| Traffic congestion problems affect major urban centers across Canada and around the world. In many cases it is impossible to mitigate congestion problems by simply adding additional infrastructure. HOV lanes can utilize existing infrastructure to provide motorists, who travel with multiple occupants in the vehicle, with a congestion free route. However, HOV lanes were found to be inefficient in many cases primarily due to the significant underutilization of available capacity. HOT lanes optimize the HOV lane concept by selling off the excess capacity to solo motorists. This research focuses on the development of a tolling algorithm that can determine the ideal toll rate dynamically and based on feedback collected from the facility. The innovation in this research is the application of a self calibration mechanism that will further optimize the HOT lane operations. The approach of this study is to combine principles of traffic microsimulation, discrete choice models, feedback control theory and other statistical tools to form an effective tolling algorithm. |
