A control unit for a vehicle is configured to detect a signalling installation ahead, wherein the signalling installation has at least one signal transmitter. The control unit is configured to ascertain digital map information indicating and/or allowing an association between the at least one signal transmitter and at least one possible direction of travel of the vehicle at the signalling installation. The control unit is further configured to operate a driving function of the vehicle on the basis of the digital map information.

A traffic indication information determining method includes: obtaining n pieces of first traffic indication information from n sensors, where the first traffic indication information is used to indicate traffic indication information of a traffic command target, the traffic indication information is used to provide a road traffic rule for a vehicle, and n is an integer greater than or equal to 1; and determining second traffic indication information based on the n pieces of first traffic indication information. In the method, the n pieces of first traffic indication information of the traffic command target are obtained based on the n sensors, and then the second traffic indication information used when the vehicle actually travels is determined based on the n pieces of first traffic indication information.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. An example system for an AV includes obtaining, by a computer located in the AV, an image from a camera located on the AV, where the image characterizes an area towards which the AV is driven on a lane on a road or a highway; determining, from the image, that a pedestrian or a cyclist is located next to the lane on the road or the highway; and in response to the determining, performing driving operations on the AV such as steering from a center of the lane to a first side of the lane that is away from the center of the lane and away from a location of the pedestrian or the cyclist, and/or slowing down the AV in response to certain conditions.

Embodiments for operational envelope detection (OED) with situational assessment are disclosed. Embodiments herein relate to an operational envelope detector that is configured to receive, as inputs, information related to sensors of the system and information related to operational design domain (ODD) requirements. The OED then compares the information related to sensors of the system to the information related to the ODD requirements, and identifies whether the system is operating within its ODD or whether a remedial action is appropriate to adjust the ODD requirements based on the current sensor information. Other embodiments are described and/or claimed.

A method for controlling an autonomous vehicle including: obtaining trip information of a current trip of a user of the autonomous vehicle and historical traffic information related to the current trip; selecting an autonomous driving (AD) mode that is suitable for the current trip from a plurality of pre-defined AD modes; comparing time required for the autonomous vehicle to complete a portion of the current trip in the selected AD mode with historical average time to complete the portion of the current trip, the historical average time being acquired based on the historical traffic information; and dynamically adjusting driving of the autonomous vehicle based on the comparison to minimize the difference between the time required for the autonomous vehicle to complete the portion of the current trip in the selected AD mode and the historical average time.

The present disclosure includes systems and methods for adjusting the lane position of a vehicle. A radar system positioned on a first vehicle is configured to transmit radio waves and receive reflections of the radio waves, which produces radar data indicative of the reflections. At least one controller of the first vehicle is configured to identify at least one radar marker based on the radar data and to determine the location of the identified marker. The at least one controller is further configured to decode encoded information of the radar marker, where the information may indicate a condition associated with the roadway on which the vehicle is traveling. The at least one controller may then adjust the lane position of the vehicle based on the location of the marker and any decoded information.

Embodiments provide extracting information respectively corresponding to predetermined dimensions from environment information corresponding to an unmanned driving environment. In some embodiments, the information respectively corresponding to the dimensions is input into an identification model to obtain a driving feature. Then a risk value representing a driving risk degree of an unmanned device is determined, and a maximum variation of the information corresponding to at least one dimension is determined when a variation of the driving feature is less than a predetermined threshold. A maximum variation of the information corresponding to each dimension is used as a risk contribution feature. A variation representative value of the information corresponding to each dimension is determined from the risk contribution feature. According to the variation representative values of the dimensions, a driving risk factor corresponding to the risk value is determined based on the driving feature.

Embodiments of this application provides example methods, media, and apparatuses for predicting moving trajectory of a target object. One example method includes obtaining a candidate moving trajectory, where the candidate moving trajectory is a motion trajectory that is of the target object in future period and that is obtained by using a prediction method, and the target object is in a sensing range of an ego vehicle. Environmental information is obtained within the sensing range. A constraint barrier is generated based on the environmental information, where the constraint barrier is used to indicate an area through which the target object is constrained to pass. The candidate moving trajectory is processed based on the constraint barrier.

An HCU is to be used in a vehicle including an autonomous driving operation, and includes a function of a presentation control device that controls presentation of information to a driver of the vehicle. The presentation control device determines interruption of a second task other than driving permitted to the driver in an autonomous traveling period where the vehicle travels by the autonomous driving operation. Based on the interruption determination of the second task, the HCU changes a provision method of content provided in association with the second task in the autonomous traveling period.

A preceding vehicle identification apparatus includes: a route acquisition portion that acquires an anticipated route along which the subject vehicle is expected to travel at a future time; a region specification portion that defines a region in which the preceding vehicle is estimated to exist as an estimated region by adding an acceptable error range that is margin of error in predicting a position of the preceding vehicle to a scheduled travel region of the subject vehicle that is defined based on the anticipated route; and a preceding vehicle settling portion that identifies an other vehicle as the preceding vehicle when the other vehicle is determined to exist in the estimated region.