ABSTRACT
In this chapter, the authors complete a review and analysis of a broad range of topics related to dynamic pricing in the United States. They look into different types of congestion pricing strategies which have been utilized across these implementations. The first goal of developing an efficient tolling algorithm was completed by adopting a system-optimal approach to the problem. The second goal of this research is to evaluate and compare the performance of three NLP algorithms to solving the dynamic programming problem. The third goal of this research is to accurately forecast demand flows on the corridor on an hourly basis. In summary, the authors bring a fresh approach to the topic of dynamic pricing. They demonstrate how system-optimal methodology can be applied to minimize travel time along the 95 HOT lanes and reduce congestion with an efficient tolling algorithm.
