Techniques are described for determining visibility conditions of an environment in which an autonomous vehicle is operated and performing driving related operations based on the visibility conditions. An example method of adjusting driving related operations of a vehicle includes determining, by a computer located in an autonomous vehicle, a visibility related condition of an environment in which the autonomous vehicle is operating, adjusting, based at least on the visibility related condition, a set of one or more values of one or more variables associated with a driving related operation of the autonomous vehicle, and causing the autonomous vehicle to be driven to a destination by causing the driving related operation of one or more devices located in the autonomous vehicle based on at least the set of one or more values.

A behavior prediction system predicts human behaviors based on environment-aware information such as camera movement data and geospatial data. The system receives sensor data of a vehicle reflecting a state of the vehicle at a given time and a given location. The system determines a field of concern in images of a video stream and determines one or more portions of images of the video stream that correspond to the field of concern. The system may apply different levels of processing powers to objects in the images based on whether an object is in the field of concern. The system then generates features of objects and identify VRUs from the objects of the video stream. For the identified VRUs, the system inputs a representation of the VRUs and the features into a machine learning model, and outputs from the machine learning model a behavioral risk assessment of the VRUs.

An example operation includes one or more of determining a characteristic of an occupant in a transport and a current driving environment of the transport, wherein the characteristic includes a position of the occupant, determining that the current driving environment will lead to a collision of the transport, and based on a predicted result of the collision, sending a predicted state of the occupant based on the position, to an emergency service node.

Systems and methods for monitoring the lane of an object in an environment of an autonomous vehicle are disclosed. The methods include receiving sensor data corresponding to the object, and assigning an instantaneous probability to each of a plurality of lanes based on the sensor data as a measure of likelihood that the object is in that lane at a current time. The methods also include generating a transition matrix for each of the plurality of lanes that encode one or more probabilities that the object transitioned to that lane from another lane in the environment or from that lane to another lane in the environment at the current time. The methods then include determining an assigned probability associated with each of the plurality of lanes based on the instantaneous probability and the transition matrix as a measure of likelihood of the object occupying that lane at the current time.

A control device for a vehicle includes an upper limit value setting unit configured to set an upper limit value of an acceleration or deceleration of the vehicle, and a vehicle controller configured to control the vehicle such that the acceleration or deceleration does not exceed the upper limit value. The upper limit value setting unit is configured to change the upper limit value according to at least one predetermined condition.

A vehicle includes a cabin having a first room and a second room that are capable of accommodating at least one passenger, and configured to isolate one or more passengers accommodated in the first room from one or more passengers accommodated in the second room, a guidance apparatus configured to guide the at least one passenger to be accommodated in either the first room or the second room, and a control apparatus configured to control the guidance apparatus. When a user boards as the at least one passenger, the control apparatus determines which of the first room and the second room the user is to board, based on information regarding the user. The guidance apparatus is configured to guide and board the user to whichever of the first room and the second room determined by the control apparatus.

An autonomous driving control apparatus installable in a vehicle includes a path determining section, an obstacle determining section that determines whether an obstacle on the planned driving path is a passage acceptable obstacle or a passage unacceptable obstacle, the passage acceptable obstacle being previously set as an obstacle that the vehicle is allowed to come into contact with while passing, the passage unacceptable obstacle being previously set as an obstacle that the vehicle is not allowed to come into contact with while passing, and a control instructing section that gives an instruction of control to a maneuver controller to perform at least one of controlling a speed of the vehicle and controlling a steering of the vehicle to control a maneuver of the vehicle. If the obstacle is determined to be the passage acceptable obstacle, the control instructing section gives an instruction of the control to pass over the obstacle.

A method can be used to control a steer-by-wire steering system in an emergency steering mode. The method comprises checking a steering system for the presence of a fault state and upon detection of a fault implementing the emergency steering mode, which involves determining a setpoint position of a steering tie rod using a setpoint wheel steering angle, determining a front wheel to be braked and a brake pressure to attain the setpoint position with a control unit, transmitting the front wheel to be braked and the brake pressure to a brake system, braking the front wheel to be braked, and increasing a torque provided by a wheel drive to compensate for a loss of speed of the motor vehicle caused by the braking of the front wheel to be braked.

Provided are methods for thermal sensor data vehicle perception, which can include obtaining thermal sensor data, obtaining non-thermal sensor data, and determining, based on the thermal sensor data and the non-thermal sensor data, a perception parameter indicative of an object. Some methods described also include generating a trajectory for an autonomous vehicle. Systems and computer program products are also provided.

An abnormal physical condition determination system includes: an extraction unit that extracts a plurality of feature quantities indicating a condition of a target person from an image of the target person; an accumulation unit that accumulates the plurality of feature quantities as time series data; a calculation unit that calculates a relationship between each feature quantity from the plurality of feature quantities accumulated in the accumulation unit; and a determination unit that determines an abnormal physical condition of the target person on the basis of the relationship. According to such an abnormal physical condition determination system, it is possible to appropriately determine the abnormal physical condition of the target person.