and social level. These un- precedented rich sources of data allow us to study how people move and, thus, how our society behaves. Previous research  show that such insights can be used to design interventions to improve our daily lives and even visitors’ expe- rience in the scope of tourism strategies, which is the case study for Andorra. However, the results of the analyses are not always comprehensible for non- experts. CityScope is a visualization framework, developed by the City Science Initiative at MIT Media Lab, that serves both as an urban data observatory and urban exploratory decision support system for city development. Cityscope is a next generation, tangible, augmented reality platform that helps to (1) visualize and understand the meaning of complex urban data and inter-relationships, (2) simulate the impact of multiple interventions and (3) support decision making in a dynamic, iterative and evidence-based process. CityScope helps non-experts to engage into conversation through visualizations that synthesize the analyses in a coherent manner on the physical model of their cities. An agent-based Model (ABM) has been used for simulating the actions and interactions of autonomous agents in this work. The central idea of the model is to show emerging patterns in visitors’ behavior during specific events . This model leads to insightful visualizations that show how visitors and locals move across the country.
The remaining of this paper is organized as follows. Section 2 gives a general overview of the framework. Section 3 describes the input data, 4 describes the ABM model. Section 5 shows the visual results of the simulation and, finally, section 6 discusses further research.
Andorra, located between Spain and France in the middle of the Pyrenees, is a country with a population around 78,000 people4 that welcomes more than eight million visitors a year. According to the statistics provided by the Departament d’Estad ́ıstica d’Andorra, the tourism sector accounts for 80% of the GDP of the country. Andorra has two types of visitors: (1) tourists, which stay over at least one night and (2) same-day visitors, which enter and leave the country the same day. The presented model has mainly been developed to simulate the movement of visitors across the territory and gain understanding on this industry. Modeling people’s flow can help us assess the actual impact of visitors in terms of traffic congestion, energy consumption, consumer spending, among others. The current model focuses on visitors’ attendance at the events held in the country as well as traffic congestion levels. The following two events in 2016 have been analyzed: (1) Cirque du Soleil, (2) Le Tour de France.
The resulting model is projected on the Andorra CityScope table, which is a 3D model of the two main cities of Andorra (see Fig. 1).
The model has been implemented using different environments: Processing  and the GAMA platform . The latter offers a more generic framework that extend the model’s functionality and allow us to process other types of data.