Abstract
Road pricing has been advocated for decades as an efficient way of reducing congestion since the 1920s. In the U.S., there are several types of managed lanes, and the high-occupancy-toll (HOT) lane is an application of road pricing on freeway. At the same time, value of time (VOT) is a key factor when deploying congestion pricing. In this study, the authors propose one new approach to estimate driversâ?? VOT and determine the real-time tolling strategy for HOT lane simultaneously when lane drop occurs downstream of freeway segment. There are two goals of operating HOT lanes, one is to maximize the freewayâ??s throughput, and another one is to maintain the free flow speed. The traffic state variables used in this paper is the queue length on HOT lane and turning in-flux of â??paidâ?? single-occupancy-vehicles (SOVs). The traffic dynamics is described by a point queue model. When the HOT lane is operated at optimal, the authors can use feedback control algorithm to estimate driversâ?? VOT; and the pricing rate for the HOT lane is calculated by the product of estimated VOT and travel time difference of two types of lanes. Simulations results are provided to validate their approach.