A Simulation-Based Approximation Algorithm for Dynamic Marginal Cost Pricing

Abstract

This work offers a simulation-based approximation algorithm for dynamic marginal cost pricing (MCP) congestion pricing that is a direct extension of its static counterpart. The algorithm approximates the time-dependent marginal costs, and is incorporated into the inner approximation dynamic user equilibrium algorithm to evaluate the results of dynamic MCP, which are then compared to static assignment results with MCP from previous study. The status quo and dynamic MCP-on-freeways scenarios are simulated (and then compared) on the Dallas-Fort Worth 35,732-link network. Due to computational requirements for such a large-scale dynamic traffic assignment application, the dynamic MCP scenario is simulated without feedback, and only route choices are permitted to vary. When prices are imposed on freeway users, some minor system benefits are observed, including a delay in the onset of congestion. Dynamic prices vary substantially over the three-hour period of analysis, reflecting changes in freeway congestion. Reasons for any inconsistencies between dynamic and static results are discussed, along with important enhancements to future implementation.

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