Application of Traffic Weighted Multi-Map Optimization Strategies to Traffic Assignment

Traffic Assignment Problem (TAP) is a critical issue for transportation and mobility models that deals mainly with the calculus delivery of best-cost routes trips in traffic network. It computationally complex problem focused on finding user equilibrium (UE) system optimum (SO). The Weighted Multi-Maps (TWM) technique offers new perspective TAP calculus, based routing decisions using different network views. These TWM are complementary cost maps combine physical networks, occupation data, policies. This paper shows how evolutionary algorithms can find optimal solve from SO perspective, minimizing total travel time providing to vehicles. Several strategies compared: baseline algorithm optimizes whole two extended k-shortest path mappings. Algorithms analyzed following simulation-optimization methodology over synthetic real networks. Obtained results show generate solutions close static UE assignment methods at reasonable computational cost. A crucial aspect its good performance terms level, avoiding need continuous route status data streaming.