Selecting Compliant Agents for Opt-in Micro-Tolling


  • Josiah P. Hanna University of Texas at Austin
  • Guni Sharon Texas A&M University
  • Stephen D. Boyles University of Texas at Austin
  • Peter Stone University of Texas at Austin



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.




How to Cite

Hanna, J. P., Sharon, G., Boyles, S. D., & Stone, P. (2019). Selecting Compliant Agents for Opt-in Micro-Tolling. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 565-572.



AAAI Special Technical Track: AI for Social Impact