System, methods, and other embodiments described herein relate to addressing inconsistencies between a trajectory plan and a communication from an occupant of an autonomously operated vehicle. A method of resolving inconsistent communication includes obtaining a trajectory plan for the vehicle, detecting, using one or more internal sensors, body language of the occupant the vehicle, analyzing sensor data from the one or more internal sensors to determine a verbal or non-verbal communication indication by the occupant, and detecting an inconsistency between the verbal or non-verbal communication indication and the trajectory plan and: 1) modifying the trajectory plan to form a modified trajectory plan aligned with the verbal or non-verbal communication indication, or 2) transmitting a notification to the occupant prompting the occupant to adjust the verbal or non-verbal communication indication.

Embodiments described herein disclose systems and methods for a dual buffer zone system to ensure a stable nudge for autonomous driving vehicles. In one embodiment, a system perceives a driving environment surrounding an autonomous driving vehicle (ADV), including perceiving one or more obstacles within a view of the ADV. For each of the one or more obstacles, if a previous planning decision for the obstacle is not a nudge, the system associates a first buffer zone with the obstacle. Otherwise, the system associates a second buffer zone with the obstacle. Based on the associated buffer zone for the obstacle, the system determines a planning decision to nudge the obstacle to ensure a buffer distance between the ADV and the obstacle. The system generates a trajectory for the ADV based on the planning decisions for the one or more obstacles.

A control device of an automated driving vehicle is configured to perform a recognition process, a search process, and a selection process. The recognition processing is a process for recognizing that the vehicle has entered a boarding area where an occupant gets off or gets on. The search process is a process of searching for a guide in the boarding area when the vehicle enters the boarding area. The selection process is a process, as the operation of the vehicle in the boarding area, in which a first operation mode is selected when the guide is not found, and a second operation mode is selected when the guide is found. The control device is configured to mitigate safety standards of an active safety system which avoids a collision between the vehicle and surrounding objects in the second operation mode, as compared with the first operation mode.

A system for modifying actions taken by an autonomous driving module of an autonomous vehicle may include one or more processors, an input device having an actuator, and a memory having an input module and a modification module. The input module includes instructions that, when executed by the one or more processors, cause the one or more processors to determine when the actuator of the input device is actuated by a passenger of the autonomous vehicle when the autonomous driving module is in an autonomous mode. The modification module includes instructions that, when executed by the one or more processors, cause the one or more processors to modify one or more actions to be performed by the autonomous driving module while maintaining the autonomous mode of the autonomous driving module when the actuator of the input device is actuated by the passenger. The one or more actions may include increasing an amount of sensor data considered by the autonomous driving module.

An autonomous vehicle computing system can include a primary perception system configured to receive a plurality of sensor data points as input generate primary perception data representing a plurality of classifiable objects and a plurality of paths representing tracked motion of the plurality of classifiable objects. The autonomous vehicle computing system can include a secondary perception system configured to receive the plurality of sensor data points as input, cluster a subset of the plurality of sensor data points of the sensor data to generate one or more sensor data point clusters representing one or more unclassifiable objects that are not classifiable by the primary perception system, and generate secondary path data representing tracked motion of the one or more unclassifiable objects. The autonomous vehicle computing system can generate fused perception data based on the primary perception data and the one or more unclassifiable objects.

This invention involves the effect of multiple rules of the road at different elevation profiles on the speed constraints and therefore the overall fuel efficiency. A vehicle designed to optimize fuel consumption that is comprised of the rules of the road that determine maximum speed, minimum speed, stop signs, streetlights, and/or changes in other rules that determine the allowable speeds of the road, a localization mechanism, and an optimization engine to optimize the fuel economy by selecting a speed profile within that maintains the vehicle within the assigned range of speeds and minimizes fuel consumption. A wide variety of methods that typically are used to optimize the fuel efficiency of human drivers operating standard vehicles can also be applied towards autonomous vehicles driving at different speed constraints and with different changes in the elevation.

A system and related method for predicting movement of a plurality of pedestrians may include one or more processors and a memory. The memory includes an initial trajectory module, an exit point prediction module, a path planning module, and an adjustment module. The modules include instructions that when executed by the one or more processors cause the one or more processors to obtain trajectories of the plurality of pedestrians, predict future exit points for the plurality of pedestrians from a scene based on the trajectories of the plurality of pedestrians, determine trajectory paths of the plurality of pedestrians based on the future exit points and at least one scene element of a map, and adjust the trajectory paths based on at least one predicted interaction between at least two of the plurality of pedestrians.

The disclosure includes embodiments for vehicular cooperative perception for identifying a subset of connected vehicles from a plurality to aid a pedestrian. In some embodiments, a method includes analyzing pedestrian data to determine a scenario depicted by the pedestrian data and a subset of the connected vehicles from the plurality that have a clearest line of the pedestrian. The method includes identifying a group of conflicted vehicles from the subset whose driving paths conflict with a walking path of the pedestrian. The method includes determining, based on the scenario, digital twin data describing a digital twin simulation that corresponds to the scenario. The method includes determining, based on the digital twin data and the pedestrian data, a group of modified driving paths for the group of conflicted vehicles. The method includes causing the group of conflicted vehicles to travel in accordance with the group of modified driving paths.

An image processing device applied to a driving assistance system, which includes: a driving assistance device that detects a relative position of a lane marking with respect to a vehicle and assists a driving of the vehicle based on a detected positional information; and a head-up display device that projects a display image on a projection area arranged on the vehicle to visually recognize a virtual image of the display image, includes: an acquisition device that acquires the positional information; and a generation device that generates the display image including a predetermined display element. The generation device generates the display image to visually recognize the display element at a position associated with the positional information and to visually recognize the display element as a shape inclined toward the vehicle from the lane marking.

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise an interface to obtain sensing data of an environment of the host vehicle. A processing device may be configured to determine a planned navigational action for the host vehicle; identify a target vehicle in the environment of the host vehicle; predict a resulting distance between the host and target vehicles if the planned action were taken; determine a host vehicle stopping distance based on a braking rate, maximum acceleration capability, and current speed of the host vehicle; determine a target vehicle stopping distance based on a braking rate and current speed of the target vehicle; and continue with the planned navigational action while the predicted distance is greater than a minimum safe longitudinal distance calculated based on the host vehicle stopping distance and the target vehicle stopping distance.