Smart Drivers: Simulating the Benefits of Giving Twitter Information about Traffic Status

• Ana L. C. Bazzan UFRGS
• Pedro G. Araújo UFRGS
• Cristiano Galafassi UFRGS
• Anderson R. Tavares UFRGS
• Alessandro Dalla Vecchia UFRGS
• Antônio Rodrigo D. de Vit UFSM
• Glaucio R. Vivian UFSM

Resumo

One of the main pillars to reach smart cities is a smart transportation system, both public and private. Our long term goal is to develop an agentbased infrastructure that can be used for investigations that are key to evaluate the effects of concepts related to smart transportation systems. However, such infrastructure demands an amount of data that few traffic authorities can afford to have. An alternative to installing sensors is to use human and their mobile devices as sensors. However, this poses challenges for the gathering and management of such data. In this paper we propose a methodology to deal with this problem. It aims at capturing and treating traffic data (mainly streets and links statuses) that appear in social networks, microblogs, etc. Specifically, we illustrate the approach with data that appears in the blog "Trânsito" that is managed by the daily paper OESP, online edition. With the implemented prototype, we have simulated thousands of agents that can do en-route adjustments on their routes based on updated knowledge of the traffic status. We were able to derive conclusions that would not be possible if only macroscopic simulation methods were used, as for instance the extent of improvement in the travel time of drivers that receive information.

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