A traveling assistance device provided on a traveling assistance target vehicle 11 includes: an outside-vehicle information acquisition unit that acquires outside-vehicle information; a communication unit that communicates with a traveling assistance management device 15 providing leading vehicle information; and a traveling control unit that performs following traveling control for traveling while following a leading vehicle indicated by leading vehicle information acquired from the traveling assistance management device. The following traveling control is performed using the outside-vehicle information acquired by the outside-vehicle information acquisition unit and the leading vehicle information. The traveling assistance management device 15 that manages the traveling assistance at a position away from the vehicle includes: a communication unit that communicates with the traveling assistance target vehicle 11; and an information processing unit that selects, as a leading vehicle, a candidate vehicle 12-1 scheduled to travel in a traveling schedule route of the traveling assistance target vehicle at a traveling schedule time of the traveling assistance target vehicle from candidate vehicles in response to a request for leading vehicle information from the traveling assistance target vehicle, and notifies the traveling assistance target vehicle of leading vehicle information indicating the leading vehicle. Following traveling is automatically and efficiently achievable.

A system for operating a vehicle includes an object-detector, and operator-monitor, and a controller. The object-detector is used to detect one or more targets proximate to a host-vehicle, said host-vehicle operable in an autonomous-mode and a manual-mode. The operator-monitor is used to detect a gaze-direction of an operator of the host-vehicle. The controller-circuit is in communication with the object-detector and the operator-monitor. The controller-circuit is configured to determine a classification of each target detected by the object-detector. The classification includes a primary-target and an ignored-target. The controller-circuit is further configured to determine that a hand-over of operation of the host-vehicle from the autonomous-mode to the manual-mode is recommended, perform a verification that the operator has gazed at each primary-target more recently than a primary-time, and in response to the verification, execute the hand-over.

A method and a system determine visibility distances based on a dynamic Field of View (FoV) of a subject vehicle. A vehicle incorporates the system. Map polygons are created, each of which determines edges of a road in a map of the surroundings of the subject vehicle. Further, visible areas are determined in the map by intersecting the map polygons with the dynamic FoV. Based on the visible areas, a visibility distance for the road is determined.

Embodiments of the present invention provide an autonomous vehicle with an emergency escape mode. When fleeing a scene is critical, embodiments provide an AV that can operate in an emergency escape mode (EEM) to enable the AV to flee a scene, protecting its occupants. Typically, a passenger or operator invokes EEM in an AV when they are in imminent danger from criminal activity such as carjacking. A least resistance route can be computed to determine an escape route that provides for reduced chance of injury and/or increased probability of a successful escape.

Aspects of the present disclosure describe systems, methods, and devices for automated vehicular control based on glare detected by an optical system of a vehicle. In some aspects, automated control includes controlling the operation of the vehicle itself, a vehicle subsystem, or a vehicle component based on a level of glare detected. According to some examples, controlling the operation of a vehicle includes instructing an automatically or manually operated vehicle to traverse a selected route based on levels of glare detected or expected along potentials routes to a destination. According to other examples, controlling operation of a vehicle subsystem or a vehicle component includes triggering automated responses by the subsystem or the component based on a level of glare detected or expected. In some additional aspects, glare data is shared between individual vehicles and with a remote data processing system for further analysis and action.

This application discloses a computing system to implement object tracking in an assisted or automated driving system of a vehicle. The computing system can assign a pre-classification to a detection event in an environmental model, update the environmental model with new sensor measurements and corresponding detection events over time, and track the detection event in the updated environmental model. The computing system can track the detection event by predicting a future state of the detection event with a state change model selected based on the assigned pre-classification, comparing the predicted future state to an actual future state of the detection event in an update to the environmental model, and determining the detection event corresponds to an object proximate to the vehicle based on the comparison. A control system for the vehicle can control operation of the vehicle based, at least in part, on the tracked detection event.

The invention is concerned with a method for controlling a vehicle (10) when an obstacle (18) is detected in surroundings (39) of the vehicle (10), wherein an autonomous driving function of the vehicle (10) plans a trajectory (15). An observer function (23) determines and/or adapts a size of a dynamic protection zone (26) that extends in a current driving direction (13), wherein the size depends on a current driving speed of the vehicle (10), wherein the observer function determines whether the obstacle (18) is detected within the dynamic protection zone (26), and in the case the obstacle (18) is detected, a limiter function (29) is signaled by the observer function, wherein the limiter function (29) is provided in the signal path (30) and the limiter function (29) reduces speed values of the planned trajectory (15) without influencing the line (25) of the movement of the vehicle (10), thereby causing the observer function (23) to shrink the dynamic protection zone (26) until the obstacle (18) lies outside the shrunken dynamic protection zone (26).

Understanding the intent of human drivers and adapting to their driving styles is used to increased efficiency and safety of autonomous vehicles (AVs) by enabling them to behave in safe and predictable ways without requiring explicit inter-vehicle communication. A Social Value Orientation (SVO), which quantifies the degree of an agent's selfishness or altruism, is estimated by the AV for other vehicles to better predict how they will interact and cooperate with others. Interactions between agents are modeled as a best response game wherein each agent negotiates to maximize their own utility. A dynamic game solution uses the Nash equilibrium, yielding an online method of predicting multi-agent interactions given their SVOs. This approach allows autonomous vehicles to observe human drivers, estimate their SVOs, and generate an autonomous control policy in real time.

Provided are autonomous vehicles (AV), computer program products, and methods for maneuvering an AV in a roadway, including receiving forecast information associated with predicted trajectories of one or more actors in a roadway, determining a relevant trajectory of an actor based on correlating a forecast for predicted trajectories of the actor with the trajectory of the AV, regenerate a distance table for the relevant trajectory previously generated for processing constraints, generate a plurality of margins for the AV to evaluate, the margins based on a plurality of margin types for providing information about risks and effects on passenger comfort associated with a future proximity of the AV to the actor, classifying an interaction between the AV and the actor based on a plurality of margins, and generating continuous scores for each candidate trajectory that is also within the margin of the actor generated for the relevant trajectory.

A context-aware safety device includes a wireless transceiver, a memory storing an application, and one or more processors. When executing the application, the one or more processors are configured to determine a context of a safety device, configure an alert based on the determined context, and broadcast the configured alert using the wireless transceiver.