Abstract

This paper proposes VehILux, a new vehicular mobility model based on real traffic counting data. It relies on two freely available sources of real information for the country of Luxembourg. The first source is traffic data collected by counting devices located on the Luxembourgian road network, while the second is geographical information about different types of areas: residential, industrial, commercial and other services. VehILux models vehicles commuting around the city of Luxembourg by considering two types of traffic, outer traffic with vehicles entering in the defined geographical area and inner traffic starting from residential zones located inside the geographical area. One part of the collected traffic data is used as input traffic, while another part is used to control the produced traffic and to fine-tune the model. VehILux is coupled with the microscopic road traffic simulator SUMO to produce realistic vehicular traces.

Abstract

In order to optimally allocate resources to help ensure that transport infrastructure networks continue to provide acceptable levels of service immediately, or as fast as possible, following the occurrence of extreme events, the resilience of the infrastructure need to be estimated. In this paper, a guideline is presented, based on (Adey et al., 2019), that allows managers to measure the resilience of infrastructure networks. The guideline emphasizes that to this scope it is required to define clearly: (i) the transport system, and the way to consistently measure (ii) the service and (iii) the resilience. Particular attention is paid on the fact that resilience can be measured with various degrees of precision depending on the specific problem to be addressed, the time-frame at disposition and the expertise available. Guide are then given on how to do this either using simulation, indicators, or the percentage of fulfilment of the resilience indicators.

Abstract

International audience; This paper reviews our most recent contributions in the field of cardiac deformation imaging, which includes a motion estimation framework based on the conservation of the image phase over time and an open pipeline to benchmark algorithms for cardiac strain imaging in 2D and 3D ultrasound. The paper also shows an original evaluation of the proposed motion estimation technique based on the new benchmarking pipeline.