A vehicle drive-assist apparatus includes: a first front-environment recognizer recognizing, with a vehicle-mounted autonomous sensor, a front environment; a second front-environment recognizer recognizing the front environment on the basis of information received from an external device via external communication; a first brake controller determining, when a preceding vehicle is recognized by the first front-environment recognizer, a target position on the basis of the preceding vehicle, and executing a first brake control based on the target position; and a second brake controller determining, when the preceding vehicle is recognized only by the second front-environment recognizer, the target position on the basis of the preceding vehicle, and determining a corrected target position by correcting the target position, and executing a second brake control based on the corrected target position in advance of the first brake control. The corrected target position is farther from the own vehicle than the target position is.

Terrain characteristics of an off-road area are determined based on a map. The terrain characteristics include a terrain type, a terrain grade, and a presence or an absence of an obstacle. Vehicle characteristics are determined including a ground clearance and a breakover angle. Based on a user level, vehicle parameters for the off-road area are determined based on the terrain characteristics, the vehicle characteristics, and the user input. The vehicle parameters include a speed and a transmission gear. The vehicle parameters for the off-road area are output.

A system and method for inferring a stop line for a vehicle at an intersection are provided. The system includes a processor configured to detect from accessed map data that a traffic control measure is positioned before an intersection and determine whether a stop line for the detected traffic control measure is painted. The processor, in response to determining that no stop line is painted, identifies a restricted lane and infers a stop line. The processor infers the stop line by identifying, as a nearest lane conflict, a lane segment of a second road intersecting the first road at the intersection and advancing a location of the entry line as an intermediate stop line a distance toward the nearest lane conflict, until the intermediate stop line is at a target distance from a nearest boundary of the nearest lane conflict to form an inferred stop line.

The technology relates to articulated autonomous vehicles that can potentially jackknife. To avoid or mitigate such hazardous conditions, the current state of the vehicle is evaluated against the vehicle's planned trajectory, for instance as it drives along a freeway or surface streets. When the evaluation indicates a likelihood of jackknifing, an automated braking approach is implemented using elective braking to stabilize the vehicle. The braking approach can depend on whether the situation involves tractor jackknifing or trailer jackknifing, and one or more different braking mechanisms can be employed for a selective modulation of the braking profile to address actual jackknifing or to prevent the vehicle from entering a jackknifing situation.

A parking assistance device includes: a traveling assistance control unit that causes a vehicle to automatically travel to a designated parking area and park the vehicle; a reception unit that receives an operation signal for shifting to a state in which traveling control by the traveling assistance control unit can be executed from an operation unit provided in a vehicle interior of the vehicle; and a braking switching unit that switches a braking device that maintains a stop state of the vehicle to a braking force generating state in a case where the operation signal is received.

A vehicle control device includes a processor. The processor is configured to: output a torque command value related to a rotation speed of a wheel of a vehicle; specify an estimated value which is a value obtained by estimating the rotation speed of the wheel based on the torque command value; and determine a parameter based on an error between the estimated value and a measured value which is a value obtained by measuring the rotation speed of the wheel. The torque command value is determined by a feedforward control using a target value which is a value as a target of the rotation speed of the wheel and the parameter.

The invention relates to a method for a control unit (10) for stopping a vehicle (1) when stopping at different types of stop positions (2, 3, 4), the method comprising the following steps: —(S1) the control unit receiving input about a specific stop position for the vehicle, associated with when the vehicle is about to stop during a stopping sequence, the input being indicative of whether the specific stop position requires a high-precision stop or if a stop with a lower precision can be used; and —(S2) when the stop position requires a high-precision stop, the control unit controlling the stopping sequence such that the vehicle stops with a first stopping precision level with respect to the specific stop position, and when a lower precision can be used for the stop, the control unit controlling the stopping sequence such that the vehicle stops with a second stopping precision level which is lower than the first precision level. The invention further relates to a control unit and to a vehicle comprising the control unit.

Systems, methods, and devices are disclosed for predicting yield behaviors of objects (vehicles, bicycles, pedestrians, etc.) at a location. An autonomous vehicle located at a first road segment connecting to an intersection having a stop sign can detect a first vehicle approaching the intersection from a second road segment connecting to the intersection. Using a model indicating an average yield location and yield time where both are specific to the second road segment connecting to the intersection, the autonomous vehicle can predict that the first vehicle will yield at the average yield location that is specific to the second road segment.

The present invention is intended to make it possible to automatically drive a test object without performing pre-learning for a running performance map for each vehicle. There is provided an automatic test object driving device that automatically drives a test vehicle based on a command vehicle speed, and that includes a driving actuator for performing driving operation of the test vehicle, and a driving control unit for controlling the driving actuator. The driving control unit includes a first accelerator map and a second accelerator map each of which indicates a relationship among a vehicle-speed-related value, an acceleration-related value, and an accelerator-depression-amount-related value. The driving control unit uses the first accelerator map to determine an accelerator depression amount corresponding to the command vehicle speed, and uses the second accelerator map to correct the accelerator depression amount by feeding back a vehicle speed and an acceleration of the test vehicle.

A driving support device includes a storage device storing a program and a hardware processor. The hardware processor executes the program stored in the storage device to perform driving support of a vehicle based on a detection result of at least one of a radar device and an imaging device mounted in the vehicle, determine whether the vehicle is traveling in an underpass which is a traffic route along which the vehicle is able to pass under an overlying structure, and suppress an operation of the driving support when the vehicle is determined to be traveling under the underpass.