Route choice models are a vital tool for evaluating the impact of transportation policies and
infrastructure improvements, such as the addition of new roads, tolls, or congestion charges …

In this paper, the Bush–Mosteller (BM) reinforcement learning (RL) scheme is introduced to
model the route choice behaviors of the travelers in traffic networks, who aim to seek the …

With the increase in the use of private transportation, developing more efficient ways to
distribute routes in a traffic network has become more and more important. Several attempts …

Route choice is an important stage in transport planning and modeling. Most of the existing
approaches do not consider that road users can nowadays consult new technologies to plan …

Navigation apps have become more and more popular, as they give information about the
current traffic state to drivers who then adapt their route choice. In commuting scenarios …

As the demand for mobility in our society seems to increase, the various issues centered on
urban mobility are among those that worry most city inhabitants in this planet. For instance …

The effects of traffic congestion can be mitigated with a range of different methods. This
paper addresses multiagent reinforcement learning (MARL) as a contribution to this effort …

RESUMO A área de sistemas inteligentes de transporte há muito investiga como empregar
tecnologias da informação e comunicação a fim de melhorar a eficiência do sistema como …

Solving the traffic assignment problem (TAP) is an important step towards an efficient usage
of the traffic infrastructure. A fundamental assignment model is the so-called User …