Aspects of the disclosure relate to controlling a first vehicle in an autonomous driving mode. While doing so, a second vehicle may be identified. This vehicle may be determined to be a tailgating vehicle. An initial allowable discomfort value representing expected discomfort of an occupant of the first vehicle and expected discomfort of an occupant of the second vehicle may be identified. Determining a speed profile for a future trajectory of the first vehicle that meets the value may be attempted based on a set of factors corresponding to a reaction of the tailgating vehicle. When a speed profile that meets the value cannot be determined, the value may be adjusted until a speed profile that meets the value is determined. The speed profile that meets an adjusted value is used to control the first vehicle in the autonomous driving mode.

Technologies and techniques for determining a trajectory of an assisted-operated motor vehicle. At least one object is detected in an environment of the motor vehicle and at least one uncertainty with respect to the object is determined. A future environment with the object is predicted via an electronic computing device, as a function of the detected environment and the detected object, wherein a risk value for a planned trajectory is determined on the basis of a collision probability. A most probable impact constellation and accident severity for the most probable impact constellation is determined, wherein the collision probability and the accident severity is weighted in a risk value, and wherein the trajectory is determined as a function of the determined risk value.

A sensor fusion system and method are disclosed. One or more processors are operable to receive a plurality of object detection measurements from a plurality of sensors. Each of the plurality of object detection measurements are associated with a potential object detection track. A plurality of sensor confidence values associated with each of the plurality of sensors are received. A track confidence value is determined for each of the potential object detection tracks based on the received plurality of object detection measurements and the received plurality of sensor confidence values. An object detection for a potential object detection track that has a determined track confidence value meeting a predetermined detection threshold is then determined, or confirmed, and stored in a memory for subsequent use, and is relatively unaffected by a measurement from a sensor that has a field of view that omits or is occluded with respect to the given object detection track.

A travel control apparatus is configured to control a travel of a vehicle so as to travel along a target path. The travel control apparatus is configured to perform: acquiring a change schedule information of a traffic light installed over each of a plurality of merge lanes that merge with a main line and configured to be able to change an indication form between a first indication form permitting the vehicle to merge with the main line and a second indication form instructing the vehicle to stop before a stop line; determining a merge lane on which the vehicle travels among the plurality of merge lanes, based on the change schedule information of a traffic light located in a travel direction of the vehicle; and generating a target path of the vehicle leading to the stop line of the merge lane.

A vehicle includes an engine, an accelerator pedal, and a controller. The controller is programmed to command torque to the engine based on a set speed of adaptive cruise control and is programmed to, in response to the adaptive cruise control being active, a measured lateral acceleration of the vehicle exceeding a user-defined lateral acceleration threshold during a road curve, and the accelerator pedal being released, reduce a speed of the vehicle below the set speed until the measured lateral acceleration is less than the lateral acceleration threshold.

Systems and methods for vehicle motion control are provided. The method includes: calculating a correction factor using one of three different sets of operations when the vehicle is performing a limit handling maneuver, wherein the correction factor is calculated using a first set of operations when the vehicle is operating in an understeer state, calculated using a second set of operations when the vehicle is operating in an oversteer state, and calculated using a third set of operations when the vehicle is operating in a neutral steer state; adjusting a desired lateral acceleration and a desired yaw rate by applying the correction factor to account for a reduced level of friction experienced by the vehicle when traveling on a non-ideal friction surface; calculating optimal control actions based on the adjusted desired lateral acceleration and adjusted desired yaw rate; and applying the optimal control actions with vehicle actuators during vehicle operations.

The present disclosure relates to a driver controlling system for a vehicle, a vehicle comprising such a driver controlling system, a driver controlling method for a vehicle and a computer program element for such a driver controlling system.

The driver controlling system comprises a longitudinal control means, a lateral control means and a control unit. The longitudinal control means and the lateral control means are arrangeable in the vehicle. The control unit is configured to determine at least one of a longitudinal adjustment parameter and a later adjustment parameter to propel the vehicle in an automated mode. The control unit is configured to prompt the longitudinal control means to apply the longitudinal adjustment parameter of the vehicle and/or the lateral control means to apply the lateral adjustment parameter in the automated mode. The control unit is further configured to modify at least one of the longitudinal adjustment parameter and the lateral adjustment parameter to be applied in the vehicle by a defined rate of deviation for causing a reaction of the driver.

Among other things, we describe techniques for operation of a vehicle based on measured load characteristics and/or passenger comfort. One or more sensors of the vehicle can measure passenger data and/or load data of the vehicle. The passenger data and/or load data of the vehicle can be used by the vehicle to determine how to navigate within the surrounding environment.

A travel control device for a vehicle, includes: a lane information acquisition unit configured to acquire lane information; a steering control unit configured to control steering of the vehicle by executing lane travel control to make the vehicle travel along the lane; and a vehicle speed control unit configured to control a vehicle speed by executing constant speed travel control in which the vehicle is made to travel at a set vehicle speed and/or adaptive cruise control in which the vehicle is made to travel at a speed equal to or lower than the set vehicle speed so as to follow a preceding vehicle. The vehicle speed control unit is configured to control the vehicle speed during a turn of the vehicle by setting a vehicle speed upper limit value, which is set to different values depending on whether the lane travel control is being executed.

The technology employs a variable motion control envelope that enables an on-board computing system of a self-driving vehicle to estimate future vehicle driving behavior along an upcoming path, in order to maintain a desired amount of control during autonomous driving. Factors including intrinsic vehicle properties, extrinsic environmental influences and road friction information are evaluated. Such factors can be evaluated to derive an available acceleration model, which defines an envelope of maximum longitudinal and lateral accelerations for the vehicle. This model, which may identify dynamically varying acceleration limits that can be affected by road conditions and road configurations, may be used by the on-board control system (e.g., a planner module of the processing system) to control driving operations of the vehicle in an autonomous driving mode.