Issue |
E3S Web Conf.
Volume 165, 2020
2020 2nd International Conference on Civil Architecture and Energy Science (CAES 2020)
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Article Number | 04051 | |
Number of page(s) | 6 | |
Section | Civil, Architectural Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202016504051 | |
Published online | 01 May 2020 |
Macroscopic Fundamental Diagram based Road Network Characteristics Identification and Simulation
1 Shanghai Jiuxuan Engineering Technology Co., Ltd., 201000 Shanghai, China
2 . China University of Mining and Technology, School of mines, 221116, China
3 Shanghai Maritime University, College of Transport and Communications, 201306 Shanghai, China
4 Shanghai Maritime University, China Institute of FTZ Supply Chain, 201306 Shanghai, China
* Corresponding author: yyleno@126.com
As an inherent property of the road network, macroscopic fundamental diagram (MFD) method can effectively describe the traffic status of the urban roads and identify the relationship among key factors, such as traffic flow and occupancy. Currently, using MFD is easily affected by various network inner factors including topology and road density, so in this paper we propose a method to identify inner characteristic of road network and do a series of comparisons under different scenarios with fixed traffic input circumstance. The differential impact of data collector setting locations are discussed with a aim to reveal the respective location setting suitable for various networks conditions in initial; then road topology and density are designed in road network and simulated MFD performances with flow equilibrium affections. It is shown as the dispersion decreasing of link length or road density of network, the network exhibits better operation efficiency so as to increase the output of link flow and the dissipative ability of the road network. Meanwhile, the equivalent of entrances and exits is proved as another important factor has same impact on MFD.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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