Techniques and methods for determining regions. For instance, a vehicle may determine a trajectory of the vehicle and a trajectory of an agent, such as a pedestrian. The vehicle may then determine one or more contextual factors. In some examples, the one or more contextual factors are associated with a location of the agent with respect to a crosswalk, a location of the vehicle with respect to the crosswalk, a state of the crosswalk, and/or the like. The vehicle may then determine the region using the trajectory of the vehicle, the trajectory of the agent, and the one or more contextual factors. Additionally, using a time buffer value and a distance buffer value associated with the region, the vehicle may determine whether to yield to the agent within the region.

Methods of assessing driver behavior include monitoring vehicle systems and driver monitoring systems to accommodate for a driver's slow reaction time, attention lapse and/or alertness. When it is determined that a driver is drowsy, for example, the response system may modify the operation of one or more vehicle systems. The systems that may be modified include: visual devices, audio devices, tactile devices, antilock brake systems, automatic brake prefill systems, brake assist systems, auto cruise control systems, electronic stability control systems, collision warning systems, lane keep assist systems, blind spot indicator systems, electronic pretensioning systems and climate control systems.

The present disclosure is directed generating candidate trajectories and selecting one of them to be implemented. In particular, a computing system can obtain an initial travel path for an autonomous vehicle. The computing system can obtain sensor data describing objects within an environment of the autonomous vehicle. The computing system can generate a plurality of trajectories for the autonomous vehicle based on the sensor data and the initial travel path. The computing system can determine whether the initial travel path, an offset profile, and a velocity profile meet flatness criteria. In response to determining that the initial travel path, the offset profile, and the velocity profile meet the flatness criteria, the computing system can combine the initial travel path, the offset profile, and the velocity profile into the respective trajectory. The computing system can determine a trajectory from the plurality of trajectories.

Directional stimuli are applied to a vehicle operator to enhance the operator's situational awareness. Characteristics within a vehicle's external environment may be assessed to determine whether they present at least a threshold safety risk. If so, a type and/or intensity of a directional stimulus to apply to the vehicle operator may be determined. In addition, one or more output devices may be selected to apply the directional stimulus. The selected output devices may, upon activation, apply the directional stimulus from a same direction as the underlying directionality, in relation to the vehicle, of a potential safety hazard present in the vehicle's external environment. In this manner, the applied stimulus not only elicits an immediate rise in the vehicle operator's situational awareness, but also immediately informs her—based on the direction from which the stimulus is applied/received—of the directionality of the potential safety hazard within the vehicle's external environment.

An autonomous driving system acquires information concerning a vehicle density in an adjacent lane that is adjacent to a lane on which an own vehicle is traveling, when the own vehicle travels on a road having a plurality of lanes. The autonomous driving system selects the adjacent lane as an own vehicle travel lane, when the vehicle density in the adjacent lane that is calculated from the acquired information is lower than a threshold density that is determined in accordance with relations between the own vehicle and surrounding vehicles. The autonomous driving system performs lane change to the adjacent lane autonomously, or propose lane change to the adjacent lane to a driver, when the adjacent lane is selected as the own vehicle travel lane.

A method and system for positioning a vehicle in relation to each moving target of an ordered set of moving targets. Each of the moving targets moves from an initial position at a constant velocity. Embodiments can compute an estimated time for the vehicle to be positioned within a predetermined proximity of one of the moving targets; compute an estimated location of the moving target at the estimated time, based on a current position of the moving target and the constant velocity of the moving target, and compute a required velocity for the vehicle to move from its current position to reach the estimated location by the estimated time. If the required velocity is less than or equal to a maximum velocity of the vehicle, outputting the estimated time and the estimated location for use in positioning the vehicle.

A vehicle includes a surrounding information detector detecting at least one of a position and a speed of an object around the vehicle including a vehicle ahead and a vehicle behind, a vehicle information sensor detecting at least one of a speed and an acceleration of the vehicle, a brake module generating a braking force to decelerate the vehicle, and a controller configured to determine probabilities of a forward collision and a rear-end collision based on output of the surrounding information detector and the vehicle information sensor, determine target forward and rear collision speeds to minimize a sum of injuries to an occupant by the forward collision and injuries to the occupant by the rear-end collision upon determination that there is the probabilities of the forward collision and the rear-end collision, and control the brake module based on the target forward collision speed and the target rear-end collision speed.

An autonomous driving system acquires information concerning a vehicle density in an adjacent lane that is adjacent to a lane on which an own vehicle is traveling, when the own vehicle travels on a road having a plurality of lanes. The autonomous driving system selects the adjacent lane as an own vehicle travel lane, when the vehicle density in the adjacent lane that is calculated from the acquired information is lower than a threshold density that is determined in accordance with relations between the own vehicle and surrounding vehicles. The autonomous driving system performs lane change to the adjacent lane autonomously, or propose lane change to the adjacent lane to a driver, when the adjacent lane is selected as the own vehicle travel lane.

Aspects of the disclosure relate to an autonomous vehicle that may detect other nearby vehicles and designate stationary vehicles as being in one of a short-term stationary state or a long-term stationary state. This determination may be made based on various indicia, including visible indicia displayed by the detected vehicle and traffic control factors relating to the detected vehicle. For example, the autonomous vehicle may identify a detected vehicle as being in a long-term stationary state based on detection of hazard lights being displayed by the detected vehicle, as well as the absence of brake lights being displayed by the detected vehicle. The autonomous vehicle may then base its control strategy on the stationary state of the detected vehicle.

Systems and methods are described herein for managing communications for a connected vehicle, such as between the connected vehicle and other connected vehicle and/or between the connected vehicle and infrastructure entities, such as providers of services to the connected vehicle. For example, a communication network, such as a network provided by a network carrier, may include various cloud engines or other network-based servers that manage, coordinate, and/or provision communications between the connected vehicle and other parties, such as vehicles, road devices, buildings, and other infrastructure entities.