Bruno Sarno Mugnela,  Marcio Lobo Netto. 

There is a considerable knowledge base for traffic engineering optimization using genetic algorithms, but rare are the real applications on environments that lack on traffic flow data or Intelligent Transportation Systems (ITS). This paper summarizes a new simulation model over which a genetic algorithm is applied for finding signal timing plans that reduce stops and delays in congested urban sub-networks. The tool is simplified for achieving fast running times using only the parameters measured by the Traffic Engineering Company of the city of São Paulo (CET-SP). The case study in one of its sub-networks resulted in approximate 30% reduction of the delays registered in the simulations of the previous plans.

http://www.lbd.dcc.ufmg.br/colecoes/sbsi/2012/0023.pdf

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