Abstract
Road pricing has been attracting attention as a method to alleviate road congestion. In recent years, applying tolls dynamically has become technically feasible owing to information communication technology and the advancement of connected and autonomous vehicles. Marginal cost tolls (MCT) are a well-known method guaranteed to achieve optimal system performance. However, it is difficult to accurately calculate MCT, and it is unclear how MCT affects the system performance in noisy environments.
In this study, we show the theoretical noise conditions that do not decrease the system performance when using MCT with link-specific noise expressed as a constant factor. First, this study defines the Price of Anarchy Safety Zone (PoASZ) as the set of theoretical conditions of noise that guarantees that the system performance of applying inaccurate MCT will not lead to worse traffic than the scenario without tolls. We further demonstrate the simulation experiments under various traffic networks and discuss the effect of tolls on the system performance. Simulation results verify the theoretical conditions of this study using the simulation-based Price of Anarchy Safety Zone (PoASZ) in some traffic networks.
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Notes
- 1.
Note that this paper does not focus on technical or political issues in applying tolls.
- 2.
The source code of Algorithm B in language C (https://sboyles.github.io/teaching/ce392c/tap.zip) is modified for the purpose of this experiment.
- 3.
Even in case (b), when the variance is equal to 0, i.e., when the noise is constant across the network (\(\tau _e= r\tau _e^{*}\), \(\forall e\in E\), \(r\): const.), the result supports the conclusion of [15] that the system performance increases monotonically for \(r\ge 1\).
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Yoshida, N., Fujita, K. (2023). Robustness of Congestion Pricing in Traffic Networks with Link-Specific Noise. In: Aydoğan, R., Criado, N., Lang, J., Sanchez-Anguix, V., Serramia, M. (eds) PRIMA 2022: Principles and Practice of Multi-Agent Systems. PRIMA 2022. Lecture Notes in Computer Science(), vol 13753. Springer, Cham. https://doi.org/10.1007/978-3-031-21203-1_1
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