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The durability performance of brake hoses is a crucial issue for such components. Accelerated fatigue testing of brake hoses is necessary for understanding achievable lifetime, actually computation of durability is quite cumbersome due to the many different materials the hoses are made from. Despite SAE standards are available, accelerated testing of brake hoses subject to actual torsional and bending stresses seem important to provide relevant feedback to designers. In this paper, an innovative methodology for assessing the fatigue behavior of brake hoses of road vehicles is proposed. A dynamic testbed is specifically designed and realized, able to reproduce the actual assembly conditions of the hoses fitted into a vehicle suspension. The designed testbed allows to replicate actual loading conditions on the brake hoses by simulating the vertical dynamics and steering of the suspension system together with brake pressure.

The rising environmental awareness has led to a growing interest in electric and lightweight vehicles. Four-wheeled Ultra-Efficient Lightweight Vehicles (UELVs) have the potential to improve the quality of urban life, reduce environmental impact and make efficient use of land. However, the safety of these vehicles in terms of dynamic behaviour needs to be better understood. This paper aims to provide a quantitative assessment of the handling behaviour of UELVs. An analytical single-track model and a numerical simulation by VI-CarRealTime are analysed to evaluate the dynamic performance of a UELV compared to a city car. This analysis shows that the lightweight vehicle has a higher readiness (i.e. lower reaction time to yaw rate) for step steering and lower steering effort (i.e. higher steady-state value). Experimental analysis through real-time driving sessions on the Dynamic Driving Simulator assesses vehicle responses and subjective perception for different manoeuvres.

Roundabouts are intersections at which automated cars seem currently not performing sufficiently well. Actually, sometimes, they get stuck and the traffic flow is seriously reduced. To overcome this problem a V2N-N2V (vehicle-to-network-network-to-vehicle) communication scheme is proposed. Cars communicate via 5G with an edge computer. A cooperative machine-learning algorithm orchestrates the traffic. Automated cars are instructed to accelerate or decelerate with the triple aim of improving the traffic flow into the roundabout, keeping safety constraints, and providing comfort for passengers on board of automated vehicles. In the roundabout, both automated cars and human-driven cars run. The roundabout scenario has been simulated by SUMO. Additionally, the scenario has been reconstructed into a dynamic driving simulator, with a real human driver in a virtual reality environment. The aim was to check the human perception of traffic flow, driving safety and driving comfort.