A navigation system for a host vehicle may include a processing device including circuitry and a memory storing instructions that when executed by the circuitry cause the at least one processing device to receive images acquired by a camera representative of an environment of the host vehicle, and analyze the images to identify a double merge scenario including a first flow of traffic and a second flows of traffic in a same direction that merge to form a merged flow of traffic in a merged lane. The instructions that when executed by the circuitry may further cause the processing device to cause a navigational change in the host vehicle based on a trajectory of a first target vehicle in the first flow of traffic and a trajectory of a second target vehicle in the second flow of traffic.

A vehicle control device includes: a three-dimensional object detecting unit, an oncoming vehicle detecting unit, and an erroneous detection determination unit. The three-dimensional object detecting unit detects a three-dimensional object provided between a travel lane in which a host vehicle travels and an opposite lane in which an oncoming vehicle travels. The oncoming vehicle detecting unit detects the oncoming vehicle traveling in the opposite lane. The erroneous detection determination unit determine that the oncoming vehicle detected by the oncoming vehicle detecting unit has been erroneously detected when the oncoming vehicle detected by the oncoming vehicle detecting unit is present within a threshold range from the three-dimensional object detected by the three-dimensional object detecting unit.

A collision visualization device includes an identification unit analyzing vehicle traveling information in which information representing at least a type and occurrence time of an event generated in a vehicle to be analyzed in a time period including occurrence time of a collision or each of a series of collisions occurring for the vehicle, is recorded in accordance with occurrence order, and identifying a state of the vehicle in the time period, and a visualization unit causing a display device to display an iconic image representing the state of the vehicle identified by the identification unit.

This disclosure describes an autonomous vehicle configured to obtain sensor data associated with objects proximate a projected route of the autonomous vehicle, determine static constraints that limit a trajectory of the autonomous vehicle along the projected route based on non-temporal risks associated with a first subset of the f objects, predict a position and speed of the autonomous vehicle as a function of time along the projected route based on the static constraints, identify temporal risks associated with a second subset of the objects based on the predicted position and speed of the autonomous vehicle, determine dynamic constraints that further limit the trajectory of the autonomous vehicle along the projected route to help the autonomous vehicle avoid the temporal risks associated with the second subset of the objects, and adjust the trajectory of the autonomous vehicle in accordance with the static constraints and the dynamic constraints.

Systems and methods for selecting a trajectory for an autonomous vehicle based on perceived risk are provided. A trajectory is selected that satisfies objective safety constraints and minimizes an overall cost based at least in part on cost components representing the perceived risk of the trajectory. The vehicle is navigated according to the selected (e.g., optimized) trajectory.

A driving assistance device configured to execute deceleration assistance for a driver's vehicle when the driver's vehicle turns right or left at an intersection is configured to recognize, based on a detection result from an external sensor of the driver's vehicle, an adjacent vehicle traveling in an adjacent lane adjacent to a traveling lane of the driver's vehicle, determine whether the adjacent vehicle turns in the same direction of the driver's vehicle at the intersection based on the detection result from the external sensor when the adjacent vehicle is recognized and the driver's vehicle turns right or left at the intersection, and execute the deceleration assistance to cause a vehicle-to-vehicle distance between the driver's vehicle and the adjacent vehicle to reach a distance equal to or larger than a target driver's vehicle-to-adjacent vehicle distance when the driving assistance device determines that the adjacent vehicle turns in the same direction.

Methods and devices for generating a trajectory for a self-driving car (SDC) are disclosed. The method includes: for a given one of the plurality of trajectory points of a given trajectory: (i) determining a presence of plurality of dynamic objects around the SDC, (ii) applying a first algorithm to determine a set of collision candidates, (iii) generating a segment line for the SDC, (iv) generating a bounding box for each of set of collision candidates, (v) for a given one of the set of collision candidates, determining a distance between the segment line and the respective bounding box to determine a separation distance, (vi) in response to the separation distance being lower than a threshold, determining that the given one of the set of collision candidates would cause the collision with the SDC, (vii) amending at least one of the plurality of trajectory points to render a revised candidate trajectory.

A vehicular collision avoidance system includes a forward-viewing camera viewing through the windshield at least forward of the equipped vehicle, a rearward-sensing radar sensor sensing at least rearward of the equipped vehicle, and an electronic control unit. The vehicular collision avoidance system detects vehicles present forward and/or rearward of the equipped vehicle. Responsive to data processing of radar data captured by the rearward-sensing radar sensor, the vehicular collision avoidance system detects another vehicle approaching the equipped vehicle from the rear, determines distance between the equipped vehicle and the other vehicle, and determines speed difference between the equipped vehicle and the other vehicle. Based at least in part on the determined distance between the equipped vehicle and the other vehicle and the determined speed difference between the equipped vehicle and the other vehicle, the vehicular collision avoidance system controls the equipped vehicle to mitigate impact by the other vehicle.

A vehicle condition estimation method performed by an information processing device including a processor and a memory connected to the processor to estimate a position or a condition of a vehicle, includes: acquiring an image including a vehicle to be estimated; and estimating the position or the condition of the vehicle to be estimated, using a line segment connecting at least two points selected from a region in which the vehicle to be estimated is captured in the image, with reference to an imaging device that has captured the image.

The vehicle control device sets a region including a stationary object on a road, calculates a passing position at which a host vehicle and an oncoming vehicle pass each other in accordance with a velocity of the host vehicle and a position and a velocity of the oncoming vehicle, calculates a first score that is a larger value as the velocity of the oncoming vehicle is greater, calculates a second score that is a larger value as an acceleration rate of the oncoming vehicle is greater, integrates the first score with the second score so as to calculate an integration score, and causes the host vehicle to decelerate when the integration score is greater than or equal to a predetermined value or causing the host vehicle to keep the velocity or accelerate when the integration score is smaller than the predetermined value.