A system for estimating a trajectory of a vehicle includes vehicle state sensors detecting a state of movement of the vehicle and environment sensors monitoring an environment of the vehicle. A free space module determines a free space corridor based on the detected state of movement of the vehicle and the monitored environment of the vehicle. A goal point determination module determines at least one goal point for the trajectory to be estimated based on the free space corridor. A trajectory planning module estimates a reference trajectory based on the at least one goal point and calculates a deviation between an actual trajectory and the reference trajectory of the vehicle. A trajectory control module minimizes the deviation between the actual trajectory and the reference trajectory of the vehicle and outputs optimal control parameters for the movement of the vehicle based on the minimized deviation.

A vehicle driving assist device includes an oncoming moving body recognizer configured to recognize an oncoming moving body; a lateral position distribution characteristics acquisition unit configured to acquire distribution characteristics of a lateral position of the oncoming moving body; a risk determination region setting unit configured to set, based on the distribution characteristics, a risk determination region for calculating a risk degree; a risk degree calculator configured to calculate the risk degree for the oncoming moving body; and a preliminary collision avoidance controller configured to recognize the oncoming moving body as the obstacle in accordance with the risk degree, and perform preliminary collision avoidance control in response to the oncoming moving body prior to the emergency collision avoidance control. The risk determination region setting unit is further configured to variably set the risk determination region so that the risk degree relatively increases as the distribution characteristics tend to disperse.

Disclosed herein are system, method, and computer program product embodiments for determining objects that are kinematically capable, even if non-compliant with rules-of-the-road, of affecting a trajectory of a vehicle. The computing system (e.g., perception system, etc.) of a vehicle may generate a trajectory for the vehicle and a respective trajectory for each object of a plurality of objects within a field of view (FOV) of the sensing device associated with the vehicle. The computing system may identify objects of the plurality of objects with trajectories that intersect the trajectory for the vehicle and remove from such objects, objects with trajectories that at least one of exit the FOV or intersect with other objects of the plurality of objects within the FOV. The computing system may select, from remaining objects with trajectories that intersect the trajectory for the vehicle, objects with trajectories that indicate a respective collision between the object and the vehicle and assign a severity of the respective collision.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

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.

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise at least one processor. The processor may be programmed to receive images representative of an environment of the host vehicle and analyze the images to identify a first object and a second object. The processor may determine a first predefined navigational constraint implicated by the first object and a second predefined navigational constraint implicated by the second object, wherein the first and second predefined navigational constraints cannot both be satisfied, and the second predefined navigational constraint has a priority higher than the first predefined navigational constraint. The processor may determine a navigational action for the host vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint and, cause an adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.

Provided are methods, systems, and computer program products for vehicle dynamics classification for collision and loss of control detection. Some methods described also include obtaining sensor data associated with dynamics of a vehicle, wherein the dynamics characterize motion of the vehicle and the vehicle is associated with a dynamics event classification. The methods include obtaining predicted dynamics, wherein the predicted dynamics are based on control signals and feedback on control signals from a previous time instance. Additionally, the methods include determining the dynamics event classification of the vehicle based on the dynamics and the predicted dynamics and controlling operation of the vehicle according to the dynamics event classification.

A driving assist device includes, a traveling environment information acquisition unit, an intersection determination unit, a vehicle position information acquisition unit, a predicted travel path setting unit, a blinker signal acquisition unit, a traffic division information acquisition unit, a determination unit, and a notifier. The determination unit determines whether directions indicated by three factors of traffic division information acquired by the traffic division information acquisition unit; a blinker signal acquired by the blinker signal acquisition unit, and a predicted travel path predicted by the predicted travel path setting unit match each other. When the determination unit determines that directions indicated by two factors of the three factors match each other and a mismatch occurs between the directions indicated by the two factors and a direction indicated by a remaining factor of the three factors, the notifier issues a notification about the mismatch of the direction indicated by the remaining factor.

Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

Embodiments of the present disclosure provide a method, an apparatus and a device for an illegal vehicle warning. The method includes: detecting an illegal vehicle in a preset area; and performing the illegal vehicle warning on a target vehicle entering the preset area according to vehicle information of a detected illegal vehicle in the preset area. In the embodiments of the present disclosure, the traffic control unit detects the illegal vehicle in the preset area, and the illegal vehicle warning is performed on the target vehicle entering the preset area according to the vehicle information of the detected illegal vehicle in the preset area, thereby avoiding or mitigating the collision of the target vehicle with the illegal vehicle, and improving the traffic safety of the target vehicle.