Agent-based network transmission model using the properties of macroscopic fundamental diagram. (August 2018)

• Record Type: Journal Article
• Authors: Kim, Sunghoon; Tak, Sehyun; Yeo, Hwasoo
• Is Part Of: Transportation research. Volume 93(2018)
• Page Start: 79
• Page End: 101
• Publication Date: 2018-08
• Subjects: Cell transmission model -- Macroscopic fundamental diagram (MFD) -- Network dynamics -- Perimeter control -- Traffic simulation; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2018.05.024
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: An agent-based network transmission model for large-scale urban traffic is proposed. The effect of outbound demand on network outflow is newly modeled. The effect of boundary capacity on network outflow is newly modeled. A new approach using agent concept is suggested for expressing travel behaviors. The appropriate accuracy of network-wide traffic estimation is shown by the model. Abstract: The field of research that has recently come to the fore is the perimeter control, which aims to control traffic demand for a large urban area prior to controlling internal flow inside the area. Such control concept needs to be tested by simulations, hence, it is necessary to develop a model that can appropriately estimate the network-wide flow dynamics. In this paper, agent-based network transmission model (ANTM) is proposed for describing the aggregated flow dynamics over an urban area of multiple large-scale networks. The proposed model is the combination of the cell transmission model (CTM), macroscopic fundamental diagram (MFD), and agent concept. The CTM-based simulation is adopted for the simplicity considering the computation requirements for real-time feasibility. The MFD concept is applied for representing the network properties, and a new approach is taken particularly for estimating network outflow affected by both demand patterns and boundary capacity. The agent concept is applied for representing drivers' travel behaviors. The model is compared with microscopic simulations and shows reasonable accuracy for large areas. In addition, various travel direction choice behaviors are applicable to this model. Various perimeter control policies are applicable as well, thus, the proposed model can be a useful tool for testing various control methods, in terms of reducing the congestion in urban areas.