Abstract: There may be provided a method for electrical scooter alert, the method may include sensing sensed information about an environment of a vehicle; detecting, based on the sensed information, a situation related to the environment; detecting, based on the sensed information, a electrical scooter within the environment; predicting, using a machine leaning process and based in the situation, a future behavior of the electrical scooter and an impact of the future behavior of the electrical scooter on a future progress of the vehicle; and responding to the predicting.

Abstract: A method for following a person associated with a vehicle, the method may include entering a tracking mode for following the person; when operating in the tracking mode performing at least one out of: autonomously driving an autonomous vehicle towards the person and parking in proximity to the person, and autonomously driving towards the person and picking up the person.

Abstract: A method for open door steer assist, the method may include receiving by a vehicle computerized system, at least one future open door predictor that is indicative of a future vehicle door opening process, the future open door predictor is generated by a machine learning process and is visible before a start of an opening of the vehicle door and before reaching the vehicle door; wherein each of the at least one future open door predictor is sensed before a start of the future vehicle door opening process; obtaining sensed information regarding an environment of the vehicle; processing the sensed information, wherein the processing comprises searching for a future open door predictor of the at least one future open door predictor; and detecting the future open door predictor.

Abstract: A method for child forward collision warning, the method may include sensing sensed information about an environment of a vehicle; detecting, based on the sensed information, a situation related to the environment; detecting, based on the sensed information, one or more children within the environment; classifying each child of the one or more children to a class; predicting, using a machine leaning process, a future behavior of the one or more children and an impact of the future behavior of the one or more children on a future progress of the vehicle; wherein the predicting of each child of the one or more children is responsive to a class of the child and to the situation; and responding to the predicting.

Abstract: A method for providing an audio-based model of an environment of a vehicle, the method may include obtaining, during a driving session of a vehicle, sensed information about the environment of the vehicle; wherein the sensed information may include sensed audio information. The sensed information may also include at least one type of non-audio sensed information; and generating an audio-based model of the environment based, at least in part, on the sensed audio information.

Abstract: A method for motorcycle roll angle robust object detection, the method includes receiving, by a processing circuit, an image of an environment of the vehicle, wherein the image was obtained by a camera associated with a motorcycle; and generating, by the processing circuit, a signature of the image; finding, by the processing circuit, using the generated signature, a matching concept data structure out of multiple concept data structures; wherein the multiple concept data structure represents images acquired at multiple roll angles of a field of view of the camera; and detecting, by the processing circuit, within the image, an object or a scenario that is associated with the matching concept data structure.

Abstract: A method for driving related applications based on aerial images. The method includes (i) determining, by a processor, based on aerial map segment information and sensed environmental information, a driving control action in association the vehicle within at least the environment of the location estimate of the vehicle; (ii) determining, based on the sensed environmental information and according to the aerial map segment information, whether to perform the driving related operation within at least the environment of the location estimate of the vehicle; and (iii) responsive to determining the performance of the driving related operation, outputting information regarding the driving related operation to a control system of the vehicle.

Abstract: 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.

Abstract: A method for detecting a state of a motorcycle, the method includes (i) obtaining, by a camera of the motorcycle, one or images of an environment of the vehicle; wherein there is a known angular relationship between the field of view of the camera and predefined part or a vertical axis of the motorcycle; (ii) generating signatures of the one or more images; (iii) searching, using the signatures, multiple groups of concept data structures, for one or more matching concept data structures; wherein different groups of concept data structures represent images virtually acquired at different roll angles; and (iv) determining a roll angle of the motorcycle based on an outcome of the searching and the known angular relationship.

Abstract: A method for generating the at least one highway exit indicator, the method may include receiving video information and location information obtained during driving sessions of the plurality of vehicles; determining, based on the location information, multiple suspected highway exit events; selecting video information segments, wherein each selected video information segment is acquired before a suspected highway exit event and in timing proximity to the suspected highway exit event; and applying a machine learning process on at least some of the selected video information segments to find the at least one highway exit indicator.

Abstract: A method for cut in maneuver alert, the method may include receiving by a vehicle computerized system of a vehicle, one or more cut in maneuver predictors, each cut in maneuver predictor is (a) indicative of a predicted cut in maneuver initiated by another vehicle, and is (b) generated by a machine learning process; obtaining sensed information regarding an environment of the vehicle; processing the sensed information, wherein the processing comprises searching for a cut in maneuver predictor; and finding the cut in maneuver predictor.

