Multiagent Routing Simulation with Partial Smart Vehicles Penetration
Summary
The invention and implementation of smart connected cars will change the way how the transportation networks in cities around the world operate. This technological shift will not happen instantaneously—for many years, both human-driven and smart connected vehicles will coexist. In this paper, using a multiagent simulation framework, we model a complex urban transportation system that involves heterogeneous participants. Vehicles are assigned into two groups: the first one consists of smart cars and the second one involves regular ones. Vehicles in the former group are capable of rerouting in response to changes in the observed traffic while regular ones rely on historical information only. The goal of the paper is to analyze the effect of changing smart cars penetration on system characteristics, in particular, the total travelling time. The smart car routing algorithm proposed in this paper reduced travelling time up to 30%. Analysis has shown that the behaviour of the system and optimal configuration of underlying algorithms change dynamically with smart vehicles penetration level.
Keywords
Vehicular networks, multi-agent simulation, smart cars routing
2021 Journal Impact Factor: 2.249
Publication date: March 3, 2020
Links
References
APA | Kamiński, B., Kraiński, Ł., Mashatan, A., Prałat, P., & Szufel, P. (2020). Multiagent Routing Simulation with Partial Smart Vehicles Penetration. Journal of Advanced Transportation, 2020, 3152020. |
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BibTeX | @article{Kaminski2020MultiagentRS, title={Multiagent Routing Simulation with Partial Smart Vehicles Penetration}, author={Kami{\'n}ski, Bogumi{\l} and Krai{\'n}ski, {\L}ukasz and Mashatan, Atefeh and Pra{\l}at, Pawe{\l} and Szufel, Przemys{\l}aw}, journal={Journal of Advanced Transportation}, year={2020}, volume={2020}, doi= {10.1155/2020/3152020} } |
DOI | https://doi.org/10.1155/2020/3152020 |
IEEE | B. Kamiński, Ł. Kraiński, A. Mashatan, P. Prałat, and P. Szufel, “Multiagent Routing Simulation with Partial Smart Vehicles Penetration,” Journal of Advanced Transportation, vol. 2020, p. 3152020, Mar. 2020. |
ISSN | 0197-6729 |
Funding
This research was supported, in part, through generation contributions by NXM Labs Inc. (external link, opens in new window) , The Fields Institute for Research in Mathematical Sciences (external link) (formerly known as The Fields Institute Centre for Quantitative Analysis and Modelling), and Natural Sciences and Engineering Research Council of Canada (external link, opens in new window) .