According to various embodiments, described herein are methods and systems for collecting data for training a load inference regression model for use in an ADV. According to one exemplary method, an ADV is manually driven on a segment of a road for a number of periods of time. During each period of time, a set of features of the ADV are recorded, including one or more features at a first time prior to a gear shift from a first gear position to a second gear position, and one or more features at a second time after the gear shift. For each of the number of periods of time, a weight of the ADV is also recorded using a weight sensor. The recorded features and the total weight of the ADV for each of the periods of time are then used to train a neural network regression model for inferring a load of the ADV in real time.
根据各种实施方式,本文描述的是收集用于训练在ADV中使用的载荷推断回归模型的数据的方法和系统。根据一个示例性方法,ADV在一段道路上手动驾驶多个时间段。在每个时间段期间,记录ADV的一组特征,包括在从第一档位换档至第二档位之前的第一时间时的一个或多个特征,以及在换档之后的第二时间时的一个或多个特征。对于多个时间段中的每个,ADV的重量也使用重量传感器进行记录。然后使用这些时间段中的每个的ADV的记录特征和总重量训练神经网络回归模型,以实时推断ADV的载荷。
GEAR BASED VEHICLE LOAD INFERENCE SYSTEM
基于齿轮的车辆载荷推断系统
2021-03-05
Patent
Electronic Resource
Chinese
IPC: | B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |