Method for monitoring operation of a technical object, wherein a) a first orientation of the first acceleration sensor in the form of a position vector is determined, b) the mathematical model for operation of the object is generated and trained, c) the first acceleration sensor is disassembled and a three-axle replacement acceleration sensor is assembled with a new orientation on the object, d) acceleration values are detected, e) respective indicator values are calculated from the temporal course of the detected acceleration values of the replacement acceleration sensor, f) a replacement vector is determined from the indicator values and a differential vector between the replacement vector and the position vector of the first acceleration sensor determined in step b) is determined, and g) the model during operation of the object for the position vector in the orientation of the replacement vector is applied by taking into account the differential vector.

A system includes a processor and a memory. The memory stores instructions executable by the processor to determine an action for a vehicle based on an identified risk condition, to determine a minimum time for performing the action, and based on data including a vehicle battery state of charge, an outdoor temperature, and a vehicle mode of operation, to determine an available electrical power for performing the action. The instructions further include instructions to determine maximum permissible electrical energy discharge rate based on the minimum time for performing the action and the determined available electrical power, to determine a load control plan for a plurality of electrical devices in the vehicle based on the maximum permissible electrical energy discharge rate, an electrical load status of the vehicle, and load priority data; and to execute the determined load control plan.

System, methods, and other embodiments described herein relate to a training system to train a driver about occurrences of anomalous driving events of automated vehicle systems. In one embodiment, a method includes determining, upon receiving a selection of a vehicle behavior from one or more anomalous driving events and a detected state change signal, whether the vehicle behavior affects one or more entities. The method includes assessing a state of the one or more entities to simulate the vehicle behavior according to a safety standard. The method includes triggering simulation of the vehicle behavior if the state satisfies a threshold. The method includes simulating the vehicle behavior by at least controlling the vehicle to simulate the vehicle behavior during automated driving of the vehicle.

An autonomous mobile device (AMD) includes an active braking circuit able to quickly stop the movement of the AMD. For example, the device may stop to avoid an obstacle, upon determining a failure of an internal component, upon receipt of a command, and so forth. Responsive to a signal to stop, an active braking circuit uses sensor data from a driving motor moving with a first rotation to actively commutate that motor to an opposite rotation, bringing the AMD quickly to a stop. In some implementations, the active braking circuit may include an independent power source and motor drivers and operate as a backup to a primary braking system.

According to various embodiment, described herein are methods and systems for reliably detecting malfunctions in a variety of software or hardware components in an autonomous driving vehicle (ADV). In one embodiment, a redundant system can be provided on an independent computing device in an ADV to check for malfunctions in a number of software or hardware components. When no malfunction occurs in the ADV, an autonomous driving system (ADS) in the ADV operates to drive the ADV, while the redundant system can monitor the ADS in a standby mode. In the event of a malfunction, the redundant system can take over the control of the ADV, and take appropriate actions based on a severity level of the malfunction.

Disclosed embodiments relate to performing updates to Electronic Control Unit (ECU) software while an ECU of a vehicle is operating. Operations may include receiving, at the vehicle while the ECU of the vehicle is operating, a software update file for the ECU software; writing, while the ECU is operating, the software update file into a first memory location in a memory of the ECU while simultaneously executing a code segment of existing code in a second memory location in the memory of the ECU; and updating a plurality of memory addresses associated with the memory of the ECU based on the software update file and without interrupting the execution of the code segment currently being executed in the second memory location in the memory of the ECU.

A substitution apparatus for installation in a vehicle in which a plurality of in-vehicle control apparatuses are implemented, the substitution apparatus including a control unit and a substitute unit. The control unit is configured to control the substitute unit based on transmission data transmitted from the in-vehicle control apparatuses, specify an abnormal in-vehicle control apparatus based on the transmission data, disable the specified abnormal in-vehicle control apparatus, and apply, to the substitute unit, a program for exhibiting functions otherwise normally executed by the specified abnormal in-vehicle control apparatus. The substitute unit is configured to substitute for the disabled in-vehicle control apparatus by executing the applied program.

A vehicle drive assist apparatus includes a traveling environment information acquisition unit, a traveling state information acquisition unit, and a traveling control unit. The traveling environment information acquisition unit acquires traveling environment information. The traveling state information acquisition unit acquires traveling state information. The traveling control unit includes a malfunction detector and a takeover request processor. The malfunction detector detects a malfunction in the traveling environment information acquisition unit and the traveling state information acquisition unit. The takeover request processor executes a takeover request process for manual driving in a case where the malfunction is detected. The takeover request processor includes a waiting time measurement section and an output restricting section. The waiting time measurement section measures a waiting time from detection of the malfunction to transition to the manual driving. The output restricting section restricts an output of a drive source during the waiting time.

An autonomous vehicle is operated using a main autonomy system that analyzes data collected by a sensor system of the autonomous vehicle to determine a trajectory of travel of the autonomous vehicle, and wherein the main autonomy system provides instructions to a propulsion system of the autonomous vehicle to cause the propulsion system to navigate the autonomous vehicle according to the trajectory. In response to determining that navigating the autonomous vehicle according to the trajectory is likely to result in collision, instructions are provided from a parallel autonomy system to the propulsion system to cause the autonomous vehicle to avoid collision. In response to detecting a fault in the main autonomy system, control of the propulsion system is provided from the main autonomy system to a failover autonomy system, wherein the failover autonomy system is configured to override the propulsion system.

A system and method of detecting and responding to a failure of one or more vehicle components, the method including: receiving system input at a failure detection module regarding the one or more vehicle components; determining a system state through use of one or more onboard vehicle sensors; obtaining a nominal state transition matrix and a nominal state input matrix; calculating a present state transition matrix estimate and a present state input matrix estimate based on the nominal state transition matrix, the nominal state input matrix, the system input, and a sampled state derivative; detecting a failure of at least one of the vehicle components based on one or more component parameters of the present state transition matrix estimate and/or the present state input matrix estimate; and performing a vehicle action in response to the detection of the failure.