Due to the increasing ease and affordability of intelligent transportation systems (ITS) data collection, new methods for assessing conditions along current and future transit corridors are available. Measures such as average speed, travel time, and intersection delay can be determined for car and bus traffic along a corridor using readily available technology. These measures can be used to monitor the performance of the transportation system for existing modes and to estimate measures for proposed additions to the system.
The goal of this research is to utilize GPS device records from regular vehicles as well as busses to estimate running time and potential passenger demand for a proposed Bus Rapid Transit (BRT) corridor on Cedar Avenue in the southern Twin Cities Metropolitan Area. Demand for future BRT service is predicted based on frequency and reliability of service and socio-demographic characteristics of the region around the corridor. Average passenger counts for existing transit service along the corridor in combination with existing commuting patterns in the region are used to estimate passenger demand.
The running time and demand models produced by this study can be integrated with existing cost benefit software to evaluate the effects of intelligent transportation systems technologies on BRT running time (IBAT). The findings of this research introduce a benchmark for comparison between transit and private vehicle running time for general applications in Hennepin County. These findings also help to create additional understanding of the potential for BRT service in the Twin Cities region.