# Towards Integrated Traffic Control with Operating Decentralized Autonomous Organization

arXiv: https://arxiv.org/abs/2308.03769 · HTML: https://mlsanity.com/paper/2308.03769/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 34 references that are in the map.
- First posted on arXiv 25 Jul 2023.

## Builds on (most cited first, 5 of 5)

- [Expert Level control of Ramp Metering based on Multi-task Deep Reinforcement Learning](https://mlsanity.com/paper/1701.08832/) (2017)
- [Blockchain for the Internet of Vehicles towards Intelligent Transportation Systems: A Survey](https://mlsanity.com/paper/2007.06022/) (2020)
- [Privacy-Preserving Smart Parking System Using Blockchain and Private Information Retrieval](https://mlsanity.com/paper/1904.09703/) (2019)
- [MARL-FWC: Optimal Coordination of Freeway Traffic Control Measures](https://mlsanity.com/paper/1808.09806/) (2018)
- [An Energy-Efficient Transaction Model for the Blockchain-enabled Internet of Vehicles (IoV)](https://mlsanity.com/paper/1811.12610/) (2018)

## Built on by (most cited first, 2 of 2)

- [Evolutionary City: Towards a Flexible, Agile and Symbiotic System](https://mlsanity.com/paper/2311.14690/) (2023)
- [Data on the Move: Traffic-Oriented Data Trading Platform Powered by AI Agent with Common Sense](https://mlsanity.com/paper/2407.00995/) (2024)

## Abstract (arXiv)

With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS that is capable of considering plentiful heterogeneous intelligent agents is desired. However, existing control methods based on the centralized or the decentralized scheme have not presented their competencies in considering the optimality and the scalability simultaneously. To address this issue, we propose an integrated control method based on the framework of Decentralized Autonomous Organization (DAO). The proposed method achieves a global consensus on energy consumption efficiency (ECE), meanwhile to optimize the local objectives of all involved intelligent agents, through a consensus and incentive mechanism. Furthermore, an operation algorithm is proposed regarding the issue of structural rigidity in DAO. Specifically, the proposed operation approach identifies critical agents to execute the smart contract in DAO, which ultimately extends the capability of DAO-based control. In addition, a numerical experiment is designed to examine the performance of the proposed method. The experiment results indicate that the controlled agents can achieve a consensus faster on the global objective with improved local objectives by the proposed method, compare to existing decentralized control methods. In general, the proposed method shows a great potential in developing an integrated control system in the ITS