There is a lack of proper travel demand forecasting tools that can evaluate and determine the impacts of pricing on travelers’ decision. The current methods use aggregated and zonal-based approaches that lack the capability of tracing individual travelers through the supply network. Transportation analysis simulation system (TRANSIMS) has unique capabilities of accessing individual records such as socioeconomic and trip characteristics and tracing vehicle as well as individual traveler movements. Although TRANSIMS environment has been significantly improved over the past few years, there are issues that still need to be improved, including the pricing of a high-occupancy toll (HOT) lane and the rescheduling of activities in case a traveler chooses time choice versus route choice. This study extends the previous work on a HOT lane system by developing a departure time choice model. The proposed method is a post-processing of route choice and represents a sequential decision-making process of travelers who want to depart early or late based on congestion, individual attributes, and activity characteristics. The paper presents the results of a departure time choice model and its impacts on a HOT lane system using Portland, Oregon as a case study. The results show that 13.9% of households did change their departure time because of congestion and/or tolls.
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Lee et al. (2009) studied this question.
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