Partitioning a heterogeneous road network into homogenous subnetworks is one way of solving the problem of high scattering or a hysteresis loop that may be inherent in the empirics of a macroscopic fundamental diagram. This study conducts cross-comparison analysis of two well-studied partitioning methods—(i) community detection through modularity maximization and (ii) normalized cut graph partitioning—to investigate the applicability of these methods. Through a case study using real traffic data recorded by an enormous number of detectors in the Tokyo central business district, we found that both methods work well for the test transportation network; however, undesirable results may be obtained if there is only one bottleneck in a subnetwork, or if there is a drastic change in traffic conditions between adjacent links.
Cross Comparison of Spatial Partitioning Methods for an Urban Transportation Network
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 18 , 3 ; 412-421
2020-09-01
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Network partitioning , Macroscopic fundamental diagram , Normalized cut , Community detection Engineering , Electrical Engineering , Automotive Engineering , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics , Civil Engineering , User Interfaces and Human Computer Interaction
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