Patent classifications
B60W2556/10
Vehicle control device and vehicle control method
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.
Vehicle control device, vehicle control method, and storage medium
A vehicle control system includes a recognizer configured to recognize a surrounding situation of a vehicle, a driving controller configured to perform driving control on at least one of steering and a speed of the vehicle on the basis of a recognition result of the recognizer, an environment controller configured to control an operation of a predetermined device for providing a comfortable environment of the vehicle and limit an operation state of the predetermined device at a timing when a user gets out of the vehicle, and a reproducer configured to reproduce the operation state of the predetermined device at a timing when the user gets into the vehicle when the driving controller performs driving control for moving the vehicle from a parking area and picking up the user.
Road friction estimation
Techniques are described for dynamically selecting vehicles to perform road friction probing maneuvers and estimating road friction based on sensor data collected while a vehicle performs the road friction probing maneuvers. In one example, a computing system is configured to select, from a plurality of vehicles, based on an amount of elapsed time since each respective vehicle of the plurality of vehicles has performed a road friction probing maneuver, a vehicle to perform the road friction probing maneuver within a road segment of a roadway, and responsive to selecting the vehicle, output, to the vehicle, a command causing the vehicle to perform the road friction probing maneuver within the road segment.
Apparatus, system and method for controlling vehicle
An apparatus for controlling a vehicle includes: a sensor that obtains vehicle surrounding environment information and vehicle driving information; and a controller that determines whether an engagement of an Electronic Parking Brake (EPB) is possible based on the vehicle driving information, performs control for preventing a slip based on the vehicle surrounding environment information upon determining that the engagement of the EPB is impossible, calculates a steering angle for preventing the slip, transmits the steering angle to a portable terminal, receives a steering control command from the portable terminal, and controls steering based on the received steering control command.
Detection of object awareness and/or malleability to state change
Determining whether another entity is coordinating with an autonomous vehicle and/or to what extent the other entity's behavior is based on the autonomous vehicle may comprise determining a collaboration score and/or negotiation score based at least in part on sensor data. The collaboration score may indicate an extent to which the entity is collaborating with the autonomous vehicle to navigate (e.g., a likelihood that the entity is increasingly yielding the right of way to the autonomous vehicle based on the autonomous vehicle's actions). A negotiation score may indicate an extent to which behavior exhibited by the entity is based on actions of the autonomous vehicle (e.g., how well the autonomous vehicle and the entity are communicating with their actions).
INFORMATION PROVISION SYSTEM, INFORMATION PROVISION METHOD, AND STORAGE MEDIUM
The present invention provides an information provision system that provides information to a driver of a straddle type vehicle, the system comprising: an acquisition unit configured to acquire information on a course of the straddle type vehicle; a specification unit configured to specify an attention portion to which attention of the driver should be paid in the course acquired by the acquisition unit; and a notification unit configured to notify the driver of the attention portion specified by the specification unit, wherein the specification unit is configured to specify the attention portion based on inclination information indicating an inclination on the course of a reference vehicle that has previously traveled on the course, and specify the attention portion based on a difference in a travel route on the course between the straddle type vehicle and a four-wheeled vehicle as the reference vehicles.
COLLISION DETECTION METHOD, ELECTRONIC DEVICE, AND MEDIUM
A collision detection method, an electronic device, and a storage medium are provided, which relate to a field of artificial intelligence technology, and in particular to fields of intelligent transportation and autonomous driving technologies. The method includes: determining a predicted travel range of a target object based on a planned travel trajectory of the target object and a historical travel trajectory of the target object; determining, in response to a target obstacle being detected, a predicted travel range of the target obstacle based on a current travel state of the target obstacle; and determining whether the target object has a risk of colliding with the target obstacle, based on the predicted travel range of the target object and the predicted travel range of the target obstacle.
METHOD FOR CARRYING OUT A LANE CHANGE ON A DECELERATION LANE BY MEANS OF AN ASSISTANCE SYSTEM, COMPUTER PROGRAM PRODUCT, AND ASSISTANCE SYSTEM
Technologies and techniques for carrying out an assisted lane change onto a deceleration lane, during which an intervention in an acceleration device may be carried out in an at least partially assisted manner as a function of a driver input on a driving lane of the roadway. The lane change from the driving lane onto the deceleration lane may be carried out in an at least partially assisted manner, wherein swarm data are received from at least one further motor vehicle, which carried out a lane change onto the deceleration lane at a crossing, and a change position for the lane change of the motor vehicle is determined as a function of the received crossing position. The lane change is carried out at the determined change position. Other aspects relate to a computer program product and to an assistance system.
EVACUATION RUNNING ASSISTANCE SYSTEM
An evacuation running assistance system includes a road shoulder evacuation possibility determiner to determine if an own vehicle can be evacuated to a road shoulder; an own vehicle situation determiner to determine a current situation of an own vehicle in accordance with a time limit and the road shoulder evacuation possibility, a controller to control an own vehicle in accordance with the situation of the own vehicle; and a road shoulder evacuation possibility road determiner to acquire evacuation space information from a past running history of the own vehicle. The own vehicle situation determiner determines that the own vehicle is in the situation to be controlled to perform the on-lane stopping when the road shoulder evacuation possibility road determiner does not determine within the provisional time that the evacuation of the own vehicle to the road shoulder is possible.
APPARATUS AND METHOD FOR PROCESSING SENSOR DATA TO PREDICT FUTURE OUTCOMES
A method, apparatus, and system are described. The method includes generating a set of current values associated with at least one component included on a moving vehicle and providing the set of current values over a wireless network. The values are generated by one or more sensors. An edge computing device receives the current values. The method further includes processing the set of current values in real-time using at least one machine learning algorithm to identify a value of a point in time for a failure of one of the at least one component based on the set of current values and at least one set of past values received. The past values are stored in a memory. The set of current values are transmitted with a low time latency between the generating the set of current values and the processing of the set of current values.