Exploring Intra-Urban Accessibility and Impacts of Pollution Policies with an Agent-Based Simulation Platform: GaMiroD

Abstract

International audienceIn this work we address the issue of sustainable cities by focusing on one of their verycentral components: daily mobility. Indeed, if cities can be interpreted as spatial organizationsallowing social interactions, the number of daily movements needed to reach this goal iscontinuously increasing. Therefore, improving urban accessibility merely results in increasingtraffic and its negative externalities (congestion, accidents, pollution, noise, etc.), while eventuallyreducing the quality of life of people in the city. This is why several urban-transport policies areimplemented in order to reduce individual mobility impacts while maintaining equitable access tothe city. This challenge is however non-trivial and therefore we propose to investigate this issuefrom the complex systems point of view. The real spatial-temporal urban accessibility of citizenscannot be approximated just by focusing on space and implies taking into account the space-timeactivity patterns of individuals, in a more dynamic way. Thus, given the importance of localinteractions in such a perspective, an agent based approach seems to be a relevant solution. Thiskind of individual based and “interactionist” approach allows us to explore the possible impactof individual behaviors on the overall dynamics of the city but also the possible impact of globalmeasures on individual behaviors. In this paper, we give an overview of the Miro Project andthen focus on the GaMiroD model design from real data analysis to model exploration tunedby transportation-oriented scenarios. Among them, we start with the the impact of a LEZ (LowEmission Zone) in the city center

The GDPR beyond Privacy: Data-Driven Challenges for Social Scientists, Legislators and Policy-Makers

“…Several researchers in the CSS area suggest coping with this risk by combining data with different methods, deepening the range of possibilities offered by computational development. Results produced by sophisticated data analytics tools, for examples, can be embedded in large-scale simulation models, which aim to explain from the bottom-up the complex dynamics of a social phenomenon and, eventually, to assess how such dynamics could react to a change, like the introduction of a new policy [72,73]. Similar integrated approaches can make new sense of data, allowing more robust knowledge to be drawn from it and also for it to be involved in a frame of long-term policy decisions [31,74,75].…”

The daycourse of place

“…To get place attributes which would be hour-stamped, web scraping is a first alternative: it provides the opportunity to extract information about opening and closing hours of listed services from platform such as Google Map. A second alternative is to make phone calls to get temporal information about a stratified random sample of shops, services and businesses, as it was done in Grenoble, France (Fosset et al, 2016).…”

“…Complex systems approaches help to more fully realise on-going incursions into explaining how dynamics -processes of change over timeimpact upon health (Lewis, 2017). In agent-based models, individuals are considered as autonomous and reactive entities (agents), able to perceive and explore places, to modify them and to adapt their (mobility) behaviour when facing unusual conditions (Fosset et al, 2016). Complex space-time data such as peak periods for services or car traffic could be simulated hourly accounting for feedback and dependency between individuals and between individuals and place attributes.…”

Building, composing and experimenting complex spatial models with the GAMA platform

“…A good example is the GaMiroD model [29] that deals with daily mobility in a city. This model proposes a realistic representation of the transportation infrastructure (roads, public transportation...) and to model every inhabitants of a city and their daily activities.…”