methods for embedded encodings of contextual information by using a neural network

• Main Authors: MARCUS J. HUBER, PRAVEEN PALANISAMY
• Format: Patent
• Language: Chinese; English
• Published: 03.03.2020
• Subjects: CALCULATING; COMPUTING; CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PERFORMING OPERATIONS; PHYSICS; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT; TRANSPORTING; VEHICLES IN GENERAL

The present invention provides systems, Apparatuses and Methods for implementing a neural network system for controlling an autonomous vehicle (AV). The system includes: a neural network having a plurality of nodes with context to vector (context2vec) contextual embeddings to enable operations of the of the AV; a plurality of encoded context2vec AV words in a sequence of timing to embed data of context and behavior; a set of inputs which comprise: at least one of a current, a prior, and a subsequent encoded context2vec AV word; a neural network solution applied by the at least one computer todetermine a target context2vec AV word of each set of the inputs based on the current context2vec AV word; an output vector computed by the neural network that represents the embedded distributional one-hot scheme of the input encoded context2vec AV word; and a set of behavior control operations for controlling a behavior of the AV. 本发明提供了用于实现控制自主车辆(AV)的神经网络系统的系统、装置以及方法，包括：具有多个节点的神经网络，这些节点具有实现自主车辆操作的"上下文到向量(context2vec)"上