Research Article
Modelling and Multi-agent Simulation of Urban Road Network
@INPROCEEDINGS{10.1007/978-3-031-34896-9_2, author={Aurel Megnigbeto and Ars\'{e}ne Sabas and Jules Degila}, title={Modelling and Multi-agent Simulation of Urban Road Network}, proceedings={Towards new e-Infrastructure and e-Services for Developing Countries. 14th EAI International Conference, AFRICOMM 2022, Zanzibar, Tanzania, December 5-7, 2022, Proceedings}, proceedings_a={AFRICOMM}, year={2023}, month={6}, keywords={Smart mobility Multi-agent system Road network simulation}, doi={10.1007/978-3-031-34896-9_2} }- Aurel Megnigbeto
Arsène Sabas
Jules Degila
Year: 2023
Modelling and Multi-agent Simulation of Urban Road Network
AFRICOMM
Springer
DOI: 10.1007/978-3-031-34896-9_2
Abstract
In many African cities, there is a constant increase in road network usage, while we notice an absence of proper means of traffic regulation. Decision-makers should make decisions about road network improvement to ease the management and availability of the road network. They must consider the smart city’s concept because of its features that will enable smart mobility. The most popular and tedious method to provide mobility data is the traditional traffic count, which is used in many cities. However, this method does not make it possible to assess mobility according to travel scenarios and requires significant financial and human resources compared to a computer simulations-based way.
We propose, a simulation tool based on multi-agent technology to facilitate the testing of mobility scenarios and to help in decision-making about traffic regulation. The tool we designed has been applied to the city of Cotonou to simulate mobility and to have a fully functional representation of the existing road network. This virtual representation can help to identify the key metrics decision-makers can leverage to improve the traffic and get an insight into the city road network. To test it, we simulated the traffic by considering a travel scenario: the home-work journey of the citizens of Cotonou. The results help in decisions making to improve mobility under this scenario. Even though our example is applied to the city of Cotonou, our model from its design is flexible enough to support the peculiarity of African cities.
