The disclosed technology provides solutions for validating operation of a sensor assembly by performing an assembly test. In some aspects, a process of performing the assembly test includes steps for collecting motor controller measurements, wherein the motor controller measurements include an amount of current supplied to a motor coupled when performing a sensor sweep, calculating an average current drawn by the motor based on the current measurements, and calculating a peak current drawn by the motor based on the current measurements. In some aspects, the process can further include steps for determining if the sensor assembly passes the sensor assembly test based on the average current drawn and the peak current drawn. Systems and machine-readable media are also provided.

Methods and systems are disclosed for cross-validating a second sensor with a first sensor. Cross-validating the second sensor may include obtaining sensor readings from the first sensor and comparing the sensor readings from the first sensor with sensor readings obtained from the second sensor. In particular, the comparison of the sensor readings may include comparing state information about a vehicle detected by the first sensor and the second sensor. In addition, comparing the sensor readings may include obtaining a first image from the first sensor, obtaining a second image from the second sensor, and then comparing various characteristics of the images. One characteristic that may be compared are object labels applied to the vehicle detected by the first and second sensor. The first and second sensors may be different types of sensors.

A vehicle includes a storage device configured to store an estimation algorithm configured to output a degree of deterioration of a component mounted on the vehicle in response to an input of a value of a parameter related to the component, a sensor configured to detect the value of the parameter, and a control device. The control device is configured to execute a performance test by autonomous driving of the vehicle, acquire data indicating performance of the component during the performance test, and update the estimation algorithm by using the data acquired during the performance test.

Process for clearing an autonomous machine including first evaluating operation at a high curvature offline location. Following acceptable operation, the machine is placed into service and evaluated at a worksite. Following acceptable worksite operation, online operating speed of the machine is increased incrementally, and performance reevaluated. Following acceptable performance characteristics, online operating speed of the machine continues to be increased and revaluated until the machine reaches maximum designated operating speed, or is evaluated as unacceptable, in which case the machine continues to operate at the last acceptable online operating speed and identifies the unacceptable performance characteristic for further evaluation.

A mobile object control method including: recognizing physical objects near a mobile object and a route shape; generating a target trajectory based on a result of the recognition and cause the mobile object to travel autonomously along the target trajectory; and determining that an abnormality has occurred in a control system for causing the mobile object to travel autonomously by performing the recognition when a time period from a timing when a degree of deviation between a reference target trajectory determined by the route shape and serving as a reference for generating the target trajectory and a position of the mobile object is greater than or equal to a predetermined degree to a timing when the degree of deviation is less than the predetermined degree is greater than or equal to a first predetermined time period and output a determination result.

Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. This may include receiving, by one or more processors of the vehicle, first information identifying a current relative humidity measurement within a sensor housing of a vehicle having an autonomous driving mode. The relative humidity measurement and pre-stored environmental map information may be used by the one or more processors to estimate a condition of a sensor within the sensor housing at a future time. This estimated condition may be used by the one or more processors to control the vehicle.

The invention relates to a control device for a driver assistance system, wherein the control device comprises a sensor interface via which the control device can be connected to at least one sensor module to receive data from the at least one sensor module, a power processor which is adapted to detect objects and to provide object data based on the data from the at least one sensor module, and a system interface via which the control device can be connected to a higher-level control device of the driver assistance system for forwarding object data provided by the power processor.

A system for controlling an intelligent network vehicle is provided, and the system comprises a sensor group configured to obtain sensor information; a sensing and positioning module configured to obtain sensing information and positioning information based on the sensor information; a planning and control module configured to determine vehicle planning control information based on the sensing information and the positioning information; a safety control module configured to determine safety control information based on the sensing information and the positioning information; a function assessment module configured to determine a vehicle state assessment result; a risk assessment module configured to determine a risk assessment result; a logical arbitration module configured to determine vehicle execution information by arbitrating the vehicle planning control information and the safety control information; and an execution module configured to control the vehicle driving based on the vehicle execution information.

A vehicle system, including: a steering system; and a longitudinal-force application system including longitudinal-force application actuators configured to apply longitudinal forces respectively to one or more left-side wheels and one or more right-side wheels and a longitudinal-force controller configured to control the longitudinal-force application actuators to control the longitudinal forces applied respectively to the one or more left-side wheels and the one or more right-side wheels;, and an onboard power source device including a main power source and a secondary power source. When the main power source fails to supply electric power to the longitudinal-force application system and the steering system, the longitudinal-force controller controls the longitudinal-force application actuators to control a difference between the longitudinal force applied to the one or more left-side wheels and the longitudinal force applied to the one or more right-side wheels, thereby turning the vehicle.

Systems and methods of autonomously controlling a vehicle across the grip driving and drift driving operating ranges, are provided. The contemplated autonomous control can be effectuated using a closed-loop control system. In some embodiments, closed-loop control may be accomplished by deriving control laws involving sideslip angle, yaw rate, wheel speed, and other vehicle states. These control laws may be used to control the vehicle in a stable drift condition.