Scalable Coordinated Intelligent Traffic Light Controller for Heterogeneous Traffic Scenarios Using UPPAAL STRATEGO

Thamilselvam, B and Kalyanasundaram, Subrahmanyam and Rao, M V Panduranga (2021) Scalable Coordinated Intelligent Traffic Light Controller for Heterogeneous Traffic Scenarios Using UPPAAL STRATEGO. In: 2021 International Conference on COMmunication Systems and NETworkS, COMSNETS 2021, 5 January 2021 - 9 January 2021.

Full text not available from this repository. (Request a copy)


We propose a new approach for coordinating traffic flows in large cities that helps in reducing the travel time and carbon emissions from vehicles. We use the UPPAAL STRATEGO tool chain that leverages statistical model checking and machine learning for synthesizing optimal traffic coordination strategies. Our approach employs a hierarchical view of the city with two levels-individual traffic intersections and area controllers. While the choice of a phase at an intersection is decided locally, the phase threshold is decided at the level of an area consisting of several intersections. The algorithm and models that we report in this paper are a nontrivial generalization of previous approaches that used UPPAAL STRATEGO. This generalization allows scaling to large cities with several traffic intersections, with improved results.We compare our approach against other techniques including fixed-time and fully-actuated controllers. Experiments show that the it performs better in terms of waiting time and carbon emissions, especially in scenarios of changing traffic loads. Our approach also reduces overall and individual delays at intersections.

[error in script]
IITH Creators:
IITH CreatorsORCiD
Thamilselvam, BUNSPECIFIED
Kalyanasundaram, SubrahmanyamUNSPECIFIED
Rao, M V PandurangaUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Area controllers; Carbon emissions; Heterogeneous traffic; Individual traffic; Intelligent traffics; Statistical model checking; Traffic coordination; Traffic intersections
Subjects: Computer science
Depositing User: . LibTrainee 2021
Date Deposited: 15 Jul 2021 04:31
Last Modified: 15 Jul 2021 04:31
Publisher URL:
Related URLs:

Actions (login required)

View Item View Item
Statistics for RAIITH ePrint 8327 Statistics for this ePrint Item