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.

An autonomous driving system for an autonomous vehicle includes a plurality of on-board autonomous sensors that sense data related to operation of the autonomous vehicle and a surrounding environment and an automated driving controller in electronic communication with the plurality of on-board autonomous sensors. The automated driving controller is instructed to receive an indication one or more of the plurality of on-board autonomous sensors are non-functional and a secondary autonomous sensor system including one or more replacement sensors are installed. The automated driving controller is instructed to verify the secondary autonomous sensor system based on a security check and perform a redundancy check between the one or more replacement sensors and the plurality of on-board autonomous sensors. In response to determining the one or more replacement sensors are valid based on the redundancy check, the automated driving controller operates the autonomous vehicle in a limp home mode.

A control system for a vehicle includes wheel slip control loop including a wheel slip controller configured to control wheel slip based on wheel speed measured at one or more wheels of the vehicle. A wheel flare control loop includes a wheel flare controller configured to control wheel flare based on transmission output speed at an output of a transmission of the vehicle. A controller is configured to select one of the wheel slip controller to control the wheel slip and the wheel flare controller to control the wheel flare during operation of the vehicle.

A control device includes control circuits of a plurality of systems. When a transition condition is established, the control circuits of the systems make transition of a driving mode from a first driving mode to a second driving mode, and when a return condition is established in a state in which the driving mode has transitioned to the second driving mode, the control circuits of the systems make transition of the driving mode from the second driving mode to the first driving mode while gradually changing the current command values of the control circuits’ own systems toward the current command values before the adjustment.

A method for determining a driving state of a vehicle includes determining a torque command of a vehicle drive apparatus based on vehicle driving information collected during driving of the vehicle, determining an acceleration error defined as a difference between a reference longitudinal acceleration of the vehicle interlocked with the torque command and a measured longitudinal acceleration of the vehicle, determining an acceleration disturbance rate defined as a difference between an actual rotational acceleration of the vehicle drive and a reference drive apparatus rotational acceleration interlocked with the torque command based on the determined torque command, integrating the determined acceleration disturbance rate to determine the acceleration disturbance, and determining a current vehicle driving state of the vehicle based on the determined acceleration error, the determined acceleration disturbance rate and the acceleration disturbance.

The disclosed technology provides solutions for improving work ticketing triage and in particular, for improving the triage of work orders for detected failure events (or predicted failure events) for a fleet of vehicles, such as a fleet of autonomous vehicles (AVs). In some aspects, a process of the disclosed technology can include steps for receiving field data, processing the field data to identify two or more potential failure events associated with at least one AV from among one or more AVs, and automatically generating a work order for each of the two or more potential failure events. In some aspects, the process can further include steps for calculating a dynamic priority number for each of the two or more potential failure events and sorting the work orders based on the dynamic priority. Systems and machine-readable media are also provided.

An approach for assisting users with disabilities in an emergency situation relating to a vehicle is disclosed. The approach determines the profile of the passenger in a vehicle by noting preferences and disabilities associated with the passenger. After a vehicle accident, the approach determines the condition of the vehicle and the condition of the passenger. Based on various information received, the approach creates an action list of solutions for the passenger, wherein the action list has assigned dynamic risk scores. The approach determines the best solution based on the risk scores and selects the best solution from the action list.

Disclosed embodiments relate to adjusting vehicle Electronic Control Unit (ECU) software versions. Operations may include receiving a prompt to adjust an ECU of a vehicle from executing a first version of ECU software to a second version of ECU software; configuring, in response to the prompt and based on a delta file corresponding to the second version of ECU software, the second version of ECU software on the ECU in the vehicle for execution; and configuring, in response to the prompt, the first version of ECU software on the ECU in the vehicle to become non-executable.

Disclosed embodiments relate to adjusting vehicle Electronic Control Unit (ECU) software versions. Operations may include receiving a prompt to adjust an ECU of a vehicle from executing a first version of ECU software to a second version of ECU software; configuring, in response to the prompt and based on a delta file corresponding to the second version of ECU software, the second version of ECU software on the ECU in the vehicle for execution; and configuring, in response to the prompt, the first version of ECU software on the ECU in the vehicle to become non-executable.

It is presented a method performed in a vehicle action determiner for determining an undesired action of a first vehicle and a resulting action. The method comprises: detecting that a first user is focusing on the first vehicle; acquiring brain activity data of the first user; determining a negative reaction of the first user based on the brain activity data; determining when the first vehicle is performing an undesired action based on the first user focusing on the first vehicle and the negative reaction of the first user; determining the resulting action taken by an autonomous vehicle, based on the first vehicle performing the undesired action; and triggering the autonomous vehicle to perform the resulting action.