Abstract

International audience; Intelligent transportation systems that distribute information between roadside infrastructures and vehicles are one of the most promising solutions to the problem of traffic congestion. When most existing ITS solutions are centralized and information-complete, we propose PDLAIS-a Partial, Decentralized and Locally Autonomous Strategy, tested with an application called Smooth Way, allowing drivers to customize and improve their travel time and/or fuel consumption when traveling. Our study shows that, with only 2% of independently equipped intersections, a global improvement in the fuel consumption induces a reduction of 10% of the total travel time and 25% of the global waiting time. Local decisions with pertinent partial knowledge of the network are still 5 − 7% close to the performance of a centralized solution.

Abstract

Global local analysis is a part of the structural analysis that allows to study, with an iterative solution, a coarse global linear model with a specific zone. This zone is defined as a local model with fine mesh and a non-linear behaviour such as crack propagation. However, the current trend in Global Local analysis is to impose displacements on the fine model to later obtain the reactions that will be applied to the global model for each iteration (Primal to Dual solution algorithm). Therefore, we propose a mixed analysis in the local and global models through the application of Robin conditions on the interface, allowing a higher grade of flexibility for the case of the patch or fine model with crack propagation behaviour. As a result, the algorithm converges successfully, presenting kinematic compatibility and good results with respect to the Monolithic (non-decomposed) model. Finally, a sensitivity analysis is performed on some variables regarding the crack propagation for 2D models. Finally, the proposed methodology also allows to improve the performance of the method for cracked models or other nonlinearities when compared with the current global local analysis, presented in the state of the art.