A system 100 for remote assistance of an autonomous agent can include and/or interface with any or all of: a sensor suite 110, a computing system 120, a communication interface 130, and/or any other suitable components. The system can further optionally include a set of infrastructure devices 140, a teleoperator platform 150, and/or any other suitable components. The system 100 functions to enable information to be exchanged between an autonomous agent and a tele-assist. Additionally or alternatively, the system 100 can function to operate the autonomous agent (e.g., based on remote inputs received from a teleoperator, indirectly, etc.) and/or can perform any other suitable functions.

In one embodiment, a method for monitoring a localization function in an autonomous driving vehicle (ADV) can use known static objects as ground truths to determine when the localization function encounter errors. The known static objects are marked on a high definition (HD) map for the real-time driving environment. When the ADV detects one or more known static objects, the ADV can use sensor data, locations of the one or more static objects, and one or more error tolerance parameters to create a localization error tolerance area surrounding a current location of the ADV. The ADV can project the tolerance area on the HD map, performs a localization operation to generate an expected location of the ADV on the HD map, and determines whether the generated location falls within the projected tolerance area. If the generated location falls outside the projected tolerance area, indicating a localization function of the ADV encounter errors, the ADV can generate an alarm to alert a human driver to switch to a manual driving mode. If no human driver is available in the ADV, the ADV can activate a vision-based fail-safe localization procedure.

A vehicle includes a navigation configured to output navigation information; and a controller configured to receive a requested stopping location of the vehicle for a passenger to get on or off, to determine a stopping location of the vehicle based on the navigation information and information on a designated no-stopping zone, in response to the receiving of the requested stopping location, and to control the vehicle to head to the determined stopping location.

A system for controlling operation of a vehicle during a turning maneuver includes an object detection sensor, a vehicle turning angle sensor, and a processor. A memory is communicably coupled to the processor and stores a turning alert zone module configured to determine if a speed of the vehicle is within a predetermined range of speeds and, if the speed of the vehicle is within the predetermined range of speeds, determine if a vehicle turning angle is above a predetermined threshold value. If the turning angle is above the predetermined threshold value, and using the turning angle, a turning alert zone is determined. The system may then determine if at least a portion of an object resides in the turning alert zone and, if at least a portion of an object resides in the turning alert zone, control an operation of the vehicle (for example, a braking operation).

A contact determination system includes a processor, and determines whether a contact event occurs between target objects in a vicinity of a host vehicle. The processor is configured to acquire, regarding each of the target objects including at least one of (i) a road user other than the host vehicle and (ii) a road-installed object, a type and a moving speed of the target object. The processor is also configured to perform an overlap determination regarding whether at least two target models respectively modeling the target objects overlap with each other. The processor is further configured to determine whether or not the contact event occurs for a pair of the target objects that have been determined to have an overlap based on the type and moving speed of the target object.

The present disclosure relates to a pull up controlling system of a vehicle for controlling the vehicle in a planned stop-and-go situation. The pull up controlling system determines a position of the vehicle and identifies a stop-and-go destination within a predeterminable distance from the vehicle position. The stop-and-go destination includes an interaction interface. The pull up controlling system provides a user input request relating to whether to discard or acknowledge the stop-and-go destination. The pull up controlling system receives intention data indicative of confirmation to acknowledge the stop-and-go destination. The pull up controlling system further derives preference data indicative of an openable section of the vehicle. The pull up controlling system maneuvers the vehicle to pull up at the stop-and-go destination, with the openable section aligned with the interaction interface.

The techniques discussed herein may comprise an autonomous vehicle guidance system that generates a path for controlling an autonomous vehicle based at least in part on a static object map and/or one or more dynamic object maps. The guidance system may identify a path based at least in part on determining set of nodes and a cost map associated with the static and/or dynamic object, among other costs, pruning the set of nodes, and creating further nodes from the remaining nodes until a computational or other limit is reached. The path output by the techniques may be associated with a cheapest node of the sets of nodes that were generated.

A proactive pedal algorithm is used to modify an accelerator pedal map to ensure the deceleration when the accelerator pedal is released matches driver expectation. Modifying the accelerator pedal map provides the driver of a vehicle the sensation that the vehicle resists moving when travelling in dense scenes with potentially high deceleration requirements and coasts easily in scenes with low deceleration requirements. The accelerator pedal map is modified based on a scene determination to classify other remote vehicles as in-lane, neighbor-lane, or on-coming.

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 and an assistance device assist automated driving operation of a motor vehicle. Surroundings raw data recorded by way of a surroundings sensor system of the motor vehicle are processed by the assistance device in order to generate semantic surroundings data. This is accomplished by carrying out semantic object recognition. Further, a comparison of predefined semantically annotated map data against the semantic surroundings data is performed. This involves static objects indicated in the map data being identified in the semantic surroundings data as far as possible. Discrepancies detected during the process are used to recognize perception errors of the assistance device. A recognized perception error prompts a predefined safety measure to be carried out.