Every HOV lane is unique in its demand composition and operational characteristics. These characteristics are often difficult to quantify, so it is challenging for HOV operators to know exactly how well their HOV lanes are operating. Likewise, the impacts of any policy changes to their HOV facilities are also difficult to quantify, and would create additional uncertainty concerning future HOV performance. So before making any changes, it is critical to understand: (1) the current operating conditions of the existing HOV facility; (2) what impacts on the operational performance of the HOV facility can be expected with policy shifts; and (3) whether policy shifts will help the operator meet the goals and objectives established in the study region.
POET-ML is one feasible alternative to travel demand modeling. The tool makes it possible for HOV operators to complete a current HOV system condition assessment, quantify the impacts of HOV lane policy shifts on operational performance and financial feasibility, and ultimately prioritize the most appropriate HOV policy changes, or combination of HOV policy changes, to best align with their system goals and performance objectives. This will all be accomplished through a simple user interface that does not require extensive modeling know-how. Users equipped with even limited input data will be able to apply what they know to get sketch-level planning output and suggestions for HOV policy modification.
Specifically, POET-ML has been structured to help HOV operators answer the following questions:
United States Department of Transportation - Federal Highway Administration