Patent classifications
B60W2754/30
VISIBILITY CONDITION DETERMINATIONS FOR AUTONOMOUS DRIVING OPERATIONS
Techniques are described for determining visibility conditions of an environment in which an autonomous vehicle is operated and performing driving related operations based on the visibility conditions. An example method of adjusting driving related operations of a vehicle includes determining, by a computer located in an autonomous vehicle, a visibility related condition of an environment in which the autonomous vehicle is operating, adjusting, based at least on the visibility related condition, a set of one or more values of one or more variables associated with a driving related operation of the autonomous vehicle, and causing the autonomous vehicle to be driven to a destination by causing the driving related operation of one or more devices located in the autonomous vehicle based on at least the set of one or more values.
SYSTEM AND METHOD OF DETECTING AND MITIGATING ERRATIC ON-ROAD VEHICLES
A system and method of detecting and mitigating an erratic vehicle by a host vehicle. The method includes gathering sensor information on a calibratable external region surrounding the host vehicle; analyzing the sensor information to detect a target vehicle traveling in a lane and a movement of the target vehicle in the lane; determining whether the movement of the target vehicle in the lane is erratic; if erratic then designating target vehicle as erratic vehicle; assigning a risk score to the erratic vehicle; and implementing a predetermined mitigating action correlating to the assigned risk score to the erratic vehicle. The mitigating action includes one or more of: warning an operator of the host vehicle, warning a vehicle proximal to the host vehicle, and taking at least partial control of the host vehicle to further distance the host vehicle apart from the erratic vehicle.
Method for sharing data between motor vehicles to automate aspects of driving
Provided is a navigation system for a leader vehicle leading follower vehicles, including: the leader vehicle, configured to transmit, real-time movement data to follower vehicles; and, the follower vehicles, each comprising: a signal receiver for receiving the data from the leader vehicle; sensors configured to detect at least one maneuverability condition; a memory; a vehicle maneuver controller; a distance sensor; and a processor configured to: determine a route for navigating the local follower vehicle from an initial location; determine a preferred range of distances from the vehicle in front of the respective follower vehicle that the respective follower vehicle should stay within; determine a set of active maneuvering instructions for the respective follower vehicle based on at least a portion of the data received from the guiding vehicle; determine a lag in control commands; and, execute the set of active maneuvering instructions in the respective follower vehicle.
Method and system for controlling an automated driving system of a vehicle
A method for setting a tuning parameter for an Automated Driving System (ADS) of a vehicle is disclosed. A corresponding non-transitory computer-readable storage medium, vehicle control device and a vehicle comprising such a control device are also disclosed. The method comprises receiving environmental data from a perception system of the vehicle, said environmental data comprising a plurality of environmental parameters, determining, by means of a self-learning model, an environmental scenario based on the received environmental data; setting the tuning parameter for the ADS based on the self-learning model and the determined environmental scenario, the tuning parameter defining a dynamic parameter of the ADS, receiving at least one signal representative of a vehicle user feedback on the set tuning parameter, and updating the self-learning model for the set tuning parameter for the identified environmental scenario based on the received vehicle user feedback.
VEHICLE CRUISE CONTROL DEVICE AND CRUISE CONTROL METHOD
A cruise control device 10 is applied to a vehicle in which an imaging device 21 is mounted. The cruise control device 10 includes: a white line recognition unit 11 which recognizes a white line 61 as a lane boundary that defines an own lane 63 that is a travel lane of an own vehicle 50, on the basis of images acquired by the imaging device 21; and a cutting-in/deviation determination unit 12 which performs cutting-in determination and deviation determination, in which the forward vehicle traveling on an adjacent lane 64 is determined to be a cutting-in vehicle that cuts into the own lane, and the forward vehicle traveling on the own lane is determined to be a deviating vehicle that deviates from the own lane on the basis of a relative position with respect to the white line in a vehicle width direction of a forward vehicle 51.
ALERT DETECTION SYSTEM
An alert detection system for a vehicle includes: a sensor unit; a controller; and an alert indication unit, the controller receiving at least one or more input signals from at least the sensor unit and determining one or more output indicators based on the at least one or more input signals, and the one or more output indicators including a first output indicator, a second output indicator, and a third output indicator which are Level 1 alert, Level 2 alert, and Level 3 alert, and the one or more output indicators being progressively actuated based on signal received from the at least one or more of input signals.
VEHICLE DRIVING ASSISTANCE APPARATUS, VEHICLE DRIVING ASSISTANCE METHOD, AND COMPUTER-READABLE STORAGE MEDIUM STORING VEHICLE DRIVING ASSISTANCE PROGRAM
A vehicle driving assistance apparatus predicts (i) a first consumed energy amount corresponding to a consumed energy amount consumed by a driving apparatus of an own vehicle when executing a first following control and (ii) a second consumed energy amount corresponding to the consumed energy amount consumed by the driving apparatus of the own vehicle when executing the second following control. The apparatus executes the second following control when the second consumed energy amount is smaller than the first consumed energy amount. On the other hand, the apparatus executes the first following control when the second consumed energy amount is equal to or greater than the first consumed energy amount.
Methods and devices for triggering vehicular actions based on passenger actions
Autonomous driving system methods and devices which trigger vehicular actions based on the monitoring of one or more occupants of a vehicle are presented. The methods, and corresponding devices, may include identifying a plurality of features in a plurality of subsets of image data detailing the one or more occupants; tracking changes over time of the plurality of features over the plurality of subsets of image data; determining a state, from a plurality of states, of the one or more occupants based on the tracked changes; and triggering the vehicular action based on the determined state.
Vehicular control system with rear collision mitigation
A vehicular control system includes a plurality of sensors disposed at a vehicle and sensing exterior of the vehicle. An electronic control unit (ECU) includes a processor that processes sensor data captured by the sensors. The vehicular control system, responsive at least in part to processing at the ECU of captured sensor data as the vehicle travels in a traffic lane of a road, detects another vehicle that is rearward of the equipped vehicle and traveling along an adjacent traffic lane. The vehicular control system detects a leading vehicle ahead of the equipped vehicle and traveling in the same traffic lane as the equipped vehicle. The vehicular control system, responsive to determination of a space along the other traffic lane ahead of the detected other vehicle, controls the equipped vehicle to maneuver into the adjacent traffic lane to pass the detected leading vehicle ahead of the detected other vehicle.
Tunnel-based planning system for autonomous driving vehicles
According to one embodiment, a system receives a captured image perceiving an environment of an autonomous driving vehicle (ADV) from an image capturing device of the ADV capturing a plurality of obstacles near the ADV. The system generates a first tunnel based on a width of a road lane for the ADV, where the first tunnel represents a passable lane for the ADV to travel through. The system generates one or more additional tunnels based on locations of the obstacles, where the one or more additional tunnels modify a width of the passable lane according to a level of invasiveness of the obstacles. The system generates a trajectory of the ADV based on the first and the additional tunnels to control the ADV according to the trajectory to navigate around the obstacles without collision.