A pull-over control apparatus includes: an input that receives information on a pull-over area determined as a pull-over destination for a vehicle present on a roadway and information on an object recognized in the pull-over area; and a controller that recognizes the pull-over area while dividing the pull-over area into a plurality of partial areas, based on the information on the pull-over area, the plurality of partial areas including at least a first partial area closest to the vehicle and a second partial area adjacent to the first partial area, the controller controlling, based on the information on the object, the vehicle so that the vehicle is pulled over to a first range where pull-over of the vehicle is possible among the plurality of the partial areas.

In a control device for a vehicle , state information indicating a state of a driver, environmental information indicating an environment around the vehicle, and vehicle information are acquired. An object existing in a vicinity of the vehicle to be alerted to the driver is detected from the environmental information. At one of a process for determining whether to output a warning that the object exists and a process for setting an intensity of the warning to be output is executed based on at least one of the state information and the environmental information when the detection unit detects the object. The warning is output according to a result of the process.

Various technologies described herein pertain to causing presentation on a user interface of an immediate portion of a navigation route of an autonomous vehicle. A computing system of the autonomous vehicle determines whether an object detected by sensor(s) of the autonomous vehicle proximate to the immediate portion of the navigation route are of a type and relative position defined as one of consequential and inconsequential for a human passenger. In response to determining that an object has both a type and relative position defined as consequential, the computing system causes presentation on the user interface a representation of the object relative to the immediate portion of the navigation route to provide a confidence engendering indication that the autonomous vehicle has detected the object. Otherwise if inconsequential, presentation on the user interface of any representation of the object is not caused by the computing system to avoid creating a confusing presentation.

A control system for controlling a motion of a vehicle to a target driving goal uses a decision-maker configured to determine a sequence of intermediate goals leading to the next target goal by optimizing the motion of the vehicle subject to a first model and tightened driving constraints formed by tightening driving constraints by a safety margin, and uses a motion planner configured to determine a motion trajectory of the vehicle tracking the sequence of intermediate goals by optimizing the motion of the vehicle subject to the second model. The driving constraints include mixed logical inequalities of temporal logic formulae specified by traffic rules to define an area where the temporal logic formulae are satisfied, while the tightened driving constraints shrink the area by the safety margin, which is a function of a difference between the second model and the first model approximating the second model.

Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

An automated speed control system includes a ranging-sensor, a camera, and a controller. The ranging-sensor detects a lead-speed of a lead-vehicle traveling ahead of a host-vehicle. The camera detects an object in a field-of-view. The controller is in communication with the ranging-sensor and the camera. The controller is operable to control the host-vehicle. The controller determines a change in the lead-speed based on the ranging-sensor. The controller reduces a host-speed of the host-vehicle when the lead-speed is decreasing, no object is detected by the camera, and while a portion of the field-of-view is obscured by the lead-vehicle.

This disclosure relates to a system and method for transitioning vehicle control between autonomous operation and manual operation. The system includes sensors configured to generate output signals conveying information related to the vehicle and its operation. During autonomous vehicle operation, the system gauges the level of responsiveness of a vehicle operator through challenges and corresponding responses. The system determines when to present a challenge to the vehicle operator based on internal and external factors. If necessary, the system will transition from an autonomous operation mode to a manual operation mode.

Example embodiments relate to techniques for three dimensional (3D) object detection and localization. A computing system may cause a radar unit to transmit radar signals and receive radar reflections relative to an environment of a vehicle. Based on the radar reflections, the computing system may determine a heading and a range for a nearby object. The computing system may also receive an image depicting a portion of the environment that includes the object from a vehicle camera and remove peripheral areas of the image to generate an image patch that focuses upon the object based on the heading and the range for the object. The image patch and the heading and the range for the object can be provided as inputs into a neural network that provides output parameters corresponding to the object, which can be used to control the vehicle.

Systems, methods, and apparatuses for improving predictive cruise control and predictive engine off coasting for a vehicle are provided. An apparatus includes one or more processing circuits having one or more memory devices coupled to one or more processors, the one or more memory devices configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to: receive look ahead information and store the look ahead information in the one or more memory devices; receive vehicle information regarding operation of a vehicle including an engine; determine a coasting opportunity for the vehicle based on the look ahead information and the vehicle information; modulate a cruise control set speed based on the determined coasting opportunity; and turn the engine off during the determined coasting opportunity for the vehicle based on modulation of the cruise control set speed.

Embodiments of the present disclosure disclose forward collision control methods and apparatuses, electronic devices, programs, and media, where the forward collision control method includes: detecting a forward suspected collision object on a road where a current traveling object is located on the basis of a neural network; predicting the collision time between the current traveling object and the suspected collision object; and performing forward collision control on the current traveling object according to the collision time, where the forward collision control includes forward collision warning and/or driving control.