Rollover risk prediction of heavy vehicles by reliability index and empirical modelling

This paper focuses on a combination of a reliability-based approach and an empirical modelling approach for rollover risk assessment of heavy vehicles. A reliability-based warning system is developed to alert the driver to a potential rollover before entering into a bend. The idea behind the proposed methodology is to estimate the rollover risk by the probability that the vehicle load transfer ratio (LTR) exceeds a critical threshold. Accordingly, a so-called reliability index may be used as a measure to assess the vehicle safe functioning. In the reliability method, computing the maximum of LTR requires to predict the vehicle dynamics over the bend which can be in some cases an intractable problem or time-consuming. With the aim of improving the reliability computation time, an empirical model is developed to substitute the vehicle dynamics and rollover models. This is done by using the SVM (Support Vector Machines) algorithm. The preliminary obtained results demonstrate the effectiveness of the proposed approach.     

汽车降噪让汽车更安静

如果拿20年前欧洲马路上的汽车噪声比，毫无疑问，现在已经安静了10倍。最近欧盟又出台了新法令，即截至201O年要进一步大幅降低交通噪声。同时，客户对于汽车舒适性要求的不断提高，促使汽车制造商们生产更加安静的新车型。