The concepts described herein relate to a calculation of desired future longitudinal horizons related to torque or acceleration, and desired future lateral horizons related to yaw rate and lateral velocity, and their use in response to driver-selectable modes. In the longitudinal direction, driver inputs of pedal and brake position as well as drivability metrics are used to calculate the desired future torque trajectory. In the lateral direction, the front and rear steering angles may be used with a bicycle model to derive the trajectories. The trajectories are used in a vehicle motion controller that uses weighting to tradeoff competing requests and deliver performance that is consistent with a selected driver mode, such as a tour mode, a sport mode, an off-road mode, a trailering mode, etc.

This document describes techniques and systems to indirectly verify speed limits based on contextual information for autonomous and semi-autonomous driving systems. In addition to camera systems, the described techniques and systems use other sensors and secondary factors to improve the accuracy and confidence in detecting posted speed limits. For example, a camera system captures an image or other data directly indicative of a speed limit. Contextual information for the road or vehicles nearby is also obtained and used to determine at least one indirect indication of the speed limit. A composite speed limit is identified by applying a respective weight to the direct and indirect indications of the speed limit. The described systems and techniques thereby enable controlling the vehicle based on the composite speed limit. In this way, the described systems and techniques can verify a speed limit to make autonomous and semi-autonomous driving systems safer.

A vehicle and method for controlling a vehicle having a traction battery and an internal combustion engine include adapting a power limitation of the internal combustion engine by sensing a currently supplied power level of the internal combustion engine and a current velocity of the vehicle, sensing an ambient temperature of the vehicle and determining an associated ambient-temperature-related weighting factor, sensing an ambient air pressure and determining an associated air-pressure-related weighting factor, determining a thermal load indicator as a function of a ratio of the sensed currently supplied power and the sensed current velocity as well as of the ambient-temperature-related weighting factor, the air-pressure-related weighting factor, and a vehicle-bodywork-related weighting factor, and limiting a maximum supplied power level of the internal combustion engine as a function of the determined thermal load indicator.

A method for predicting whether another vehicle in the driving-environment of an ego-vehicle will execute a lane-change, based on observations of the driving-environment of the ego-vehicle, including: the observations are supplied to individual classificators; based on at least a portion of the observations, each individual classificator, in accordance with an individual instruction, ascertains an individual probability that the other vehicle will change lanes; the driving situation in which the ego-vehicle finds itself is classified as a whole by a situation classificator into one of several discrete classes; a record of weighting factors, assigned to the class into which the situation-classificator has classified the driving-situation, is ascertained, that indicates the relative weighting of the individual classificators for this driving situation; the individual probabilities are set off against the weighting-factors to form an overall probability that the other vehicle will change lanes. A method for training weighting-factors and related computer-program are described.

A vehicle includes a driving device configured to control a speed of the vehicle, a camera configured to detect a surrounding vehicle, and a controller configured to determine the speed of the vehicle. The controller also calculates an image vector variation amount of the surrounding vehicle when the speed of the vehicle is lower than a predetermined speed and calculates a safety distance between the vehicle and a preceding vehicle based on the image vector variation amount of the surrounding vehicle when the image vector variation amount of the surrounding vehicle satisfies a predetermined condition. The controller also controls the driving device to control the speed of the vehicle depending on the calculated safety distance.

Provided is a travel evaluation method of making an evaluation related to travel of a vehicle capable of traveling in a leaning position, the method including: obtaining a tire force which is an external force exerted on a wheel of the vehicle from a ground surface; and deriving an evaluation index related to travel of the vehicle. The evaluation index includes a positive evaluation index as a rating of a positive evaluation related to travel of the vehicle. In deriving the evaluation index, the positive evaluation index is set higher as the tire force increases, and the evaluation index is corrected based on an influential parameter other than the tire force.

The invention relates to a method for estimating a current wheel circumference of at least one wheel arranged on a vehicle, said method comprising: determining a reference speed of the vehicle at a point in time by means of a reference apparatus, detecting a wheel rotational speed of the at least one wheel at said point in time by means of a wheel rotational speed sensor, estimating a single wheel-circumference value based on the determined reference speed and the detected wheel rotational speed for said point in time by means of a calculation apparatus, storing at least the estimated single wheel-circumference value in a circular buffer for said point in time, estimating a current wheel circumference based on the single wheel-circumference values stored in the circular buffer by the calculation apparatus, outputting the estimated current wheel circumference as a wheel circumference signal.

The vehicle includes: a sensor part configured to acquire occupancy information of an surrounding area of the vehicle and a speed of the vehicle; a camera configured to acquire a surrounding image of the vehicle; and a controller configured to form map information based on the occupancy information according to movement of the vehicle, determine presence or absence of an obstacle around the vehicle based on the map information and the surrounding image, and control, in response to presence of the obstacle, the vehicle based on the presence of the obstacle and a possibility of collision of the vehicle derived from the speed of the vehicle and the map information.

A system for estimating tire parameters for an off-road vehicle in real time, the system including a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the processing circuit to measure a position of the vehicle at a first time, determine, based on the position, motion characteristics of the vehicle, predict, based on the motion characteristics, a position of the vehicle at a second time, measure a position of the vehicle at the second time, and generate a tire parameter associated with the vehicle based on the predicted position and the measured position of the vehicle at the second time.

Embodiments of the present disclosure set forth a computer-implemented method comprising receiving, from at least one sensor, sensor data associated with an environment, generating, based on the sensor data, a set of lane change data values associated with positions of at least two vehicles relative to a first lane position in the environment, determining, based on the set of lane change data values, a collision risk value associated with the at least two vehicles attempting to occupy the first lane position, and generating, based on the collision risk value, an output signal to a first vehicle included in the at least two vehicles.