A Parallelized Algorithm for a Real-Time Traffic Recommendations Architecture Based in Multi-agents

摘要

Rapid population growth of cities has generated great predicament to their traffic and transport systems. These problems tend to be extremely dynamic and complex to be addressed by centralized solutions. However, multi-agent systems have proven to be a technology capable of handle this kind of problems. In previous work we proposed a conceptual framework based on agents able to analyze in-formation from different sources (smart phones, applications open programming, social networks, datasets open) and make recommendations in real time based on the preferences and needs users. In this paper, we extend this work by proposing the parallelized algorithm used in generating the best k routes.