A method for risk based processing, the method may include detecting, based on first sensed information sensed at a first period, a suspected risk within an environment of a vehicle; selecting, from reference information, a situation related subset of the reference information, wherein the situation related subset of the reference information is related to the situation; selecting, from reference information, a suspected risk related subset reference information, wherein the potential risk related subset of the reference information is related to the potential risk; and determining whether the suspected risk is an actual risk, based at least on part on the suspected risk related subset reference information.

A vehicle control method as executed includes acquiring surrounding information of the subject vehicle by a sensor includes, specifying an entry position located on a second lane adjacent to a first lane where the subject vehicle travels in accordance with the surrounding information of the subject vehicle, specifying a front vehicle located front the entry position and a rear vehicle located rear the entry position, determining the travel state of each of the front vehicle and the rear vehicle, determining whether there is a space for the subject vehicle to enter at the entry position, predicting whether the front vehicle starts to travel when the front vehicle and the rear vehicle are determined to be stopped and no space is determined at the entry position, and starting to move the subject vehicle to the entry position when the front vehicle is predicted to start traveling.

A method for performing at least one perception task associated with autonomous vehicle control includes receiving a first dataset and identifying a first object category of objects associated with the plurality of images, the first object category including a plurality of object types. The method also includes identifying a current statistical distribution of a first object type of the plurality of object types and determining a first distribution difference between the current statistical distribution of the first object type and a standard statistical distribution associated with the first object category. The method also includes, in response to a determination that the first distribution difference is greater than a threshold, generating first object type data corresponding to the first object type, configuring at least one attribute of the first object type data, and generating a second dataset by augmenting the first dataset using the first object type data.

A driving assist system assists driving of a vehicle. A deceleration target includes at least one of a preceding vehicle, a mandatory stop line, a mandatory stop sign, a traffic signal, and a stop line before the traffic signal that exist ahead of the vehicle. A risk factor includes at least one of a pedestrian, a bicycle, a motorcycle, an oncoming vehicle, and a parked vehicle that exist ahead of the vehicle. The driving assist system executes: deceleration assist control that automatically decelerates the vehicle before the deceleration target; and risk avoidance control that automatically performs at least one of steering and deceleration of the vehicle so as to avoid the risk factor. When both the deceleration assist control and the risk avoidance control operate concurrently, the driving assist system notifies a driver of the vehicle of not the deceleration target but the risk factor.

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.

A method for generating at least one school zone indicator, the method may include receiving by a vehicle computerized system, school zone indicators, wherein the school zone indicators are indicative of school zone elements; obtaining sensed information regarding an environment of the vehicle; processing the sensed information, wherein the processing comprises searching for one or more school zone indicators of the school zone indicators; wherein the school zone element is selected out of (i) a school zone object and (ii) a school zone situation; autonomously determining, when finding at least one of the one or more school zone identifiers, that the vehicle is driving towards a school zone or is within the school zone; and generating an alert when determining that the vehicle is driving towards the school zone or is within the school zone.

A sensor detects a variable indicative of a position of a receiving vehicle relative to a harvester during a harvester operation in which a material conveyance subsystem on the harvester is conveying harvested material to the receiving vehicle. If the receiving vehicle is in a compromised position in which it is out of range of the material conveyance subsystem or is about to be out of range, then a control signal is generated that can alert the operator of the harvester, automatically control harvester speed, or perform other control operations.

Systems and methods of controlling an active safety feature of a vehicle are provided. The systems and methods receive radar data from a radar device of the vehicle and image data from a camera of the vehicle. Object detection and tracking processes are performed on the radar data and the image data to identify and track objects in an environment of the vehicle. Conditions are assessed with respect to identified objects to ascertain whether a radar track is erroneously reported as a separate object to a camera track. When the conditions are assessed to be true, an object corresponding to the camera track is used as an input for controlling an active safety feature of the vehicle and an object corresponding to the radar track is discounted for controlling the active safety feature of the vehicle.

A system for notifying emergency services of a vehicular crash may (i) receive sensor data of a vehicular crash from at least one mobile device associated with a user; (ii) generate a scenario model of the vehicular crash based upon the received sensor data; (iii) store the scenario model; and/or (iv) transmit a message to one or more emergency services based upon the scenario model. As a result, the speed and accuracy of deploying emergency services to the vehicular crash location is increased. The system may also utilize vehicle occupant positional data, and internal and external sensor data to detect potential imminent vehicle collisions, take corrective actions, automatically engage autonomous or semi-autonomous vehicle features, and/or generate virtual reconstructions of the vehicle collision.

A method for estimating a future fall of a cargo, the method may include receiving by a computerized system, sensed information related to driving sessions of multiple vehicles; applying a machine learning process on the sensed information to detect actual or estimated cargo falling events and generate one or more future falling cargo predictors for multiple types of cargo; estimating, from the sensed information, an impact of cargo falling events related to at least some of the types of cargo; and responding to the estimating, wherein the responding comprises at least one out of (a) storing the one or more future falling cargo predictors for the multiple types of cargo, (b) transmitting the one or more future falling cargo predictors for the multiple types of cargo; (c) storing the estimated impact of cargo falling events related to the at least some of the types of cargo, and (d) transmitting the impact of cargo falling events related to the at least some of the types of cargo.