Abstract
High-Occupancy Vehicle (HOV) lanes, commonly known as carpool lanes, have been accepted as a cost-effective and environmental-friendly alternative in many metropolitan areas. It is thus very important to find ways to evaluate HOV strategies during the decision making process, and prior to any implementation. An alternative approach is microscopic traffic simulation. However, current micro-simulation models have limited capabilities to model HOV driver behaviors, particularly with respect to buffer-separated facilities. This study proposed a probabilistic HOV driver behavioral model based on discrete choice modeling derived from random utility principles, which includes a preferred access choice model for examining travel time savings and a traffic model for calculating the acceptable gap to get in/out the HOV lane. A HOV access plugin was also developed using a micro-simulation tool, Paramics, based on the proposed model. Its theoretical capability is extended to real-world application via providing additional â??implementationâ?? parameters, such as ingress and egress points selection control, and update frequency of traffic information. A real-world freeway network, SR-57 in Orange County, California, was selected to analyze the reasonableness of the model through sensitivity analysis, and was further investigated for model validation purposes. The results have shown the reasonableness of the proposed model under various traffic conditions. The proposed model also demonstrated its feasibility and applicability via setting various calibration parameters and control parameters.
