Maximizing toll revenue and level of service on managed lanes with a dynamic feedback-control toll pricing strategy

Abstract

In recent years, congestion pricing emerged as a cost-effective and efficient strategy to mitigate congestion on freeways. This study develops a dynamic toll pricing strategy based on feedback control rules and compares its performance with the current strategy deployed on the I-95 express lanes in south Florida. The proposed strategy aims to maximize the toll revenue while maintaining a minimum desirable level of service on the managed lanes. A detailed numerical example is provided to demonstrate how the proposed strategy works and the performance is examined for low and high traffic demand. An external module is developed to execute the strategy in real time during VISSIM runtime. The impact of the value of time based on the income level is also examined. Three values in the range of 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 becomes more evident, with the highest increase observed for the case of 120%. Also, during high traffic demand, high income groups exhibit higher probabilities of choosing the managed lanes despite the increase in toll rate due to the increase in travel time savings. When compared to the currently adopted toll pricing strategy on I-95, the proposed strategy shows a steadier toll rate profile and a greater overall toll revenue, while maintaining the speed at nearly 72.4 kph (45 mph).