An autonomous vehicle control system is provided. The control system may include a plurality of cameras to acquire a plurality of images of an area in a vicinity of a vehicle; and at least one processing device configured to: recognize a curve to be navigated based on map data and vehicle position information; determine an initial target velocity for the vehicle based on at least one characteristic of the curve as reflected in the map data; adjust a velocity of the vehicle to the initial target velocity; determine, based on the plurality of images, observed characteristics of the curve; determine an updated target velocity based on the observed characteristics of the curve; and adjust the velocity of the vehicle to the updated target velocity.

The present teaching relates to method, system, and medium, for operating a vehicle. The method includes the steps of receiving Real-time data related to the vehicle are received. A current mode of operation of the vehicle is determined. A first risk associated with the current mode of operation of the vehicle is evaluated based on the real-time data in accordance with a risk model. If the first risk satisfies a first criterion, a second risk associated with switching the current mode to a different mode of operation of the vehicle is determined. The vehicle is switched from the current mode to the different mode if the second risk satisfies a second criterion.

A vehicle control device includes a recognizer that is configured to recognize a peripheral situation of a vehicle and a driving controller that is configured to execute automated driving for controlling a speed and steering of the vehicle on the basis of a recognition result of the recognizer. The recognizer is configured to recognize a real-time environment including a situation of a nearby vehicle or a situation of a nearby road on which the vehicle travels, and the driving controller is configured to shunt the vehicle to a shunt location to suspend the automated driving in a case where the real-time environment corresponds to a predetermined condition, and resume the automated driving in a case where the predetermined condition is resolved after the shunt.

A system, comprising a computer having a processor and a memory storing instructions executable by the processor to identify a height of a curb that is at least one of within or bordering a parking area having a specified length and width. The instructions include instructions to identify a location of the curb. The instructions include instructions to determine a parking position within the parking area based on the height of the curb and the location of the curb. The instructions include instructions to park a vehicle at the parking position within the parking area.

A method for controlling a vehicle active chassis power system includes determining, via a processor, a minimum output voltage/current threshold for an aggregated power supply associated with an active chassis operation, and generating an aggregate State of Function (SoF) indicative of a maximum voltage/current budget for an output of the vehicle active chassis power system. The aggregate SoF is based on a primary power source voltage/current output and a power storage voltage/current output. The method further includes causing to control an active chassis power system actuator based on a minimum voltage/current value associated with the aggregate SoF. Causing to control the active chassis power system actuator can include publishing the aggregate SoF to a braking actuator, a steering actuator, or to a domain controller that actively distributes an aggregated power supply capability SoF to a braking actuator and a steering actuator based on one or more present vehicle states.

A vehicle control device includes: a target traveling path setting unit that sets a target traveling path of an own vehicle; a reference position setting unit that sets a reference position of the own vehicle for specifying a position of the own vehicle with respect to the target traveling path; and a control unit that controls a steering assist amount of a steering wheel, based on a positional deviation being a deviation between the target traveling path set by the target traveling path setting unit and the reference position of the own vehicle set by the reference position setting unit. The reference position setting unit changes the reference position according to a vehicle speed.

The steering controller calculates a target steering angle for causing the own vehicle to travel along the target course acquired by the traveling road information acquirer. The braking/driving force controller calculates a target yaw moment for correcting the positional displacement of the own vehicle from the target course. The control ratio setter sets a control ratio of cooperative control of steering control and yaw moment control based on the deviation amount of a lateral position of the own vehicle from the target course. The control ratio is set so that when the positional displacement of the own vehicle from the target course is relatively small, the ratio at which the steering control occupies is reduced, and the yaw moment control is dominant, and when the positional displacement of the own vehicle from the target course is relatively large, the ratio at which the steering control occupies is increased.

The disclosure relates to the process of ascertaining an input variable of a vehicle actuator using a model-based predictive control. According to one exemplary arrangement, a processor unit is designed to access trajectory information and a state data set, which represents a state of surroundings of a vehicle and/or the state of the vehicle and/or a driving state of the vehicle, by an interface. The processor unit carries out a secondary condition algorithm in order to calculate a secondary condition and an MPC algorithm for a model-based predictive control. By carrying out the secondary condition algorithm, a secondary condition is ascertained for the MPC algorithm on the basis of the trajectory information and on the basis of the state data set. By carrying out the MPC algorithm, an input variable is ascertained for an actuator of the vehicle on the basis of the secondary condition. This is carried out in particular such that in a future predicted trajectory, the vehicle follows the specified trajectory with a specified degree of reliability.

A lane departure suppression device including a control unit that executes a lane departure suppression control (automatic steering of the steering wheel and/or a warning being issued) when it is determined that there is a possibility that a vehicle departs from a lane. The control unit does not execute the lane departure suppression control when the control unit determines that a lateral speed and a lateral acceleration of the vehicle are increased within a predetermined time from a time point at which acceleration and deceleration of the vehicle is started, and that there is an adjacent lane on a side with respect to the lane in which the lateral speed and the lateral acceleration are increased.

A system and method for mitigating or avoiding risks due to hazards encountered by platooning vehicles. The system and method involve interrogating, with one or more sensors, a space radially extending from a lead vehicle as the lead vehicle travels over the road surface, perceiving the environment within the space, ascertaining a hazard caused by an object in the space, and causing a following vehicle, operating in a platoon with the lead vehicle, to take a preemptive braking action to avoid or mitigate risks resulting from the hazard caused by the object in the space.