A vehicle control apparatus controls movement of a vehicle in a lateral direction intersecting a direction in which the vehicle travels based on a movement trajectory of a preceding vehicle. The vehicle control apparatus includes a detection unit configured to detect a surrounding environment of the vehicle, and a preceding vehicle which travels ahead in the same lane in which the vehicle travels, a determination unit configured to determine whether or not the preceding vehicle straddles lanes or approaches within a set distance predetermined for the lanes based on lateral movement information of the preceding vehicle detected by the detection unit, and a control unit configured to control lateral movement of the vehicle based on a determination result of the determination unit and detection information of the detection unit.

A system includes a processor and a memory storing instructions executable by the processor to select a distance based on a determination of whether a lane adjacent a primary vehicle and a secondary vehicle in front of the primary vehicle is clear. The instructions include instructions to actuate a braking system of the primary vehicle when the primary vehicle is at the distance from the secondary vehicle.

A system for a vehicle includes a powertrain configured to propel the vehicle, and a controller configured to, during a first lap of the vehicle around a track, identify a portion of the track corresponding to a correlation of velocity, throttle position, and steering angle values indicative of a maximum power threshold, and, during a second lap, responsive to approaching the portion, limit power output by the powertrain causing temperature of the powertrain to fall and, upon entering the portion, increase power output to the maximum power threshold causing the temperature to rise, such that a difference in temperature between initiation of the limiting and exiting of the portion approaches zero.

In one embodiment, a method by a computing system of a vehicle includes determining an environment of the vehicle. The method includes generating, based on the environment, multiple proposed vehicle actions with associated operational data. The method includes determining a comfort level for each proposed vehicle action by processing the environment and operational data using a model for predicting comfort levels of vehicle actions. The model is trained using records of performed vehicle actions. The record for each performed vehicle action includes environment data, operational data, and a perceived passenger comfort level for the performed vehicle action. The method includes selecting a vehicle action from the proposed vehicle actions based on the determined comfort level. The method includes causing the vehicle to perform the selected vehicle action.

A database of high risk locations is formed and high risk causal factors for the high risk locations determined. Driver behavior is monitored at the sites in the database using data collection devices such as electronic logging devices or mobile phones to see if the drivers exhibit the same specific behaviors that are considered contributing factors to specific accident types at risk of occurrence at those sites. Warnings are provided to drivers approaching the specific sites to prompt behavioral changes which may further be monitored by the data collection devices.

A route risk mitigation system and method using real-time information to improve the safety of vehicles operating in semi-autonomous or autonomous modes. The method mitigates the risks associated with driving by assigning real-time risk values to road segments and then using those real-time risk values to select less risky travel routes, including less risky travel routes for vehicles engaged in autonomous driving over the travel routes. The route risk mitigation system may receive location information, real-time operation information, (and/or other information) and provide updated associated risk values. In an embodiment, separate risk values may be determined for vehicles engaged in autonomous driving over the road segment and vehicles engaged in manual driving over the road segment.

Systems and methods for characterizing a driving style of an autonomous vehicle are presented. A system may include one or more sensors configured to collect information concerning driving characteristics; a memory containing computer-readable instructions for evaluating the driving characteristics for a pattern(s) correlatable with a driving style of the autonomous vehicle and for characterizing aspects of driving style based on the one or more patterns; and a processor configured to evaluate the driving characteristics for the one or more patterns correlatable with the driving style, and characterize aspects of the driving style based on the pattern(s). Corresponding methods and non-transitory media are disclosed.

An automatic parking system is provided. The automatic parking system includes a camera processor that acquires images around a subject vehicle, converts the acquired images into external images and synthesizes the external images. A sensor processor measured spaced distances between the subject vehicle and surrounding vehicles. A parking space recognizing unit periodically receives the spaced distances and the external images and comparing the consecutive external images with the spaced distances using an image recognition technology to recognize parking areas. A controller calculates a moving path between a current position of the subject vehicle and an optimal parking area and operates the subject vehicle based on the moving path.

A map information system includes a map database including map information; and a driving assist level determination device. The map information is associated with an evaluation value indicating a certainty of the map information for each location in an absolute coordinate system. Information indicating that the intervention operation is performed is included in driving environment information indicating a driving environment of a vehicle. The driving assist level determination device is configured to acquire, based on the driving environment information, intervention operation information indicating an intervention operation location where the intervention operation is performed, acquire, based on the map information, the evaluation value for each point or section in a target range, and determine, based on the evaluation value and the intervention operation location, an allowable level for each point or section within the target range.

The invention relates to a method for the position determination of an object (6, 6a . . . 6d), which is conveyed on a conveying device (1a . . . 1c). In this process, a deviation (ΔP) between a position (P.sub.sig) of the object (6, 6a . . . 6d), which is calculated with the aid of rotation signals from the drives (M) for conveyor elements (2, 2.sub.M, 2.sub.L) of the conveying device (1a . . . 1c), and a position (P.sub.1 . . . P.sub.5) of a detection area (E.sub.1,E.sub.2) of a sensor (L.sub.1 . . . L.sub.5) fixedly installed on the conveying device (6, 6a . . . 6d) is determined and used for calculating a corrected position (P.sub.korr) of the object (6, 6a . . . 6d) during a movement of the object (6, 6a . . . 6d) away from this detection area (E.sub.1,E.sub.2). Furthermore, a conveying device (1a . . . 1c) for performing the presented method is indicated.