Abstract: A method for driving a first vehicle based on information received from a second vehicle, the method may include receiving, by the first vehicle, acquired image information regarding (a) a signature of an acquired image that was acquired by the second vehicle, (b) a location of acquisition of the acquired image; extracting, from the acquired image information, information about objects within the acquired image; and preforming a driving related operation of the first vehicle based on the information about objects within the acquired image.

Abstract: A method for detecting obstacles, the method may include receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired during executions of vehicle maneuvers that are suspected as being obstacle avoidance maneuvers; determining, based at least on the visual information, at least one visual obstacle identifier for visually identifying at least one obstacle; and transmitting to one or more of the plurality of vehicles, the at least one visual obstacle identifier.

Abstract: An autonomous driving system for a vehicle comprising: an I/O module operative to communicate with an obstacle avoidance server; at least one sensor operative to provide at least an indication of an obstacle in a path of the vehicle; processing circuitry; and an autonomous driving manager to be executed by the processing circuitry and operative to: detect the at least an indication of an obstacle based on data provided by the at least one sensor, drive the vehicle in accordance with a driving policy associated with the obstacle, and send an obstacle report with obstacle information associated with the at least an indication of an obstacle to the obstacle avoidance server.

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

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

Abstract: A method for bump alert, the method may include receiving by a vehicle computerized system, at least one visual bump indicator that is visible before driving over at least one bump; obtaining sensed information regarding an environment of the vehicle; processing the sensed information, wherein the processing comprises searching a visual bump indicator of the at least one visual bump indicator; determining whether the vehicle approaches a bump; and generating the bump alert when determining that the vehicle approaches the bump.

Abstract: A method for off road driving, the method may include obtaining environment sensed information about an environment of a vehicle of a certain model, by one of more vehicle sensors of the vehicle and while driving over an off road path; detecting, by a machine learning process, an off road driving event; determining, by the machine learning process, a characteristic behavior of vehicles of the certain model when facing the off road driving event; and responding, at least in part by the machine learning process, to the occurrence of the off road driving event.

Abstract: A system and method for generating personalized multimedia content element clusters. The method includes determining, based on at least one interest, at least one personalized concept, wherein each personalized concept represents one of the at least one user interest; obtaining at least one multimedia content element related to a user; generating at least one signature for the at least one multimedia content element, each generated signature representing at least a portion of the at least one multimedia content element; determining, based on the generated at least one signature, at least one multimedia content element cluster, wherein each cluster includes a plurality of multimedia content elements sharing a common concept of the at least one personalized concept; and creating at least one personalized multimedia content element cluster by adding, to each determined cluster, at least one of the at least one multimedia content element sharing the common concept of the cluster.

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 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: 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 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 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 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 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 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 bypass alert, the method may include obtaining sensed information about an environment of the first vehicle, by one of more vehicle sensors of a first vehicle; wherein the environment of the first vehicle comprises a passing lane and a current lane in which the first vehicle is positioned; determining whether a driver initiates a bypass of another vehicle to be bypassed, wherein the determining is made by a first machine learning process, and is based on at least one out of first vehicle parameters and the sensed information about the environment; determining that the first vehicle entered the passing lane; determining, by a second machine learning process, a determined time to collision (TTC) to an incoming vehicle that is located at the passing lane and drives towards the first vehicle; determining, based on at least on the determined TTC and an allowable TTC to provide a safety parameter of the bypass; and responding to the safety parameter.

Abstract: Systems, and method and computer readable media that store instructions for calculating signatures, utilizing signatures and the like.

Abstract: A method and system for generating signatures for three-dimensional multimedia data elements.

Abstract: A method for detecting obstacles, the method may include receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired during executions of vehicle maneuvers that are suspected as being obstacle avoidance maneuvers; determining, based at least on the visual information, at least one visual obstacle identifier for visually identifying at least one obstacle; and transmitting to one or more of the plurality of vehicles, the at least one visual obstacle identifier.