Aspects of the disclosure relate to a vehicle having an autonomous driving mode and a manual driving mode. The vehicle may include a steering system having one or more processors configured to control the orientation of the one or more wheels based on control commands. The vehicle may also include an autonomous driving control system configured to control the vehicle in an autonomous driving mode by generating the control commands and to send the control commands to the steering system. In addition, the steering system may thermally derate the steering system based on first temperature information for the steering system when the vehicle is operating in a manual drive mode, and the autonomous driving control system may thermally derate the steering system based on second temperature information for the steering system when the vehicle is operating in the autonomous driving mode.

An apparatus for controlling a vehicle capable of performing autonomous driving is provided. The apparatus includes an autonomous driving device that executes the autonomous driving and generates a transition demand when it is impossible to execute the autonomous driving. A driving controller performs a minimum risk maneuver (MRM) of applying a deceleration pattern differently depending on a driving environment of the vehicle, when the transition demand is generated, but when driving manipulation by a driver does not occur. A subsequent safety ensuring function is performed according to the MRM for the driver to recognize the MRM, and a drive mode of the vehicle is changed to a drive mode with a rapid response speed to acceleration or steering.

Techniques relating to monitoring map consistency are described. In an example, a monitoring component associated with a vehicle can receive sensor data associated with an environment in which the vehicle is positioned. The monitoring component can generate, based at least in part on the sensor data, an estimated map of the environment, wherein the estimated map is encoded with policy information for driving within the environment. The monitoring component can then compare first information associated with a stored map of the environment with second information associated with the estimated map to determine whether the estimated map and the stored map are consistent. Component(s) associated with the vehicle can then control the object based at least in part on results of the comparing.

Devices, systems, and methods for a vehicular safety system in autonomous vehicles are described. An example method for safely controlling a vehicle includes selecting, based on a first control command from a first vehicle control unit, an operating mode of the vehicle, and transmitting, based on the selecting, the operating mode to an autonomous driving system, wherein the first control command is generated based on input from a first plurality of sensors, and wherein the operating mode corresponds to one of (a) a default operating mode, (b) a minimal risk condition mode of a first type that configures the vehicle to pull over to a nearest pre-designated safety location, (c) a minimal risk condition mode of a second type that configures the vehicle to immediately stop in a current lane, or (d) a minimal risk condition mode of a third type that configures the vehicle to come to a gentle stop.

Techniques for providing remote assistance to a vehicle are discussed. The techniques include receiving, from a vehicle, an indication of an event and displaying, on a display and to a user, a portion of an environment including the vehicle. The techniques further determine a valid region in the portion of the environment associated with a location at which the vehicle is capable of navigating. The techniques also display, on the display a footprint of the vehicle, where the footprint is associated with a position and orientation. The techniques further include transmitting the position and orientation of the footprint to the vehicle, which causes the vehicle to traverse in the environment to the position and orientation.

A vehicular control system includes a plurality of electronic control units (ECUs), each providing a respective quantity of computational units representative of an amount of processing power of the respective ECU. The ECUs operate a vehicle in a nominal autonomous operational mode when a sum of the quantity of computational units exceeds a threshold. The system, while the ECUs operate the vehicle in the nominal autonomous operational mode, and responsive to detecting a failure of one of the ECUs, determines whether a sum of the quantity of computational units of the remaining ECUs that do not have a failure exceeds the threshold. The ECUs, responsive to the system determining that the sum of the quantity of computational units of the remaining ECUs fails to exceed the threshold, switches from operating the vehicle in the nominal autonomous operational mode to operating the vehicle in a degraded autonomous operational mode.

According to one embodiment, a transport service method comprises organizing a vehicle group of a plurality of self-driving vehicles in which a parameter value inherent to vehicles falls within a predetermined range, and controlling cooperative travel of the self-driving vehicles in the vehicle group to perform transport service of baggage, persons, animals, and the like.

In one embodiment, a computing system of a vehicle may receive perception data associated with a scenario encountered by a vehicle while operating in an autonomous driving mode. The system may identify the scenario based at least on the perception data. The system may generate a performance metric associated with a vehicle navigation plan to navigate the vehicle in accordance with the identified scenario. In response to a determination that the performance metric associated with the vehicle navigation plan fails to satisfy one or more criteria for navigating the vehicle in accordance with the identified scenario, the system may trigger a disengagement operation related to disengaging the vehicle from the autonomous driving mode. The system may generate a disengagement record associated with the triggered disengagement operation. The disengagement record may include information associated with the identified scenario encountered by the vehicle related to the disengagement operation.

An information processing method is an information processing method executed by a computer, and includes: detecting a first operation by a supervising party that supervises a moving body which drives autonomously from a remote location where the moving body cannot be supervised directly; and when the first operation is detected, relaxing an execution condition for autonomous driving of the moving body more than an execution condition applied when the first operation is not detected, and causing the moving body to drive autonomously under the execution condition that has been relaxed.

This document describes techniques, apparatuses, and systems for sensor fusion for object-avoidance detection, including stationary-object height estimation. A sensor fusion system may include a two-stage pipeline. In the first stage, time-series radar data passes through a detection model to produce radar range detections. In the second stage, based on the radar range detections and camera detections, an estimation model detects an over-drivable condition associated with stationary objects in a travel path of a vehicle. By projecting radar range detections onto pixels of an image, a histogram tracker can be used to discern pixel-based dimensions of stationary objects and track them across frames. With depth information, a highly accurate pixel-based width and height estimation can be made, which after applying over-drivability thresholds to these estimations, a vehicle can quickly and safely make over-drivability decisions about objects in a road.