Abstract:
Traffic congestion is an important factor in today's urban life which has a direct influence on people's quality of life. This phenomenon usually happens on peak times when people are commuting to work. As people are stuck in the traffic congestion, not only it will take more time to reach their destination, but also this wasted time can be of their work's time meaning a loss of money. In addition to that, congestion may cause pollution. Since more vehicles are stuck in traffic and cannot advance properly, higher amount of gas is ejected to the air. Thus, tackling congestion problem is critical. There are several factors that lead to traffic congestion including the times when roads are full of vehicles, or when there are constructions, maintenance or incidents on roads. These factors cause a disruption in traffic flow. It is important to note that resolving congestion problem cannot only be done by increasing capacity and by constructing new roads and motorways; It also requires developing a transportation management technology. Although the solution of building new roads may seem interesting at first sight, it is not practical as it may cause even more problems. Therefore, utilizing the existing roads and enhancing the traffic management technology would be a better solution. Having a calibrated traffic flow model that reproduces the behavior of drivers on the real road can be of benefit. A calibrated and simulated microscopic traffic flow model is used in this thesis to calibrate a second-order macroscopic traffic flow model to represent the traffic flow on the motorway in Sweden by validation. For this purpose, different scenarios which represent free flow, intermediate flow and congestion have been studied. This model can be used to better manage the traffic and implement control strategies on motorways.
