Proactive and Robust Dynamic Pricing Strategies for High-Occupancy-Toll (HOT) Lanes

Abstract

Congestion pricing has been promoted by economists and transportation researchers as one of the most efficient means to mitigate traffic congestion. When tolls implemented on highway lanes vary by the time of day, with higher values charged during peak traffic periods, it is called as dynamic tolling. The tolled lanes are often referred to as high occupancy/toll lanes (HOT) if the high-occupancy vehicles are allowed to use the lanes for free. In the literature, many studies have been conducted to determine optimal dynamic pricing strategies. However, most of these studies consider idealized and hypothetical situations in order to derive solutions. In addition, none considers the uncertainty associated with travel demand in the determination of toll rates. This study develops a more robust and proactive approach to determine time-varying tolls for HOT lanes in response to real-time traffic conditions. The toll rates are optimized to ensure free-flow conditions on managed lanes while maximizing freeway’s throughput. The approach consists of a scenario-based robust toll optimization. Simulation experiments using field data from I-95 Express in Florida are conducted to demonstrate the proposed approach. The proposed tolling scheme is compared with the one currently implemented for I-95 Express.

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