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. 2023 Mar 6;18(3):e0281658.
doi: 10.1371/journal.pone.0281658. eCollection 2023.

Dealing with mixed and non-normative traffic. An agent-based simulation with the GAMA platform

Arnaud Saval  1 , Duc Pham Minh  2   3 , Kevin Chapuis  4 , Pierrick Tranouez  1 , Clément Caron  5 , Éric Daudé  5 , Patrick Taillandier  2   3   6
Affiliations

Dealing with mixed and non-normative traffic. An agent-based simulation with the GAMA platform

Arnaud Saval et al. PLoS One. .

Abstract

Continuous improvement in computing power allowed for an increase of the scales micro-traffic models can be used at. Among them, agent-based frameworks are now appropriate for studying ordinary traffic conditions at city-scale, but remain difficult to adapt, especially for non-computer scientists, to more specific application contexts (e.g., car accidents, evacuation following a natural disaster), that require integrating particular behaviors for the agents. In this paper, we present a built-in model integrated into the GAMA open-source modeling and simulation platform, allowing the modeler to easily define traffic simulations with a detailed representation of the driver's operational behaviors. In particular, it allows modelling road infrastructures and traffic signals, change of lanes by driver agents and less normative traffic mixing car and motorbike as in some South East Asian countries. Moreover, the model allows to carry out city-level simulations with tens of thousands of driver agents. An experiment carried out shows that the model can accurately reproduce the traffic in Hanoi, Vietnam.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. A road network composing of roads and intersections.
Fig 2
Fig 2. The “lane states” of several vehicles driving on two linked roads.
Note that the right-most vehicle is occupying lanes with indices 1 and 2 from its point of view, but the latter is in fact lane 1 on the linked road.
Fig 3
Fig 3. Average speed value according to the number of cars.
Fig 4
Fig 4. Tay Son street site (based on OpenStreetMap data): The green circle represents the input point (WGS84 coordinates: (105.8224 21.005)), and the red circle the output (WGS84 coordinates: (105.8236 21.0076)).
Fig 5
Fig 5. Chua Boc street site (based on OpenStreetMap data): The green circle represents the input point (WGS84 coordinates: (105.8252 21.0089)), and the red circle the output point (WGS84 coordinates: (105.831 21.0062)).
Fig 6
Fig 6. Count of vehicles at the input and output points for the Tay Son site (time series were smoothed out using moving average with a window size of 10s).
Fig 7
Fig 7. Count of vehicles at the input and output points for the Chua Boc site (time series were smoothed out using moving average with a window size of 10s).
Fig 8
Fig 8. Simulated results for the Tay Son site.
Motorcycle and car counts for the 100 simulations with [44] model (time series were smoothed out using moving average with a window size of 10s). In red, the mean values.
Fig 9
Fig 9. Simulated results for the Tay Son site.
Motorcycle and car counts for the 100 simulations with our model (time series were smoothed out using moving average with a window size of 10s). In red, the mean values.
Fig 10
Fig 10. Observed and simulated results (with [44] and our models) for the Tay Son site.
Motorcycle and car counts—mean of the simulation (time series were smoothed out using moving average with a window size of 10s.
Fig 11
Fig 11. Simulated results for the Chua Boc site.
Motorcycle and car counts for the 100 simulations with [44] model (time series were smoothed out using moving average with a window size of 10s). In red, the mean values.
Fig 12
Fig 12. Simulated results for the Chua Boc site.
Motorcycle and cars counts for the 100 simulations with our model (time series were smoothed out using moving average with a window size of 10s). In red, the mean values.
Fig 13
Fig 13. Observed and simulated results (with [44] and our models) for the Chua Boc site.
Motorcycle and car counts—mean of the simulation (time series were smoothed out using moving average with a window size of 10s.
See this image and copyright information in PMC

References

    1. Hoogendoorn SP, Bovy PHL. State-of-the-art of vehicular traffic flow modelling. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering. 2001;215(4):283–303. doi: 10.1177/095965180121500402 - DOI
    1. Wardrop JG, Whitehead JI. Correspondence. Some theoretical aspects of road traffic research. Proceedings of the Institution of Civil Engineers. 1952;1(5):767–768. doi: 10.1680/ipeds.1952.11362 - DOI
    1. Kerner BS. The physics of traffic. Physics World. 1999;12(8):25. doi: 10.1088/2058-7058/12/8/30 - DOI
    1. Prigogine I, Herman R. Kinetic theory of vehicular traffic; 1971.
    1. DeAngelis DL, Grimm V. Individual-based models in ecology after four decades. F1000prime reports. 2014;6. doi: 10.12703/P6-39 - DOI - PMC - PubMed

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