Disruptive events occur on road networks on a daily basis and affect traffic flow. Resilience analysis aims to assess the consequences of such disruptions by quantifying the ability of a network to absorb and react to adverse events. In this paper, we advance a methodological approach based on resilience stress testing and a dynamic mesoscopic simulator. We aim to identify and rank the links most critical to the overall performance of the road network, taking into account the dynamic properties of road traffic and focusing on day-to-day disruptions. As a metric to quantify road network performance in the presence of such disruptions, we use the increase in overall travel cost. We then compare our approach with purely topological approaches. We discuss the advantages and drawbacks of the different analyzed metrics. We prove that link ranking varies greatly depending on the metric. Specifically, the proposed stress testing methodology can produce very accurate results by taking into account demand and congestion, but requires computationally intensive simulations, being therefore prohibitive even on medium-sized networks. Conversely, purely static topological metrics can be inaccurate if they do not take into account traffic demand and network dynamics. Our study highlights the need for joining traditional traffic-agnostic topological resilience analysis with demand-aware dynamic stress testing techniques.

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International tourism is steadily increasing, with 15% of travellers reporting health problems when they come back. Animal bites represent 2% of consulting causes, of which 20% are due to monkey bites. The Monkey B virus (Macacine alphaherpesvirus

L’augmentation du nombre de personnes âgées nous encourage à réfléchir à une meilleure prise en compte du vieillissement dans notre société. Leurs difficultés et leurs besoins révèlent des exigences à intégrer dans l’aménagement des espaces publics. Pauline Gauthier, cheffe de projets accessibilité au Cerema 1 , nous en décrypte les enjeux et délivre des préconisations.