A method of instance segmentation in an image and a system for instance segmentation of images. The method includes identifying, with a processor, a starting pixel associated with an object in an image, the image having a plurality of rows of pixels, the starting pixel located in a row of the plurality of rows; identifying, with the processor, at least one pixel located in an adjacent row to the row in which the starting pixel is located, the at least one pixel being part of the same object as the starting pixel; iterating the previous two identification steps using the at least one identified adjacent row pixel as a start pixel for the next iteration; and connecting, with the processor, the at least one identified adjacent row pixels to form polylines representing the object.

Devices, systems, and methods for a vehicular safety system in autonomous vehicles are described. An example method for safely controlling a vehicle includes selecting, based on a first control command from a first vehicle control unit, an operating mode of the vehicle, and transmitting, based on the selecting, the operating mode to an autonomous driving system, wherein the first control command is generated based on input from a first plurality of sensors, and wherein the operating mode corresponds to one of (a) a default operating mode, (b) a minimal risk condition mode of a first type that configures the vehicle to pull over to a nearest pre-designated safety location, (c) a minimal risk condition mode of a second type that configures the vehicle to immediately stop in a current lane, or (d) a minimal risk condition mode of a third type that configures the vehicle to come to a gentle stop.

A safety system for a vehicle may include one or more processors configured to determine uncertainty data indicating uncertainty in one or more predictions from a driving model during operation of a vehicle; change or update one or more of the driving model parameters to one or more changed or updated driving model parameters based on the determined uncertainty data; and provide the one or more changed or updated driving model parameters to a control system of the vehicle for controlling the vehicle to operate in accordance with the driving model including the one or more changed or updated driving model parameters.

Systems and methods for controlling autonomous vehicle are provided. A method can include obtaining, by a computing system, data indicative of a plurality of objects in a surrounding environment of the autonomous vehicle. The method can further include determining, by the computing system, one or more clusters of the objects based at least in part on the data indicative of the plurality of objects. The method can further include determining, by the computing system, whether to enter an operation mode having one or more limited operational capabilities based at least in part on one or more properties of the one or more clusters. In response to determining that the operation mode is to be entered by the autonomous vehicle, the method can include controlling, by the computing system, the operation of the autonomous vehicle based at least in part on the one or more limited operational capabilities.

A vehicle control device includes a tracking unit estimating a motion of a moving object, a model selection unit selecting a motion model corresponding to a moving object type, an abnormality determination unit determining a presence or absence of an abnormality of the estimation of the motion of the moving object based on the estimated moving object motion and the motion indicated by the motion model, and a control unit. A control mode in which the control unit controls traveling of a host vehicle when the abnormality determination unit determines that the abnormality is present differs from a control mode in which the control unit controls the traveling of the host vehicle when the abnormality determination unit determines that the abnormality is absent.

The present technology is directed to customizing a driving behavior of an autonomous vehicle (AV) and verifying safety of the driving behavior based on a simulation. An AV management system can determine driving parameter(s) relating to a driving behavior of an AV and determine a degree of similarity between the driving parameters and a plurality of stored driving parameters. Based on a determination that the degree of the similarity is outside of a predetermined range, the AV management system can generate a scenario to test a safety of the driving parameters, perform a simulation of the AV in the scenario, and compare a simulation result with a predetermined safety threshold. Based on a determination that the simulation result is equal to or above the predetermined safety threshold, the AV management system can adjust the driving behavior of the AV based on the driving parameters.

A vehicle control system includes an acquirer that acquires information that allows recognition of a speed of another vehicle in a travel direction of an own vehicle, a determiner that determines whether or not a low speed section whose travel speed is equal to or less than a first predetermined speed is present in the travel direction of the own vehicle on the basis of the information acquired by the acquirer, and a controller that is able to perform an automated driving mode which is executed at a second predetermined speed or less and that performs predetermined control before the own vehicle reaches the low speed section that has been determined as being present by the determiner.

A vehicle control apparatus includes a first control unit and a second control unit each configured to perform travel control of a vehicle based on a recognition result of an external recognition device group configured to obtain external information of the vehicle and a detection result of a vehicle information detection unit configured to obtain state information of an actuator group of the vehicle. In a case in which functional degradation of at least one of the external recognition device group, the actuator group, and the vehicle information detection unit is detected, based on the recognition result and the detection result, the first control unit determines contents of vehicle control in fallback control for restricting a travel control function of the vehicle and determines whether to execute the fallback control by one of the first control unit and the second control unit.

The present invention refers to a method for providing a multi-lane scenario driving support for an ego vehicle (10) in a traffic situation. Traffic surroundings are measured by an environment sensor system (14), whereby the traffic surroundings include data about traffic and free space within an ego lane (16) of the ego vehicle (10) and at least an adjacent lane (12a, 12b), and data about front proximity area (18) and rear proximity area (20) of the ego vehicle (10). A decision device (22) evaluates the measured traffic surroundings and decides a driving operation to be executed by the ego vehicle (10) based on at least one strategy. In the decision device (22) a cost function is used for choosing one of at least six strategies, the cost function being based on at least a core priority, whereby the core priority is to avoid collision of the ego vehicle (10) and not cause collision of the ego vehicle (10) with a third party vehicle (24. The decision device (22) by means of the cost function chooses one of at least the following six strategies: braking in the ego lane (16), to combine braking and steering within the ego lane (16) of the ego vehicle (10), steering within the ego lane (16) of the ego vehicle (10) to avoid an obstacle, to full-brake in the ego lane (16) of the ego vehicle (10), to combine braking and steering towards or when entering temporarily an adjacent lane (12a, 12b) and steering towards or when entering temporarily an adjacent lane (12a, 12b).

An autonomous vehicle brake failure handling method is provided. The method includes detecting a brake system failure of the autonomous vehicle and transmitting a rescue request signal to a control server when the failure is detected. A bumper of the autonomous vehicle is moved into contact with a preceding autonomous vehicle bumper or the autonomous vehicle is docked with the preceding autonomous vehicle through speed control and steering control. The autonomous vehicle having the failure-detected brake system is completely braked under deceleration control of the preceding autonomous vehicle when the autonomous vehicle bumper and the preceding autonomous vehicle bumper are in contact with each other or when the docking of the autonomous vehicle and the preceding autonomous vehicle has been completed.