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Disentangling the city traffic rhythms: A longitudinal analysis of MFD patterns over a year
- Source :
- Transportation research. Part C, Emerging technologies, Transportation research. Part C, Emerging technologies, Elsevier, 2021, 126, 21p. ⟨10.1016/j.trc.2021.103065⟩
- Publication Year :
- 2021
- Publisher :
- HAL CCSD, 2021.
-
Abstract
- Urban road transportation performance is the result of a complex interplay between the network supply and the travel demand. Fortunately, the framework around the macroscopic fundamental diagram (MFD) provides an efficient description of network-wide traffic performance. In this paper, we show how temporal patterns of vehicle traffic define the performance of urban road networks. We present two high-resolution traffic datasets covering a year each. We introduce a methodology to quantify the similarity of macroscopic traffic patterns. We do so by using the concepts of the MFD and a dynamic time warping (DTW) based algorithm for time series. This allows us to derive a few representative MFD clusters that capture the essential macroscopic traffic patterns. We then provide an in-depth analysis of traffic heterogeneity in the network which is indicative of the previously found clusters. Thereupon, we define a parsimonious classification approach to predict the expected MFD clusters early in the morning with high accuracy.
- Subjects :
- EMPIRICAL DATA
Empirical data
Dynamic time warping
Computer science
PREDICTION
Transportation
CLUSTERING
010501 environmental sciences
Management Science and Operations Research
computer.software_genre
CIRCULATION ROUTIERE
01 natural sciences
Rhythm
Similarity (network science)
11. Sustainability
0502 economics and business
TRAFIC ROUTIER
Cluster analysis
0105 earth and related environmental sciences
Civil and Structural Engineering
050210 logistics & transportation
Series (mathematics)
05 social sciences
Diagram
MODELE MACROSCOPIQUE
Urban road
MODELISATION
[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
MODELE PREDICTIF
SYSTEME DYNAMIQUE
Automotive Engineering
SIMULATION
MACROSCOPIC FUNDAMENTAL DIAGRAM (MFD)
Data mining
REGULATION DU TRAFIC
RESEAU URBAIN
computer
Subjects
Details
- Language :
- English
- ISSN :
- 0968090X and 18792359
- Database :
- OpenAIRE
- Journal :
- Transportation research. Part C, Emerging technologies, Transportation research. Part C, Emerging technologies, Elsevier, 2021, 126, 21p. ⟨10.1016/j.trc.2021.103065⟩
- Accession number :
- edsair.doi.dedup.....57b00c1e2e6f82f9ea4aeae3ff243c6b