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Multi-class traffic flow model based on three dimensional flow–concentration surface.

Authors :
Mohan, Ranju
Ramadurai, Gitakrishnan
Source :
Physica A. Sep2021, Vol. 577, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

This paper proposes a continuum model based on a three-dimensional flow-concentration surface for multi-class traffic. The model assumes that the flow of any vehicle class is a function of the class density as well as the fraction of road area occupied by other vehicle classes. By considering occupancy of road area instead of lane occupancy, the model effectively describes traffic flow that does not follow lane discipline. The propagation speed of small disturbance (PSSD), conventionally defined from the two-dimensional flow–density relationship, is reformulated for each class using a three-dimensional flow–concentration surface. Using the proposed PSSD and a speed–area occupancy (speed- A O) relationship, a second-order continuum model for multi-class traffic is formulated. The speed– A O relationship captures class-specific congestion and replicates the gap-filling behaviour commonly observed in lane-indisciplined traffic. Properties of the proposed model are validated theoretically where possible, and through numerical simulation when theoretical derivations are cumbersome. Numerical simulation of the proposed multi-class traffic model replicates field-observed phenomena such as shockwaves and rarefaction waves, local cluster effect, and gap-filling behaviour. Finally, the model is calibrated using field traffic data collected on a road section with bottleneck, and is found to replicate class-wise vehicle flows and speeds, and stop-and-go phenomena. • Use of a three-dimensional flow–concentration surface for multi-class traffic. • Analytical formulation of class-wise propagation speeds of small disturbances (PSSD) for multi-class traffic. • A novel higher-order model that does not restrict the number of vehicle classes. • Analytical proofs and numerical checks of fundamental traffic flow properties. • Calibration of the model with real-world multi-class traffic flow data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03784371
Volume :
577
Database :
Academic Search Index
Journal :
Physica A
Publication Type :
Academic Journal
Accession number :
150770539
Full Text :
https://doi.org/10.1016/j.physa.2021.126060