Selecting Compliant Agents for Opt-in Micro-Tolling
Abstract
This paper examines the impact of tolls on social welfare in the context of a transportation network in which only a portion of the agents are subject to tolls. More specifically, this paper addresses the question: which subset of agents provides the most system benefit if they are compliant with an approximate marginal cost tolling scheme? Since previous work suggests this problem is NP-hard, we examine a heuristic approach. Our experimental results on three real-world traffic scenarios suggest that evaluating the marginal impact of a given agent serves as a particularly strong heuristic for selecting an agent to be compliant. Results from using this heuristic for selecting 7.6% of the agents to be compliant achieved an increase of up to 10.9% in social welfare over not tolling at all. The presented heuristic approach and conclusions can help practitioners target specific agents to participate in an opt-in tolling scheme.
Cite
Text
Hanna et al. "Selecting Compliant Agents for Opt-in Micro-Tolling." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.3301565Markdown
[Hanna et al. "Selecting Compliant Agents for Opt-in Micro-Tolling." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/hanna2019aaai-selecting/) doi:10.1609/AAAI.V33I01.3301565BibTeX
@inproceedings{hanna2019aaai-selecting,
title = {{Selecting Compliant Agents for Opt-in Micro-Tolling}},
author = {Hanna, Josiah P. and Sharon, Guni and Boyles, Stephen D. and Stone, Peter},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2019},
pages = {565-572},
doi = {10.1609/AAAI.V33I01.3301565},
url = {https://mlanthology.org/aaai/2019/hanna2019aaai-selecting/}
}