Abstract: The present disclosure provides a risk assessment method of water inrush in tunnels constructed in water-rich grounds. The method includes the following steps: simulating a tunnel excavation process by finite element software MIDAS GTS NX and fluid-structure interaction; according to a research method of control variables, analyzing effects of a groundwater level, an elastic modulus and advanced pipe shed grouting on the stability of surrounding rock, and improving an algorithm of a radial basis function (RBF) neural network using a Grey Relation Analysis (GRA)-based Partitioning Around Medoid (PAM) clustering algorithm to assess risks of water inrush occurring in Qingdao area.

Abstract: The present disclosure provides a multi-factor quantitative analysis method for deformation of a neighborhood tunnel. The method includes the following steps: analyzing monitoring data generated at a tunnel site; simulating collapse occurring at a shallow buried section of a tunnel; determining the degree of influence of each factor on the tunnel and a stratum; and determining quantitative influence of each factor on tunnel deformation. The present disclosure can not only provide an accurate theoretical basis for the construction of the shallow buried section of the small-distance tunnel, but also guarantee safety and cost saving during tunnel construction.

Abstract: A system and method for proximate vehicle intention prediction for autonomous vehicles are disclosed. A particular embodiment is configured to: receive perception data associated with a host vehicle; extract features from the perception data to detect a proximate vehicle in the vicinity of the host vehicle; generate a trajectory of the detected proximate vehicle based on the perception data; use a trained intention prediction model to generate a predicted intention of the detected proximate vehicle based on the perception data and the trajectory of the detected proximate vehicle; use the predicted intention of the detected proximate vehicle to generate a predicted trajectory of the detected proximate vehicle; and output the predicted intention and predicted trajectory for the detected proximate vehicle to another subsystem.