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A Mathematical Model for Evaluating the Conversion of High Occupancy Vehicle Lane to High Occupancy/ Toll Lane
Abstract
A methodology for evaluating and quantifying the benefits/ costs of converting a given
High Occupancy Vehicle (HOV) lane into a High Occupancy/ Toll (HOT) lane is
presented in this study. A mathematical programming model that seeks the optimal
pricing strategy, using a logit-like choice model embedded as constraints, forms the core
of the methodology. A salient feature of this study is the incorporation of equity into the
planning process by imposing constraints thus enabling planners to limit the inequities in
vertical as well as temporal dimensions. A HOV lane on a corridor on I-80 in the San
Francisco Bay Area was studied for conversion under different objectives – revenue
maximization, total vehicular travel time minimization, total passenger time
minimization, total cost minimization and minimization of total vehicle miles traveled. It
was found that converting the HOV lane into a HOT lane would improve the objective
function in all programs except for total cost minimization. It was also found that the
capital and operating costs can be recovered in a reasonable amount of time (three-five
yrs). The analysis revealed that there can be significant differences in the pricing
strategies across different objective functions. The variation in the system performance
measures across different programs was also studied and it was found that revenue was
the most sensitive performance measure. The results of all the programs revealed that
there is an inverse relationship between equity and efficiency, with the exact nature of
this relationship being a function of the objective. Furthermore, in situations where there
is no redistribution of revenues, the vertical equity situation cannot be improved even
though all the user groups can be made better off after the conversion.
Additionally, Dynamic Programming models were constructed to solve for the optimal
sequence/ schedule of converting a given set of HOV lanes into HOT lanes. The optimal
sequences here minimized the total conversion time for a self-sustaining/ self-financing
sequence or minimized the total funding needed to complete all the conversions by a
certain deadline.
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