A system generates haptic feedback in an electric vehicle. The system comprises a frame, an energy storage device, and a wheel rotatably coupled to the frame. A motor receives power from the energy storage device and provides torque to the wheel. A controller determines a first operational state of the electric vehicle and transmits a first torque signal to the motor to control the motor to transmit first torque levels to the wheel to propel the electric vehicle. The controller determines a second operational state of the electric vehicle and transmits a second torque signal to the motor assembly. The motor assembly transmits second torque levels to the wheel to generate haptic feedback. The second torque signal is based on the second operational state of the electric vehicle and a torque profile stored in the memory, where the torque profile defines an irregular-shaped periodic waveform (e.g., a heartbeat rhythm).

A driving assistance apparatus is configured to perform an assistance control of assisting in driving a vehicle, when a first condition and a second condition are satisfied, in a situation in which a target is recognized. The driving assistance apparatus is provided with: a determinator configured to determine a state of the assistance control. The determinator is configured (i) to determine that the state of the assistance control is a standby state if a standby condition is satisfied, wherein the standby condition requires that the first condition is satisfied, but the second condition is not satisfied, in the situation in which the target is recognized, and (ii) to determine that the state of the assistance control is an interruption state if an interruption condition is satisfied, wherein the interruption condition requires that the first condition is no longer satisfied while the satisfaction of the standby condition is continued.

The disclosure relates to a method for generating a reference trajectory within a lane for a vehicle. The method comprises receiving at least one vehicle current state parameter describing a current state of the vehicle (S11). The current state of the vehicle comprises at least a current position of the vehicle. Furthermore, a destination parameter describing a destination to be reached by the vehicle (S12), and at least one route parameter describing a route for reaching the destination (S13) are received. Moreover, the method comprises estimating a power loss being caused when traveling from the current position of the vehicle to the destination (S14). The reference trajectory within the lane is determined such that it minimizes the power loss and leads to the destination (S15). Additionally, a method for operating a vehicle is presented. According to this method, a reference trajectory is generated in accordance with the above method (S21) and at least one control signal is provided for controlling a motion of the vehicle along the reference trajectory (S22). Furthermore, a data processing apparatus, a vehicle and a computer-readable medium are presented.

A vehicle control system includes a first electric motor that causes a vehicle to travel, a second electric motor that generates power by using an output of a power source and starts the power source, a power storage device that stores the power generated by the second electric motor and supplies the power to the first electric motor, a monitoring device that monitors a failure state of the vehicle, and a switch that switches the vehicle to travel from the first electric motor to the second electric motor. In a case of a predetermined driving state in which the monitoring device detects a failure of the first electric motor and a driving force is obtained from the second electric motor, the monitoring device controls the switch to switch the driving force for causing the vehicle to travel from the first electric motor to the second electric motor.

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.

An estimation apparatus of the disclosure includes a determiner that determines whether or not an attention target is visually recognizable from a driver of a vehicle based on information related to a visual field range of the driver; and an estimator that estimates a visual field abnormality of the driver based on a driving operation of the driver in a case where the determiner determines that the attention target is visually recognizable from the driver.

One or more embodiments include systems and methods for regulating control of a vehicle infotainment system. In one embodiment, a vehicle computing system includes a user interface which has one or more output components and one or more input components. Software executing in memory of the vehicle computing system may be programmed with rules to reduce driver distraction such as preventing inputs or outputs during vehicle operation. Inputs may be intercepted from the one or more input components of the user interface. Additionally or alternatively, outputs may be intercepted to the output components of the user interface. The intercepted inputs or intercepted outputs may be evaluated for one or more violations based on the rules. If the one or more violations are detected, the inputs or outputs may be prevented during vehicle operation.

A method is disclosed for analyzing historical accident information to adjust driving actions of an autonomous vehicle over a travel route in order to avoid accidents which have occurred over the travel route. Historical accident information for the travel route can be analyzed to, for example, determine accident types which occurred over the travel route and determine causes and/or probable causes of the accident types. In response to determining accident types and causes/probable causes of the accident types over the travel route, adjustments can be made to the driving actions planned for the autonomous vehicle over the travel route. In addition, in an embodiment, historical accident information can be used to analyze available travel routes and select a route which presents less risk of accident than others.

Path generation apparatus configured to generate target path of own vehicle traveling in own lane, includes: sensor configured to detect objects in surrounding area of own vehicle; and electronic control unit including processor and memory. Electronic control unit is configured to perform: recognizing adjacent vehicle traveling in adjacent lane adjacent to own lane from among detected objects; determining whether own lane is congested based on travel speed of own vehicle and determining whether adjacent lane is congested based on recognition result of adjacent lane; and generating target path of own vehicle. Generating target path includes generating target path on side away from adjacent lane with respect to that of case where own lane is determined to be congested and adjacent lane is determined to be congested, in case where own lane is determined to be congested and adjacent lane is determined not to be congested.

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.