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Contributions à la résolution du transport à la demande fondées sur les systèmes multi-agents

Abstract : This thesis addresses the problem of on-demand transport (ODT). We propose three decentralized approaches based on multi-agent systems to solve this problem. The first multi-agent approach uses the algorithm A* in order to find an optimal solution in a road network characterized by constant travel speeds. Experiments are carried out on the road network of a Lebanese city called Tripoli and good results are obtained. However, in a city like Tripoli, travel speeds depend heavily on the dynamic situation of road traffic. For this reason, the second multi-agent approach massif comes to remedy the first taking into account the evolution of traffic. The road network is considered as dynamic deterministic. It is characterized by travel speeds dependent on the usual traffic situation. These speeds are pre-calculated on the basis of historical knowledge of road traffic. The experimental results show that the number of dissatisfied customers is greater than 50 % if the speeds are considered to be constant. Nevertheless, historical knowledge is not sufficient to reflect the actual traffic situation, especially in case of an unexpected event (such as an accident) occurring on the network. For this, a self-organized massive multi-agent approach is proposed. The road network is considered as a dynamic stochastic characterized by travel speeds dependent on the actual traffic situation. This approach represents the dynamic organization of traffic on its scale based on historical traffic knowledge and real-time traffic information. Vehicle trajectories and their durations are calculated and recalculated online whenever an unexpected event disrupts the usual traffic situation. The experimental results show that up to 39 % of customers will be dissatisfied if a road accident is not considered during the processing of their demands. Otherwise, 50 % to 100 % of these customers are satisfied.
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Submitted on : Wednesday, December 13, 2017 - 9:39:43 AM
Last modification on : Thursday, November 28, 2019 - 4:05:15 AM

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  • HAL Id : tel-01661358, version 2

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Anas Malas. Contributions à la résolution du transport à la demande fondées sur les systèmes multi-agents. Intelligence artificielle [cs.AI]. Normandie Université, 2017. Français. ⟨NNT : 2017NORMIR07⟩. ⟨tel-01661358v2⟩

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