Caltrans Corridor System Management Plan (CSMP) project aims to develop a CSMP plan that identifies system management strategies to relieve the traffic congestion problems occurred on the highways. The key tools used in the CSMP studies include microscopic simulation and travel demand forecasting models. The travel demand forecasting model is employed to extract the reference demands for the microsimulation modeling area, estimate OD demands, analyze travel demand patterns of the study corridors, and perform macro level of scenario testing. The purpose of this OCTAM model enhancement subtask was to improve and enhance the TransCAD version of OCTAM in order to meet the requirements of CSMP projects in Orange County (including I-5, SR 91, SR 57, SR 55, SR 22/I-405).
The TransCAD version of OCTAM 3.1 travel demand model was used to build the customized TransCAD version of the OCTAM 3.1 model for these CSMP studies. The original TransCAD version of the OCTAM model only had a highway traffic assignment module. Through the understanding of the original GISDK codes from Caliper Corp., a few new components were added to the enhanced OCTAM model. The new modules include select link analysis, subarea analysis, OD estimation, and output data display. In addition, we also converted OCTAM’s trip generation module to TransCAD and enabled the possibility to use different types of volume delay functions on different types of roadway facilities. For example, the BPR functions can be applied to freeway segments and the default Akcelik functions can be applied to arterials.
Besides the improvement on the OCTAM GUI, the geometries for all study corridors were updated to the latest condition. We also enabled a feature to add penalties to some turns barred in the real world in order for the model to be realistic. Moreover, most CSMP study corridors allowed us to prepare a well balanced datasets that were used in the calibration of the focused models for each study corridor. Potentially, these dataset can be applied to the whole OCTAM model to make it more accurate.