Modeling Traffic Congestion Spreading Using a Topology-Based SIR Epidemic Model
Authors: Kozhabek, A., Chai, W.K. and Zheng, G.
Journal: IEEE Access
Volume: 12
Pages: 35813-35826
eISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3370474
Abstract:The continuous urbanisation and increase in vehicle ownership have increasingly exacerbated traffic congestion problems. In this paper, we advocate the use of epidemic theory to model the spreading of traffic congestion in urban cities. Specifically, we use the Susceptible-Infected-Recovered (SIR) model but propose to explicitly consider the road network structure in the model to understand the contagion process of road congestion. This departs from the classical SIR model where homogeneous mixing based on the law of mass action is assumed. For this purpose, we adopt the N-intertwined modeling framework for the SIR model based on continuous-time Markov chain analysis. In our evaluation, we used two real-world traffic datasets collected in California and Los Angeles. We compare our results against both classical and average-degree-based SIR models. Our results show better agreement between the model and actual congestion conditions and shed light on how congestion propagates across a road network. We see the potential application of insights gained from this work on the development of traffic congestion mitigation strategies.
https://eprints.bournemouth.ac.uk/39531/
Source: Scopus
Modeling Traffic Congestion Spreading Using a Topology-Based SIR Epidemic Model
Authors: Kozhabek, A., Chai, W.K. and Zheng, G.
Journal: IEEE ACCESS
Volume: 12
Pages: 35813-35826
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3370474
https://eprints.bournemouth.ac.uk/39531/
Source: Web of Science (Lite)
Modeling traffic congestion spreading using a topology-based SIR epidemic model
Authors: Kozabek, A., Chai, W.K., Zheng, G. and Kozhabek, A.
Journal: IEEE Access
Publisher: IEEE
ISSN: 2169-3536
https://eprints.bournemouth.ac.uk/39531/
Source: Manual
Modeling traffic congestion spreading using a topology-based SIR epidemic model
Authors: Kozabek, A., Chai, W.K. and Zheng, G.
Journal: IEEE Access
Publisher: IEEE
ISSN: 2169-3536
Abstract:The continuous urbanisation and increase in vehicle ownership have increasingly exacerbated traffic congestion problems. In this paper, we advocate the use of epidemic theory to model the spreading of traffic congestion in urban cities. Specifically, we use the Susceptible-Infected-Recovered (SIR) model but propose to explicitly consider the road network structure in the model to understand the contagion process of road congestion. This departs from the classical SIR model where homogeneous mixing based on the law of mass action is assumed. For this purpose, we adopt the N-intertwined modeling framework for the SIR model based on continuous-time Markov chain analysis. In our evaluation, we used two real-world traffic datasets collected in California and Los Angeles. We compare our results against both classical and average-degreebased SIR models. Our results show better agreement between the model and actual congestion conditions and shed light on how congestion propagates across a road network. We see the potential application of insights gained from this work on the development of traffic congestion mitigation strategies.
https://eprints.bournemouth.ac.uk/39531/
Source: BURO EPrints