A method for guiding a vehicle based on an open width of a roadway includes detecting a left road edge, a right road edge, an obstacle, and a free or open space on a the road ahead using an image sensor and radar installed so as to be oriented forwards in the vehicle. The width of the free/open space is determined at a plurality of positions over a predetermined distance from a front of the vehicle, and a determination is made as to whether the vehicle can traverse the road ahead based on a comparison between the width of the free space at each of the plurality of positions over the predetermined distance and a predetermined width of the vehicle.

In one aspect, a system for controlling the speed of a seed-planting implement may include a furrow closing assembly configured to close a furrow formed in the soil by the seed-planting implement. Furthermore, the system may include a sensor configured to capture data indicative of an operational parameter of the furrow closing assembly. Additionally, the system may include an implement-based controller supported on the seed-planting implement and being communicatively coupled to the sensor. As such, the implement-based controller may be configured to initiate control of a drive parameter of a work vehicle configured to tow the seed-planting implement based on sensor data received from the sensor in a manner that adjusts the speed of the seed-planting implement.

A system, comprising a computer that includes a processor and a memory, the memory storing instructions executable by the processor to track a target in lidar point cloud data by minimizing an error function based on a smoothed target position, a smoothed target velocity, a smoothed target acceleration and a measured target position. The processor can be further programmed to operate a vehicle based on tracking the target.

A vehicular control system for controlling a vehicle includes a vehicle control, an acceleration sensor and a camera. The vehicle control includes an image processor for processing image data captured by the camera as the vehicle is driven along a route by a driver of the vehicle. The vehicle control detects traffic and road topography and determines acceleration of the vehicle as the vehicle is driven along the route by the driver. The vehicle control learns the route during multiple repetitive drives of the route by the driver of the vehicle. The vehicle control increases a confidence level of the learned route during multiple repetitive drives of the route by the vehicle. When the confidence level exceeds a threshold value, the vehicle control is operable to at least semi-autonomously control the vehicle to drive the vehicle along the route.

A driving support apparatus for an own vehicle includes a lane keeping assist control unit. When an interrupting vehicle enters ahead of the own vehicle in (i) a situation in which no preceding vehicle is present ahead of the own vehicle, or (ii) a situation in which a preceding vehicle is present ahead of the own vehicle, while a deviation angle formed between a direction of a traveling trajectory of the interrupting vehicle and a traveling direction of the own vehicle is larger than a threshold, the lane keeping assist control unit is configured not to perform a lane keeping assist control based on the traveling trajectory of the interrupting vehicle, and is configured to discard the traveling trajectory of the interrupting vehicle. On and after the deviation angle becomes equal to or smaller than the threshold, the lane keeping assist control unit is configured to perform the lane keeping assist control based on the traveling trajectory of the interrupting vehicle.

A multi-spectral vehicular system for providing pre-collision alerts, comprising two pairs of stereoscopic infrared (IR) and visible light (VL) sensors, each of which providing acquired image streams from a mutual field of view, which are synchronized to provide stereoscopic vision; a data fusion module for mutually processing the data streams, to detect objects within the field of view and calculating distances to detected objects; a cellular based communication module for allowing communication between the sensors and mobile phones/Infotainment systems of the vehicle. The module runs a dedicated background application that is adapted to monitor the vicinity of the vehicle to detect other vehicles having a similar system; calculate speed and heading azimuth of each of the other vehicles; and provide alerts to the driver of the vehicle whenever other vehicles having a similar system are in a path of collision with the vehicle, based on the calculation and on the speed of the vehicle.

A vehicle radar system includes at least one radar, a detection section, an extraction section, a pair determination section, and a target position determination section. The extraction section extracts at least one observation point pair from a plurality of detected observation points. The observation point pair is a pair of the observation points located in the same direction. The target position determination section calculates a surface direction of a reflection surface from a reflection surface observation point of the observation point pair and observation points around the reflection surface observation point, and determines a position of the target from the calculated surface direction and the at least one observation point pair.

An apparatus for operating a pedestrian detection and collision mitigation system (PDCMS) function of a vehicle includes: a front detection sensor detecting a presence of a pedestrian on a driving lane of the vehicle and a distance and a relative speed between the pedestrian and the vehicle; a vehicle sensor detecting a speed of the vehicle; an electronic control unit operating a PDCMS function based on information detected by the front detection sensor and the vehicle sensor; and a warning unit operated to inform a driver of a collision of the pedestrian with the vehicle by a control of the electronic control unit.

Methods and systems for autonomous and semi-autonomous vehicle control relating to malfunctions are disclosed. Malfunctioning sensors or software of autonomous vehicles may be identified from operating data of the vehicle, and a component maintenance requirement status associated with such malfunctioning component may be generated. Based upon such status, usage restrictions may be enacted to limit operation of the vehicle while the component is malfunctioning. This may include disabling or restricting use of certain autonomous or semi-autonomous features of the vehicle until the component is repaired or replaced. Repair may be accomplished by automatically scheduling repair of the vehicle or installing an updated or uncorrupted version of a software program, in various embodiments.

A LIDAR sensor is mountable to a vehicle exterior with a field of view including a vehicle interior view first portion and a vehicle exterior view first portion. Data can be received from the LIDAR sensor. A state of a vehicle occupant can be determined based at least in part on data from the LIDAR sensor.