Method and system for narrow passage path sampling based on levy flight is disclosed. The disclosed technique is an improvisation of Random Walk to Surface (RWS), wherein, instead of performing a random walk, the disclosed technique utilizes levy flight mechanism to identify samples in narrow passages (on the obstacle boundaries). The disclosed technique for identification of narrow passages sampling points in the narrow passage is based on several techniques that include random uniform sampling technique, a levy flight function (step size) and a collision detection technique. Moreover, in addition to identification of narrow passages sampling points, the disclosed technique also performs an additional check to ensure that the identified narrow passages sampling points are present in the narrow passage based on a levy flight bridge sampler technique.

A vehicle driving assist device comprises: an oncoming moving body recognizer configured to recognize an oncoming moving body; a risk determination region setting unit configured to set a risk determination region for calculating a risk degree that decreases as a distance outward from a center of the oncoming moving body in a width direction of the oncoming moving body increases; a risk degree calculator configured to calculate the risk degree for the oncoming moving body in accordance with an overlap state between the target traveling path of the vehicle and the risk determination region; and a preliminary collision avoidance controller configured to recognize the oncoming moving body as the obstacle in accordance with the risk degree, and perform preliminary collision avoidance control in response to the oncoming moving body recognized as the obstacle prior to the emergency collision avoidance control.

A mobile object control device according to an embodiment includes a recognizer that recognizes a surroundings situation of a mobile object, and an unavoidable contact determiner that determines whether or not contact between the mobile object and an object likely to come into contact with the mobile object is unavoidable on the basis of a recognition result of the recognizer when there is the object around the mobile object, and the unavoidable contact determiner limits a recognition range of the recognizer to a predetermined range including the object when the recognition result of the recognizer satisfies a predetermined condition, and determines whether or not the contact between the mobile object and the object is unavoidable.

An Autonomous Vehicle (AV) system, including: a tracking subsystem configured to detect and track relative positioning of another vehicle that is behind or lateral to an AV configured to comply with a safety driving model, and to check a safety driving model compliance status of the other vehicle; and a risk reduction subsystem configured to plan, based on the safety driving model compliance status of the other vehicle, an AV action, wherein if the safety driving model compliance status of the other vehicle is unknown or is known to be non-compliant, the AV action is administration of a safety driving model compliance test to the other vehicle, or is a maneuver by the AV to reduce risk of collision with a leading vehicle positioned in front of the AV.

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.

A vehicle interlock system includes a wheelchair fixing device configured to fix a wheelchair to a vehicle, a seatbelt device having a seatbelt configured such that, an occupant seated in the wheelchair wears the seatbelt, and a control unit. The control unit is configured to limit at least one of an upper limit traveling speed and an upper limit acceleration of the vehicle or output a warning signal, or to output a warning signal while limiting at least one of the upper limit traveling speed and the upper limit acceleration of the vehicle depending on at least one of the following conditions: whether the wheelchair is fixed to the vehicle with the wheelchair fixing device; whether the occupant is wearing the seatbelt; and so forth.

Systems and methods for situational behavior of an autonomous vehicle are disclosed. In one aspect, an autonomous vehicle includes at least one perception sensor configured to generate perception data indicative of at least one other vehicle on a roadway, a non-transitory computer readable medium, and a processor. The processor is configured to determine that the other vehicle is violating one or more rules of the roadway based on the perception data, tag the other vehicle as a non-compliant driver, and modify control of the autonomous vehicle in response to tagging the other vehicle as a non-compliant driver.

A vehicle and control method include: a seat; an image acquirer to acquire an image of the seat; a first type of roof airbag module in a fixed position in a first area of a headlining; a rail member in a second area of the headlining in a left-right direction of a vehicle body; a second type of roof airbag module in the rail member and movable in left and right directions along the rail member; an angle detector to detect a rotation angle of the seat; and a controller. The controller identifies the seat rotation angle based on the image of the seat and controls activation of at least the first type of roof airbag module or the second type of roof airbag module based on at least the seat rotation angle based on the image of the seat or detected by the angle detector.

In an autonomous driving method, a health physiological data range is added to an operational design domain (ODD) deployed on an autonomous driving system (ADS) as an applicable range of the ODD. The ADS receives real-time physiological data of a driver/passenger collected by a monitoring device. When a difference between the real-time physiological data and a health physiological data range is greater than a preset value, and a duration in which the real-time physiological data deviates from the health physiological data range is greater than a first preset duration, the ADS degrades an autonomous driving service being executed by an autonomous driving vehicle, and executing a first driving policy based on the difference and the duration.

An autonomous vehicle (AV) implements a health protocol that may reduce pathogen transmission between users of the AV. The AV is equipped with a thermal sensor that captures a body temperature of a user. The AV compares the user’s temperature to a threshold temperature, and if the user’s temperature exceeds the threshold temperature, the AV performs checks to ensure that the user’s planned trip follows current regulations or recommendations. For example, the AV confirms that the user is traveling between the user’s home and a healthcare facility. If the trip is permitted, the AV enables the user to enter the AV. The AV may include a disinfectant system for disinfecting the passenger compartment or surfaces after the user exits the AV.