The present disclosure relates generally to autonomous vehicles, and more specifically to techniques for representing trajectories of objects such as traffic participants (e.g., vehicles, pedestrians, cyclists) in a computationally efficient manner (e.g., for multi-object tracking by autonomous vehicles). An exemplary method for generating a control signal for controlling a vehicle includes: obtaining a parametric representation of a trajectory of a single object in the same environment as the vehicle; updating the parametric representation of the single-object trajectory based on data received by one or more sensors of the vehicle within a framework of multi-object and multi-hypothesis tracker; and generating the control signal for controlling the vehicle based on the updated trajectory of the object.

A system for an autonomous vehicle that predicts a location-based maneuver of a remote vehicle located in a surrounding environment includes one or more vehicle sensors collecting sensory data indicative of one or more vehicles located in the surrounding environment. The system also includes one or more automated driving controllers in electronic communication with the one or more vehicle sensors. The one or more automated driving controllers execute instructions to compare a lane of travel of the remote vehicle with a current lane of travel of the autonomous vehicle. In response to determining the lane of travel of the remote vehicle is a different lane than the current lane of the autonomous vehicle, the one or more automated driving controllers predict the location-based maneuver of the remote vehicle based on aggregated vehicle metrics that are based on historical data collected at the specific geographical location.

An object detection device includes first and second detectors each configured to detect an object by transmitting an ultrasonic wave in a moving direction of the moving object and receiving a reflected wave of the ultrasonic wave, a second detector, a memory, and a hardware processor coupled to the memory, and configured to: determine that an obstacle is present in the moving direction of the moving object, based on object detection results by the first and second detectors; determine crossing of the obstacle based on object detection results by the first and second detectors in a state in which it is being determined that the obstacle is present; and cause a driving controller mounted on the moving object, to release driving restriction control of restricting movement of the moving object when determining the crossing, or prohibit the driving controller from releasing the driving restriction control under a predetermined condition.

A travelling support system includes a receiving unit configured to receive parked/stopped vehicle information indicating a detection of a parked/stopped vehicle on a travelling road from a preceding vehicle which is travelling or a sensor on the travelling road; and a predicting unit that predicts, based on the parked/stopped vehicle information and a duration predicting model that predicts a parked/stopped duration as a duration in which the parked/stopped vehicle continues to park or stop, the parked/stopped duration.

A system for controlling stop of a vehicle includes a steering angle comparison device that detects a current steering angle of the vehicle and compares the detected current steering angle with a preset limit steering angle when a malfunction of a steering system in the vehicle is detected during autonomous driving, a partial braking induction determination device that determines a position of a tire of the vehicle to be subjected to partial braking for steering control of the vehicle according to a result of the comparing between the current steering angle and the limit steering angle, and a partial braking control device that determines an amount of braking to be applied to each determined tire of the vehicle and applies a braking pressure corresponding to the amount of braking to each tire of the vehicle to perform the steering control by the partial braking.

A system and method for determining a predicted trajectory of a human-driven host vehicle as the human-driven host vehicle approaches a traffic signal. The method includes: obtaining a host vehicle-traffic light distance d.sub.x and a longitudinal host vehicle speed v.sub.x that are each taken when the human-driven host vehicle approaches the traffic signal; obtaining a traffic light signal phase P.sub.t and an traffic light signal timing T.sub.t; obtaining a time of day TOD; providing the host vehicle-traffic light distance d.sub.x, the longitudinal host vehicle speed v.sub.x, the traffic light signal phase P.sub.t, the traffic light signal timing T.sub.t, and the time of day TOD as input into an artificial intelligence (AI) vehicle trajectory prediction application, wherein the AI vehicle trajectory prediction application implements an AI vehicle trajectory prediction model; and determining the predicted trajectory of the human-driven host vehicle using the AI vehicle trajectory prediction application.

A cruise control method and system, and a vehicle, the method being applied to a first vehicle. When the first vehicle is driving in a first lane, before the first vehicle enters from the first lane into a preset recognition region to thereby complete vehicle identity recognition in the preset recognition region, the cut-in probability of a second vehicle cutting into the first lane can be predicted according to a movement parameter of the second vehicle that is in an adjacent second lane, and it is determined, according to the cut-in probability and the stopping time of the first vehicle, whether to brake to stop the first vehicle; therefore, during the process of controlling the first vehicle to pass through the preset recognition region, the driver is not required to temporarily take over control of the first vehicle.

A driving assist device includes a driving assist controller. The driving assist controller is configured to perform driving assistance when the vehicle changes a course by crossing the oncoming lane. The driving assist controller sets a predicted travel region based on behavior of the oncoming vehicle when the oncoming vehicle is approaching the vehicle that enters an intersection. When the vehicle enters the predicted travel region in a travel path of the vehicle, the driving assist controller determines whether there is a possibility of contact between the vehicle and the oncoming vehicle based on the predicted travel region and the travel path of the vehicle. The driving assist controller causes the vehicle to stop outside of the predicted travel region when there is a possibility of the contact.

A driving assist device includes a driving assist controller. The driving assist controller includes an oncoming vehicle detection unit, a prediction determination unit, a predicted travel region setting unit and a stop controller. The oncoming vehicle detection unit is configured to, when a vehicle enters an intersection, determine whether an oncoming vehicle going to enter the intersection is present. The prediction determination unit is configured to, when the oncoming vehicle detection unit determines that the oncoming vehicle is going to enter the intersection, determine whether a course of the oncoming vehicle is predictable based on vehicle behavior of the oncoming vehicle. The predicted travel region setting unit is configured to set a predicted travel region of the oncoming vehicle based on the vehicle behavior. The stopping controller is configured to cause the vehicle to stop outside of the predicted travel region set by the predicted travel region setting unit.

Aspects of the disclosure relate to methods for controlling a vehicle having an autonomous driving mode. For instance, sensor data may be received from one or more sensors of the perception system of the vehicle, the sensor data identifying characteristics of an object perceived by the perception system. When it is determined that the object is no longer being perceived by the one or more sensors of the perception system, predicted characteristics for the object may be generated based on one or more of the identified characteristics. The predicted characteristics of the object may be used to control the vehicle in the autonomous driving mode such that the vehicle is able to respond to the object when it is determined that the object is no longer being perceived by the one or more sensors of the perception system.