Techniques for determining a trajectory for an autonomous vehicle are described herein. In general, determining a route can include utilizing a search algorithm such as Monte Carlo Tree Search (MCTS) to search for possible trajectories, while using temporal logic formulas, such as Linear Temporal Logic (LTL), to validate or reject the possible trajectories. Trajectories can be selected based on various costs and constraints optimized for performance. Determining a trajectory can include determining a current state of the autonomous vehicle, which can include determining static and dynamic symbols in an environment. A context of an environment can be populated with the symbols, features, predicates, and LTL formula. Rabin automata can be based on the LTL formula, and the automata can be used to evaluate various candidate trajectories. Nodes of the MCTS can be generated and actions can be explored based on machine learning implemented as, for example, a deep neural network.

Aspects of the present disclosure may include methods, apparatuses, and computer readable media for receiving one or more images having a plurality of objects, receiving a notification from an occupant of the self-driving vehicle, generating an attention map highlighting the plurality of objects based on at least one of the one or more images and the notification, and providing at least one of a steering control or a velocity control to operate the self-driving vehicle based on the attention map and the notification.

A method, system and device are disclosed for determining safety conflicts in redundant subsystems of autonomous vehicles. Each redundant subsystem calculates a world model or path plan, including locations, dimensions, and orientations of moving and stationary objects, as well as projected travel paths for moving objects in the future. The travel paths and projected future world models are subsequently compared using a geometric overlay operation. If at future time moments the projected world models match within predefined margins, the comparison results in a match. In case of a mismatch at a given future moment between projected world models, a determination is made as to whether the autonomous vehicle and all road users in this future moment are safe from collision or driving off the drivable space or road based on a geometric overlay operation.

A method, an apparatus and a system for displaying an image of a vehicle blind spot are provided. The apparatus is coupled to at least one external camera disposed outside the vehicle, at least one internal camera disposed inside the vehicle with a lens facing towards a driver, and at least one display disposed inside the vehicle. The method comprises capturing an image of the external environment of the vehicle by the external camera as an external image, capturing an image including the driver by the internal camera as an internal image, recognizing a face of the driver and a displacement of the face in the internal image, and adjusting a position of an ROI in the external image according to the recognized displacement, to display an image of the ROI on the display corresponding to the external camera. The displayed image of the external of the vehicle may be adjusted according to the posture or the angle of view of the driver, to have the image of the current blind spot by the driver shown correctly.

The present disclosure relates to a driving control apparatus, a driving control method, and a program that can resolve a conflict between a deliberate action and a reflex action during determination of a next action in autonomous driving.

During autonomous driving, a reflex action is determined as a simplified action on the basis of detection results detected by a variety of sensors provided in a vehicle, and a deliberate action ranked higher than a reflex action is determined through elaborate processing. A plurality of resolution modes are made available to deal with a possible conflict between the reflex action and the deliberate action, and by which of the resolution modes the conflict is resolved is specified in advance so that the conflict is resolved by the specified resolution mode. The present disclosure is applicable to motor vehicles that drive autonomously.

Methods and systems for multi-hypothesis object tracking for automated driving systems. One system includes an electronic processor configured to receive environment information and generate pseudo-measurement data associated with an object within an environment of the vehicle. The electronic processor is also configured to determine, based on the environment information and the pseudo-measurement data, a set of association hypotheses regarding the object. The electronic processor is also configured to determine, based on the set of association hypotheses, an object state of the object. The electronic processor is also configured to control the vehicle based on the determined object state.

A method for improving pedestrian safety is provided. The method includes determining operating conditions of a vehicle using a plurality of vehicle sensors. A path of the vehicle is predicted based on the determined operating conditions. Pedestrian parameters for a pedestrian in a vicinity of the vehicle are acquired using the plurality of vehicle sensors. The pedestrian parameters include at least one of a position, a speed of the pedestrian, gait, body posture and a level of distractedness. A determination is made whether a notification of the pedestrian is necessary based on the determined vehicle operating conditions and the acquired pedestrian parameters. A mode of notification of the pedestrian is selected from a plurality of modes of notification, in response to determining that the notification of the pedestrian is necessary. The pedestrian is notified using the selected mode of notification.

Methods, systems, computer-readable media, and apparatuses for executing an event pertaining to a vehicle and a user of the vehicle are presented. In some embodiments, a includes (a) detecting that a motion state of the vehicle is in a first state, (b) detecting a condition that warrants a change in the motion state of the vehicle to a second state, and (c) detecting the user of the vehicle's engagement in an activity that potentially impairs the user from performing an action to change the motion state of the vehicle to the second state. The method also includes, detecting the condition, and (c) detecting the user of the vehicle's engagement in the activity, executing an event to facilitate the change in the motion state of the vehicle to the second state.

A method for autonomously controlling a vehicle is disclosed. In some examples, a vehicle can maneuver out of a parking space in an autonomous and unmanned operation. While parking, the vehicle can capture first one or more images of its surroundings and store the images in a memory included in the vehicle. Upon starting up, the vehicle can capture second one or more images of its surroundings and compare them to the first one or more images to determine if there is an object, person, or animal proximate to the vehicle, for example. In some examples, in accordance with a determination that there is no object, person, or vehicle present that was not present during parking, the vehicle can autonomously move from the parking space with or without a user present in the vehicle.

An in-vehicle system includes: a detection unit that detects visual line information of a passerby on the basis of an image obtained by capturing an image in front of a vehicle; a decision unit that decides a motion of the vehicle on the basis of the visual line information of the passerby which is detected by the detection unit; and operation units which perform processing corresponding to the motion of the vehicle which is decided by the decision unit. As a result, the in-vehicle system can attain an effect capable of improving communication between the vehicle and the passerby on the basis of the visual line information of the passerby.