A Simulation-Based Optimization Framework for Urban Congestion Pricing Considering Travelers’ Departure Time Rescheduling

Abstract

This paper develops a simulation-based optimization (SBO) framework for addressing urban congestion pricing problems considering travelers’ departure time rescheduling, and demonstrates the framework using a large-scale simulation-based dynamic traffic assignment (SBDTA) model of Melbourne, Australia. The pricing regime considered is a distance toll linearly proportional to the total distance traveled within the pricing zone (PZ). To optimize the toll rates such that the network fundamental diagram (NFD) of the PZ does not enter the congestion regime, we employ the discrete proportional-integral (PI) controller and further incorporate the scheduling cost for adjusting travelers’ departure times, with the objective of minimizing their generalized travel costs. A comparison among three scenarios is performed: non-pricing and pricing with and without departure time rescheduling. Results clearly show the benefits of pricing on the network performance as well as the significance of adjusting travelers’ departure times.