An agricultural work machine includes a geographic position sensor that detects a geographic location of the agricultural work machine. An in-situ sensor detects a value of a dynamic response characteristic of the agricultural work machine corresponding to the geographic location. A predictive model generator generates a predictive model that models a relationship between the terrain feature characteristic and the dynamic response characteristic based on a value of the terrain feature characteristic in a prior information map at the geographic location and a value of the dynamic response characteristic sensed by the in-situ sensor at the geographic location. A predictive map generator generates a functional predictive dynamic response map of the field, that maps predictive values of the dynamic response characteristic to the different geographic locations in the field, based on the values of the terrain feature characteristic in the prior information map and based on the predictive model.

Based on a recognition result of a recognition sensor installed in a mobile body, a mobile body control system calculates a first target path for moving to a destination while avoiding a risk around the mobile body. Further, based on the first target path, the mobile body control system calculates a second target path having higher granularity than the first target path. Then, the mobile body control system controls the mobile body so as to follow the second target path. The mobile body control system determines in which field the mobile body moves, a normal field or a specific field having more risks than the normal field. When the mobile body moves in the specific field, the mobile body control system reduces a frequency of update of the first target path compared with that when the mobile body moves in the normal field.

A vehicle for performing an autonomous parking function, the vehicle including: at least one camera configured to acquire a surrounding image of a vehicle; a display; a storage configured to store a HD map of a parking lot including an autonomous parking preparation zone; and at least one process configured to, based on the surrounding image of the vehicle being processed, generate a surround view image, based on an upper end of a road mark defining the autonomous parking preparation zone being recognized in the surround view image, track a position of the upper end of the road mark, upon the vehicle being stopped while a part of the road mark is recognized, correct a starting point on the HD map of the parking lot based on the position of the upper end of the road mark, and upon a user input for performing an autonomous parking function being received, perform the autonomous parking function based on the correct starting point.

According to a method for self-localization of a vehicle, a first pose of the vehicle is determined in a map coordinates system, based on environment sensor data representing an environment of the vehicle, a landmark is detected in the environment, a position of the landmark is determined in the map coordinates system and a second pose of the vehicle is determined in the map coordinates system dependent on the position of the landmark. An assignment instruction is consulted, matching up the first pose with at last one preferred sensor type or at least one dominant landmark type. Depending on the assignment instruction, a first environment sensor system is activated and a second environment sensor system is deactivated, whereupon the environment sensor data are generated by means of the first environment sensor system.

In various embodiments, methods, systems, and vehicles are provided for executing a lane change for a host vehicle. In various embodiments, a method includes: receiving, by a processor, an indication that a lane change from an initial lane to an intended lane is desired for the host vehicle; defining, by the processor, an initial lane center target, a negotiation target, and an intended lane center target based on the desired lane change; and controlling, by the processor, the host vehicle to at least one of the initial lane center target, the negotiation target, and the intended lane center target based on a finite state machine, wherein the initial lane center target is at or in proximity to a determined center of the initial lane, wherein the intended lane center target is at or in proximity to a determined center of the intended lane, and wherein the negotiation target is offset from the initial lane center target and within the initial lane.

A vehicular driver assistance system includes a front camera module (FCM) disposed at a vehicle. The system, responsive to processing captured image data, generates FCM lane information including information regarding a traffic lane the vehicle is currently traveling along. An e-Horizon module (EHM) generates EHM lane information including information regarding the traffic lane the vehicle is currently traveling along. The vehicular driver assistance system determines an FCM correlation using the FCM lane information and sensor data captured by at least one exterior sensor. The vehicular driver assistance system determines an EHM correlation using the EHM lane information and the sensor data captured by the at least one exterior sensor. Responsive to determining the FCM correlation and the EHM correlation, the system controls lateral movement of the vehicle based on one selected from the group consisting of (i) the FCM lane information and (ii) the EHM lane information.

Traveling environment information is recognized. A predicted traveling path is calculated based on a driving condition of a vehicle. An oncoming-vehicle predicted traveling path is calculated based on behavior of an oncoming vehicle. It is determined whether the vehicle has an intention to enter a first intersecting road at an intersection. When the vehicle cannot enter the first intersecting road, the predicted traveling path is corrected to a limit traveling path. It is determined whether the oncoming vehicle has an intention to enter a second intersecting road at the intersection. When the oncoming vehicle cannot enter the second intersecting road, the oncoming-vehicle predicted traveling path is corrected to an oncoming-vehicle limit traveling path. The oncoming vehicle is set as a control target against which emergency braking is executed when the predicted traveling path and the oncoming-vehicle predicted traveling path overlap each other at least in part.

Disclosed herein are an autonomous driving method for avoiding a stopped vehicle and an apparatus for the same. The autonomous driving method for avoiding a stopped vehicle is performed by an autonomous driving control apparatus provided in an autonomous vehicle, and includes obtaining taillight recognition information for a stopped vehicle identified ahead of the autonomous vehicle, determining whether the stopped vehicle is to be avoided in consideration of the taillight recognition information, when it is determined that the stopped vehicle is to be avoided, setting an avoidance method in consideration of whether lane returning is to be performed, which is determined based on an autonomous driving task, and setting an avoidance time point corresponding to the avoidance method and controlling the autonomous vehicle to avoid the stopped vehicle by traveling along an avoidance path generated in conformity with the avoidance time point.

A method for at least partially automated driving of a motor vehicle includes the steps of: determining that a need exists for infrastructure-based, at least partially automated driving of the motor vehicle, and transmitting, via a communication network, a request to transmit a plurality of infrastructure data based on which the motor vehicle is drivable in an at least partially automated manner, in response to determining that a need exists for infrastructure-based, at least partially automated driving of the motor vehicle. Receiving, via the communication network, the infrastructure data in response to transmitting the request. Generating a plurality of control signals for at least partially automated controlling of a lateral and/or a longitudinal operation of the motor vehicle based on the infrastructure data, and outputting the generated control signals.

To provide a vehicle control system which can reduce dependence on determination of an automatic driving vehicle and can make the automatic driving vehicle perform evacuation driving under control of the vehicle control system, at the time of occurrence of an evacuation cause. A vehicle control system acquires traveling nodes for automatic driving which makes the object vehicle perform automatic driving from the travel node storage unit, and transmits it to the object vehicle; and irrespective of a presence or absence of occurrence of an evacuation cause for evacuating the object vehicle, acquires the evacuation nodes corresponding to the travel nodes for automatic driving from the evacuation node storage unit, and transmits to the object vehicle.