Abstract: A method for bypass alert, the method may include obtaining during a driving session of a vehicle, sensed information about an environment of the first vehicle, by one of more vehicle sensors of the vehicle; detecting that the vehicle is within a certain distance from a destination of the driving session; detecting, using a first machine learning process, one or more parking indicators that are indicative of an allowable parking area that precedes the vehicle; detecting a vacant parking space within the parking area that is large enough to facilitate a parking of the vehicle within the vacant parking space; and responding to the vacant parking space.

Abstract: A system and method for enriching a concept database. The method includes determining, based on at least one signature of a first multimedia data element (MMDE) and signatures of a plurality of existing concepts in the concept database, at least one first concept among the plurality of existing concepts, wherein each of the at least one first concept matches a portion of the at least one signature of the first MMDE; generating a reduced representation of the first MMDE, wherein generating the reduced representation further comprises removing the portion of the first MMDE matching the at least one first concept; comparing the reduced representation of the first MMDE to signatures representing a plurality of second MMDEs to determine a plurality of matching second MMDEs; generating, based on the reduced representation of the first MMDE and the plurality of matching second MMDEs, at least one second concept; and adding the generated at least one second concept to the concept database.

Abstract: A method for A method for automatic emergency braking (AEB) of a vehicle, the method may include obtaining sensed information regarding an environment of the vehicle and regarding a motion of the vehicle; determining an occurrence of current situation, based on the sensed information; selecting, based on the current situation, a selected narrow AI agent out of multiple narrow AI agents; wherein different narrow AI agents are trained, using a machine learning process, to perform AEB related decisions at different scenarios; wherein the selected narrow AI agent is associated with the occurrence of the current situation; processing, by the selected narrow AI agent, at least one out of (a) at least a first part of the sensed information, and (b) an outcome of a pre-processing of at least a second part of the sensed information; wherein the processing results in a AEB related decision; and responding to the AEB related decision, wherein the responding comprises at least one out of (a) executing the AEB related dec

Abstract: A method for providing an audio-based model of an environment of a vehicle, the method may include obtaining, during a driving session of a vehicle, sensed information about the environment of the vehicle; wherein the sensed information may include sensed audio information. The sensed information may also include at least one type of non-audio sensed information; and generating an audio-based model of the environment based, at least in part, on the sensed audio information.

Abstract: A method for pedestrian crossing alert, the method may include receiving, by a vehicle computerized system, pedestrian crossing indicators; obtaining sensed information regarding an environment of the vehicle; processing the sensed information, wherein the processing comprises searching for at least one of the pedestrian crossing indicators; autonomously determining, when finding the at least one of the pedestrian crossing identifiers, that the vehicle is approaching a pedestrian crossing; and generating an alert when determining that the vehicle is approaching the pedestrian crossing.

Abstract: Systems, and method and computer readable media that store instructions for generating a hybrid representation of a media unit.

Abstract: A system and method for at least partially completing a user profile. The method includes analyzing the user profile to identify at least one missing informational element in the user profile, wherein identifying the at least one missing element further comprises determining at least one concept based on the user profile and matching the determined at least one concept to a plurality of category concepts, each concept including a collection of signatures and metadata describing the concept, wherein each category concept is associated with at least one required informational element, wherein each missing informational element is one of the at least one required informational element that is not included in the user profile; sending a query for the missing informational element; and updating at least a portion of the user profile based on a response to the query.

Abstract: A method for bypass alert, the method may include obtaining during a driving session of a vehicle, sensed information about an environment of the first vehicle, by one of more vehicle sensors of the vehicle; detecting that the vehicle is within a certain distance from a destination of the driving session; detecting, using a first machine learning process, one or more parking indicators that are indicative of an allowable parking area that precedes the vehicle; detecting a vacant parking space within the parking area that is large enough to facilitate a parking of the vehicle within the vacant parking space; and responding to the vacant parking space.

Abstract: A method for determining driving related features of a vehicle, which may include repeating, during each time interval out of multiple time intervals of a period: obtaining sensed information during at least a part of the time interval; selecting, based on a predefined decision, a selected sub-set of narrow artificial intelligence (AI) agents; and calculating one or more driving related feature. The calculating may include applying the selected sub-set of narrow AI agents on the sensed information.