The present invention provides a saddle ride type vehicle including a sensing unit configured to sense a four-wheel vehicle that is present in front of a self-vehicle and is traveling in a travel lane of the self-vehicle, and a control unit configured to, in a case where the four-wheel vehicle is sensed by the sensing unit, perform follow-travel control for causing traveling of the self-vehicle to follow traveling of the four-wheel vehicle, wherein the sensing unit senses a vehicle width of the four-wheel vehicle, and the control unit, in the follow-travel control, controls a travel position in a vehicle width direction of the self-vehicle so that at least a portion of the self-vehicle falls within a region within the vehicle width of the four-wheel vehicle.

A vehicle control method for controlling a vehicle using a vehicle control apparatus includes: a sensor configured to detect a state outside a subject vehicle; and a control device. The vehicle control method includes: executing control of recovering a travel trajectory of the subject vehicle to a target trajectory, as ordinary control, by giving a steering amount in a lateral direction with respect to a travel lane of the subject vehicle; using detection data of the sensor to determine whether or not another vehicle is traveling in an adjacent lane to the travel lane of the subject vehicle; and when determining that the other vehicle is traveling in the adjacent lane ahead of the subject vehicle, increasing a response of the steering amount to a higher response than that in the ordinary control, before the subject vehicle passes the other vehicle.

Systems and methods are provided for vehicle navigation. In one implementation, at least one processing device may receive, from a camera of the host vehicle, at least one captured image representative of an environment of the host vehicle. The processing device may analyze one or more pixels of the at least one captured image to determine whether the one or more pixels represent at least a portion of a target vehicle. For pixels determined to represent at least a portion of the target vehicle, the processing device may determine one or more estimated distance values from the one or more pixels to at least one edge of a face of the target vehicle; and generate, based on the analysis of the one or more pixels, including the determined one or more distance values associated with the one or more pixels, at least a portion of a boundary relative to the target vehicle.

Techniques are discussed for controlling a vehicle, such as an autonomous vehicle, based on predicted occluded areas in an environment. An occluded area can represent areas where sensors of the vehicle are unable to sense portions of the environment due to obstruction by another object. A first occluded region for an object is determined at a first time based on a location of the object. A predicted location for the object can be used to determine a predicted occluded region caused by the object at a second time after the first time. Predicted occluded regions can be determined for multiple trajectories for the vehicle to follow and/or at multiple points along such trajectories, and a trajectory can be selected based on associated occlusion scores and/or trajectory scores associated therewith. The vehicle can be controlled to traverse the environment based on the selected trajectory.

Provided herein is a system and method of a vehicle that determines an action of a vehicle. The system comprises one or more sensors; one or more processors; and a memory storing instructions that, when executed by the one or more processors, causes the system to perform determining a location of one or more other vehicles relative to the vehicle; determining an action of the vehicle based on the determined location of one or more other vehicles; sending a signal to the one or more other vehicles indicating the determined action; and performing the determined action of the vehicle.

A driving support control device for a vehicle includes an acquisition unit configured to acquire, from a first detector which detects change of a brightness value of an object which occurs in accordance with displacement of the object, information indicating change of a brightness value of a partially shielded object partially shielded by an obstacle which occurs in accordance with displacement of the partially shielded object, as a first detection signal, and a control unit configured to, in a case where it is determined, by using the first detection signal, that the partially shielded object is moving, cause a driving support execution device to execute collision prevention support for preventing a collision with the partially shielded object.

An intelligent harvester with instantaneous stop functions includes a harvester body, a detecting system for detecting a human body within an area range on a traveling route of the harvester body, and a brake system arranged on the harvester body and operatively connected to the detecting system. When the detecting system detects a human body present within the area range on a traveling path of the harvester body, the brake system controls the harvester body to brake.

A method and system of intelligently alerting and/or routing vehicles to improve driving safety is disclosed. The method includes sharing data collected by vehicles in different locations to determine whether the presence of dynamically moving objects such as animals and pedestrians will affect traffic conditions for other vehicles on the nearby roadways. If the system determines there is a likelihood of such objects being obstacles to other vehicles, an alert can be automatically presented to the drivers of the impacted vehicles. The method further includes generating routes for the driver that avoid, or limit, the driver's exposure to the obstacle.

A vehicle control device includes a recognizer that is configured to recognize an object around a subject vehicle, a driving controller that is configured to control a speed or steering of the subject vehicle, and a predictor that is configured to predict that a predetermined vehicle will move to a front of the subject vehicle on a subject lane. The driving controller is configured to perform a behavior control in a case where it is predicted that the predetermined vehicle will move to the front of the subject vehicle on the subject lane and limits the vehicle behavior control in a case where it is predicted that the predetermined vehicle does not move to the front of the subject vehicle on the subject lane as compared with a case where it is predicted that the vehicle will move to the front of the subject vehicle on the subject lane.

The present disclosure discloses a method for simulating an obstacle in an unmanned simulation scene, an electronic device, and a storage medium, and relates to a field of unmanned driving technologies. The method includes: for obstacle information in a three-dimensional scene map, determining Gaussian distribution information of obstacle position detected by using a perception algorithm to be tested based on actual perception performance of the perception algorithm; adjusting each position of the simulated obstacle in the initial motion trajectory sequence, such that a position deviation between each adjusted position point in the target motion trajectory sequence and the corresponding position point in the initial motion trajectory sequence follows a Gaussian distribution; and adding the target motion trajectory sequence of the simulated obstacle to the three-dimensional scene map.