Dynamic Feedback-Control Toll Pricing Methodology for Revenue Maximization: Case Study on I-95 Managed Lanes

Abstract

Recently, congestion pricing emerged as a cost-effective and efficient strategy to mitigate the congestion problem on freeways. This study develops a dynamic toll strategy based on feedback control rules and compares its performance to that of the current strategy deployed on Interstate 95 express lanes. The proposed strategy aims to maximize the toll revenue while maintaining a minimum desired level of service on the managed lanes. The performance was examined for low and high traffic demand. A detailed numerical example is provided to explain how the proposed strategy works, and an external module is developed to execute the strategy in real time during VISSIM runtime. The impact of the value of time and level of income is also examined. Three values ranging from 60% to 120% of the mean hourly income are used. The results show that for high demand, an increase in the probability of choosing managed lanes is obvious, with the highest increase observed for the case of 120%. Also, during high demand, high income groups exhibit higher probabilities of choosing the managed lanes as a result of the increase in travel time savings and despite the increase in toll rate. When compared to the currently adopted toll pricing strategy on I-95, the proposed strategy shows a steadier toll rate profile, while keeping the speed at 45 mph or more and producing larger toll revenue.

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