Recently, congestion pricing emerged as a cost-effective and efficient strategy to mitigate the congestion problem on freeways. This study develops a feedback-control based dynamic toll approach to formulate and solve for optimal tolls. The study compares the performance of the proposed methodology to that of the current strategy deployed on Interstate 95 express lanes. Two objectives are studied: one is to maximize the toll revenue while maintaining a minimum level of service on the managed lanes and the other is to maximize both revenue and throughput on the managed lanes while keeping a minimum level of service. The impact of drivers value of time based on their income level 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%. Besides, the effects of distributions of drivers value of time among drivers are addressed. Two numerical examples are provided to explain how the proposed strategy works under three driver groups and forty-four driver groups, and an external module is developed to execute the strategy in real time during VISSIM runtime. When compared to the currently adopted toll pricing strategy on I-95, the proposed strategy with both objectives produce steadier toll rate profiles, while keeping the speeds at 45 mph or more. The objective of revenue maximization produces larger toll revenue and objective of both revenue and throughput maximization produces higher throughput on the managed lanes.
Dynamic Feedback Control Toll Pricing Methodology: A Case Study on Interstate 95 Managed Lanes
2013
57 pages
Report
No indication
English
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