Towards Integrated Traffic Control with Operating Decentralized Autonomous Organization
Shengyue Yao, Jingru Yu, Yi Yu, Jia Xu, Xingyuan Dai, Honghai Li,, Fei-Yue Wang, Yilun Lin

TL;DR
This paper introduces a decentralized autonomous organization framework for integrated traffic control, achieving faster consensus on global energy efficiency and improving local objectives in intelligent traffic systems.
Contribution
It proposes a novel DAO-based control method with a consensus and incentive mechanism, enhancing scalability and optimality in traffic management.
Findings
Faster consensus on energy consumption efficiency achieved
Improved local objectives of intelligent agents
Demonstrated potential for integrated traffic control systems
Abstract
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…
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Taxonomy
TopicsTraffic control and management · Blockchain Technology Applications and Security · Transportation Planning and Optimization
