Aspects of the disclosure provide for reducing inconvenience to other road users caused by stopped autonomous vehicles. As an example, a vehicle having an autonomous driving mode may be stopped at a first location. While the vehicle is stopped, sensor data is received from a perception system of the vehicle. The sensor data may identify a road user. Using the sensor data, a value indicative of a level of inconvenience to the road user caused by stopping the vehicle at the first location may be determined. The vehicle is controlled in the autonomous driving mode to cause the vehicle to move from the first location and in order to reduce the value.

A vehicle control device includes: a storage portion in which map information is stored, the map information showing a position where a roadside machine configured to transmit a radio signal including predetermined information is provided; a route setting portion configured to set a route where an autonomous driving vehicle is to travel when a current position, of the autonomous driving vehicle, that is measured by a positioning portion provided in the autonomous driving vehicle is included within a predetermined distance from the position of the roadside machine on the map information and the autonomous driving vehicle approaches the position where the roadside machine is provided, the route being set so that a communication portion provided in the autonomous driving vehicle can receive the radio signal; and a vehicle controlling portion configured to control the autonomous driving vehicle so that the autonomous driving vehicle travels along the route.

A first blind spot information acquisition unit inputs road geometry information and traveling environment information which are acquired by an information acquisition unit to a first blind spot inference model, and thereby acquires, using the first blind spot inference model, first blind spot information indicating a blind spot area of a road along which a vehicle is traveling, the first blind spot inference model being configured to output first blind spot information indicating a blind spot area of a road when receiving road geometry information about geometry of the road and traveling environment information about a traveling environment of the road. A parking position determination unit determines a parking position of the vehicle by using the first blind spot information acquired by the first blind spot information acquisition unit.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. An example method for operating an AV includes receiving, from a sensor located on the AV, sensor data that captures a road sign located at a distance from the AV that is operating on a roadway; obtaining, from the sensor data, roadway information indicated by the road sign that corresponds to a segment of the roadway associated with the road sign that is ahead of a current position of the AV on the roadway; determining trajectory-related information for the AV for the distance that is based on the roadway information obtained from the sensor data; and causing the AV to travel in accordance with the trajectory-related information until a determination that the AV has arrived within the segment of the roadway associated with the road sign.

The described techniques relate to coordinating and managing faults of systems of a vehicle, such as an autonomous vehicle, to enable the vehicle to respond safely and appropriately to the faults. In examples, a centralized fault monitor system receives faults from different vehicle systems, maps the received faults to associated fault constraints, prioritizes different and shared parameters between the fault constraints, and communicates the constraint parameters to appropriate vehicle systems accordingly.

A device (16) for determining a discrete representation (30) of a road section ahead of a vehicle (12) includes an input interface (22) for receiving sensor data (20) of a sensor (14) with information about the road section ahead of the vehicle, a setting unit (24) for ascertaining a control distance at which a property of the road section ahead of the vehicle that is relevant for an open-loop control of the vehicle changes based on the sensor data and for setting a support point in a discrete representation of the road section corresponding to the control distance. The setting unit is configured for setting a lower predefined second number (n2) of support points based on a predefined first number (n1) of support points. The device also includes an output interface (26) for outputting the lower predefined second number of support points to an optimizer (52) in order to determine a profile of at least one control parameter for the open-loop control of an open-loop system, a vehicle function based on the second number (n2) of support points.

A system includes a memory device, and a processing device, operatively coupled to the memory device, to receive a set of input data including a roadgraph. The roadgraph includes an autonomous vehicle driving path. The processing device is further to determine that the autonomous vehicle driving path is affected by one or more obstacles, identify a set of candidate paths that avoid the one or more obstacles, each candidate path of the set of candidate paths being associated with a cost value, select, from the set of candidate paths, a candidate path with an optimal cost value to obtain a selected candidate path, generate a synthetic scene based on the selected candidate path, and train a machine learning model to navigate an autonomous vehicle based on the synthetic scene.

A system includes a memory device, and a processing device, operatively coupled to the memory device, to receive a set of input data including a roadgraph, the roadgraph including an autonomous vehicle driving path, modify the roadgraph to obtain a modified roadgraph by adjusting a trajectory of the autonomous vehicle driving path, place a set of artifacts along one or more lane boundaries of the modified roadgraph to generate a synthetic scene, and train a machine learning model used to navigate an autonomous vehicle based on the synthetic scene.

A driving control device including a processor. The processor detects that a vehicle has encroached into an area configured for car-washing by a carwash machine, switches a travel mode of the vehicle to autonomous driving, and controls the vehicle so as to stop at a carwash position for the carwash machine under autonomous driving.

A device according to one aspect of the present disclosure is an on-vehicle control device configured to control a traveling speed of a vehicle including the on-vehicle control device. The on-vehicle control device includes: an acquisition unit configured to acquire a present light color of a traffic light unit installed at an intersection; a calculation unit configured to calculate an avoidance position and an avoidance speed with respect to a dilemma zone at a time when yellow light starts; and a control unit configured to execute a first deceleration process of reducing the traveling speed of the vehicle at the avoidance position to a speed equal to or lower than the avoidance speed, in a case where a present position of the vehicle is on an upstream side relative to the avoidance position and the present light color is green.