A method of controlling a vehicle having wheels provided with tires resting on a surface, the method using a model of the physical behavior of each tire as a function of a sideslip angle (β.sub.ij) for each tire relative to the surface. The model is obtained by implementing an adaptive algorithm that selectively applies an affABREGEine model (Z1), a DUGOFF model (Z2), or a constant model (Z3).

Connected and automated vehicles (CAVs) have shown the potential to improve safety, increase road throughput, and optimize energy efficiency and emissions in several complicated traffic scenarios. This invention describes a mixed-integer programming (MIP) optimization method for global multi-vehicle decision making and motion planning of CAVs in a highly dynamic environment that consists of multiple human-driven, i.e., conventional or manual, vehicles and multiple conflict zones, such as merging points and intersections. The proposed approach ensures safety, high throughput and energy efficiency by solving a global multi-vehicle constrained optimization problem. The solution provides a feasible and optimal time schedule through road segments and conflict zones for the automated vehicles, by using information from the position, velocity, and destination of the manual vehicles, which cannot be directly controlled. Despite MIP having combinatorial complexity, the proposed formulation remains feasible for real-time implementation in the infrastructure, such as in mobile edge computers (MECs).

Methods and systems are provided for controlling an autonomous vehicle. In one embodiment, a method includes: identifying, by a processor, at least one constraint on a longitudinal dimension of an upcoming road; defining, by the processor, constraint activation logic based on a type of the at least one constraint; performing, by the processor, the constraint activation logic to determine a state of the constraint to be at least one of active and inactive; when the state of the constraint is active, validating, by the processor, a motion plan of the autonomous vehicle based on the constraint; and selectively controlling the autonomous vehicle based on the validating of the motion plan.

A vehicle includes: an input configured to receive a destination; a display; a driver assistance system configured to control a behavior of the vehicle based on surrounding environment information; and a controller configured to control the display to display a driving route. The controller may be configured to determine, when a distance between a branch point on the driving route and the vehicle reaches a first distance, a possibility that the vehicle deviates from the driving route based on GPS information, vehicle speed information, and the surrounding environment information, and search for, when the possibility is greater than or equal to a preset threshold, a deviation route for reaching the destination based on the deviated direction and control the display to display the deviation route until the distance between the branch point on the driving route and the vehicle reaches a second distance.

An information processing system, including: a surveillance camera that detects a plurality of obstacles in the vicinity of a specific vehicle; a first determiner that determines whether an unidentified obstacle, which is included in the plurality of obstacles and is not visible from the specific vehicle, is present based on first information regarding the plurality of obstacles detected by the surveillance camera and vehicle information indicating the specific vehicle; and a first communicator that outputs information indicating the unidentified obstacle to the specific vehicle when the first determiner determines that the unidentified obstacle is present.

A method for controlling motion of a vehicle, the method comprising the steps of: obtaining input information on a vector related to the velocity of said vehicle; computing repeatably a future trajectory of said vehicle based on said input information and trial torques to be applied to at least one wheel of said vehicle for optimizing said future trajectory in view of a target vehicle motion, thereby obtaining target trial torques; and applying the obtained target trial torques to the at least one wheel for controlling the motion of said vehicle.

A method of maintaining stability of a motor vehicle having a first axle, a second axle, and a steering actuator configured to steer the first axle includes determining localization and heading of the vehicle. The method also includes determining a current side-slip angle of the second axle and setting a maximum side-slip angle of the second axle using the friction coefficient at the vehicle and road surface interface. The method additionally includes predicting when the maximum side-slip angle would be exceeded using the localization, heading, and determined current side-slip angle as inputs to a linear computational model. The method also includes updating the model using the prediction of when the maximum side-slip angle would be exceeded to determine impending instability of the vehicle. Furthermore, the method includes correcting for the impending instability using the updated model and the maximum side-slip angle via modifying a steering angle of the first axle.

Disclosed are apparatuses and methods for controlling the steering of an autonomous vehicle. The apparatus including an electric power steering device to generate an assist torque for a steering wheel, an autonomous driving position controller to control a steering position according to a command steering angle input from an autonomous driving module, a driver steering intervention judger to judge whether a driver intervenes in steering based on a column torque and a vehicle speed, a weight detector to detect a weight for integrating output of an electric power steering device and output of an autonomous driving position controller based on judging whether the driver intervenes in steering, and an output controller to apply the weight to the output of the electric power steering device and the output of the autonomous driving position controller to integrate the output of the electric power steering device and the output of the autonomous driving position controller, wherein the autonomous driving position controller is further configured to adjust a gain value for controlling the steering position by applying the weight.

An information processing apparatus includes: a point group data acquisition unit configured to acquire, based on information from a sensor configured to detect an object existing in surroundings of a vehicle, point group data related to a plurality of points representing the object; a movement amount estimation unit configured to estimate a movement amount of the vehicle; a storage unit configured to store, as a point group map recorded in association with position information including a latitude and a longitude, relative positions of the plurality of points relative to a first reference position that is a place on a travel path of the vehicle; and a position estimation unit configured to estimate a position of the vehicle based on the point group map, the point group data, and the movement amount.

Aspects of the disclosure provide for generating distributions for hypothetical or potentially occluded objects. For instance, a location for which to generate one or more distributions may be identified. Observations of road users by perception systems of a plurality of autonomous vehicles may be accessed. Each of these observations may identify a characteristic of one of the road users. A distribution of the characteristic for the location may be determined based on the observations. The distribution may be provided to one or more autonomous vehicles in order to enable the one or more autonomous vehicles to use the distribution to generate a characteristic for a hypothetical occluded road user and to respond to the hypothetical occluded road user.