Abstract
This paper represents a novel solution to the traffic and bus transit congestion issue by proposing a multimodal route recommendation framework. The framework relies on simulating the traffic and transit data, modeling the multimodal road network, computing a congestion index for each road segment and finally providing route plans for the framework’s users. As a result, road congestion can be diminished and the use of public transport can be encouraged. The multimodal network is represented using a weighted multi-layered graph, where the weights changes depending on the computed congestion indexes. A novel method is suggested to calculate the congestion indexes, it takes into consideration multiple aspects of congestion by combining three commonly used congestion measures. For the multimodal least congested pathfinding, a solution is proposed to provide relevant recommendations; it takes into account all viable constraints for an optimal route suggestion.
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Berrouk, S., Sadgal, M. (2020). A Multimodal Route Recommendation Framework Based on Urban Congestion Management. In: Hamlich, M., Bellatreche, L., Mondal, A., Ordonez, C. (eds) Smart Applications and Data Analysis. SADASC 2020. Communications in Computer and Information Science, vol 1207. Springer, Cham. https://doi.org/10.1007/978-3-030-45183-7_8
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DOI: https://doi.org/10.1007/978-3-030-45183-7_8
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