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 system for controlling an intelligent network vehicle is provided, and the system comprises a sensor group configured to obtain sensor information; a sensing and positioning module configured to obtain sensing information and positioning information based on the sensor information; a planning and control module configured to determine vehicle planning control information based on the sensing information and the positioning information; a safety control module configured to determine safety control information based on the sensing information and the positioning information; a function assessment module configured to determine a vehicle state assessment result; a risk assessment module configured to determine a risk assessment result; a logical arbitration module configured to determine vehicle execution information by arbitrating the vehicle planning control information and the safety control information; and an execution module configured to control the vehicle driving based on the vehicle execution information.

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 method, apparatus and computer program product for activating a flood event warning are described herein. In the context of a method, a location may be identified as a flood prone location. Data relating to the flood prone location may be received from one or more remote devices. The method may determine a flood confidence for the flood prone location based upon the data. The method may identify an active flood event for the flood prone location based on the flood confidence and cause a flood event warning to be activated in an instance in which the active flood event is identified.

When a subject vehicle performs first autonomous lane change control from a subject vehicle lane to an adjacent lane and then consecutively perform autonomous lane change control to a next adjacent lane in the same direction of lane change, lateral speed to perform second and subsequent autonomous lane change control is set slower than lateral speed to perform the first autonomous lane change control. Thus, the second and subsequent autonomous lane change control to the adjacent lane in the same direction of lane change is performed more slowly than the previously performed autonomous lane change control. Time used for confirming surrounding situations is lengthened, and the surrounding situations can be properly confirmed prior to the lane change.

An apparatus and a method for controlling an autonomous vehicle depending on weather are provided. The apparatus obtains information including at least one of an image around the autonomous vehicle, sensing information of a Light Detection and Ranging (LiDAR) of the autonomous vehicle, sensing information of a rain sensor of the autonomous vehicle, an operation state of a windshield wiper of the autonomous vehicle, climate information through vehicle to everything (V2X) communication, an acceleration of the autonomous vehicle, or wheel sensor information of the autonomous vehicle and determines whether the climate state is an inclement weather state, based on the information including the at least one of the image around the autonomous vehicle, the sensing information of the LIDAR, the sensing information of the rain sensor, the operation state of the windshield wiper, the climate information through the V2X communication, the acceleration, or the wheel sensor information.

The present disclosure provides a method for identifying a confidence level of an autonomous driving system in an autonomous driving vehicle. The method includes determining hardware currently used by the autonomous driving system to realize required functions and environmental factors which affect the hardware capability of the hardware, and establishing a relationship between the hardware capability and the environmental factors; based on environmental factors on a future specific road section acquired in real time, calculating a degree to which the hardware capability will be affected on the specific road section; in consideration of acquired the environmental factors, judging an influence of the affected hardware capability on the realization of required functions of the autonomous driving system based on the acquired the environmental factors; and reflecting the influence on the realization of required functions of the autonomous driving system as a confidence level, and prompting the confidence level to a driver.

A vehicle controller device including: a communication section configured to receive operation information to operate a vehicle from an operation device located externally to the vehicle; a first memory; and a first processor, the first processor being configured to: acquire peripheral information regarding a periphery of the vehicle from a peripheral information detection section; generate a travel plan for the vehicle based on the peripheral information of the vehicle; control autonomous driving in which the vehicle travels based on the generated travel plan and also control remote driving in which the vehicle travels based on the received operation information; predict that a compromised state in which autonomous driving of the vehicle becomes compromised will arise based on environmental information including meteorological information received by the communication section; and notify the operation device of the compromised state in a case in which the compromised state has been predicted to arise.

To realize an apparatus and a method for receiving a recognition level of an own vehicle from another vehicle and/or an infrastructure facility and performing control to improve a recognition level. A recognition level of the own vehicle calculated by another vehicle or the infrastructure facility is received, and control for improvement of a recognition level of the own vehicle is executed in accordance with the received recognition level. As the control for improvement of a recognition level of the own vehicle, any process is executed among: (a) a process of reducing a traveling speed or stopping; (b) a process of turning on a light; and (c) a process of changing transmission information from the own vehicle. As the process of changing transmission information, a process of adding, to the transmission information, vehicle location information, vehicle speed information, vehicle size information, or reference marker position information is executed.

A travel control system for a vehicle includes a vehicle speed calculator, a mode continuation determiner, and a mode continuing unit. The vehicle speed calculator evaluates a level of worsening of a traveling environment and calculates a first vehicle speed on the basis of the level of the worsening of the traveling environment. The mode continuation determiner determines whether it is possible to continue with driving assist control in the second driving assist mode by comparing a second vehicle speed in the second driving assist mode with the first vehicle speed. When it is not possible to continue with the driving assist control in the second driving assist mode, the mode continuing unit lowers the second vehicle speed in the second driving assist mode to the first vehicle speed to allow the driving assist control in the second driving assist mode to continue.