An unmanned vehicle 20 is a vehicle that drives an electric motor by electric power generated in a power generator to travel by driving of the electric motor and includes a position sensor 240 that detects a position of the unmanned vehicle 20, a speed sensor 250 that detects a speed of the unmanned vehicle 20, and a vehicle control device 220 that controls the unmanned vehicle 20. The vehicle control device 220 calculates a work progression of a loading operation to the unmanned vehicle 20 by a loading machine 30 or a work progression of a preceding vehicle based on the position of the unmanned vehicle 20 detected by the position sensor 240 and the speed of the unmanned vehicle 20 detected by the speed sensor 250, calculates a period from a predicted time at which the calculated work progression exceeds a predetermined proportion until a predicted time at which the unmanned vehicle 20 starts acceleration as an acceleration preparation time, and drives the power generator to generate electricity during the calculated acceleration preparation time.

In an aspect, a self-balancing two-wheeled vehicle is provided, having a body, and first and second wheels rotatably coupled to the body. The second wheel has at least one lateral roller rotatable about an axis that is one of oblique and orthogonal to a rotation axis of the second wheel. At least one motor is coupled to the second wheel to control rotation of the second wheel and the at least one lateral roller. At least one sensor is coupled to the body to generate orientation data therefor. A control module is coupled to the at least one motor to control operation thereof at least partially based on the orientation data generated by the at least one sensor.

A computer-implemented method of refining a high definition (HD) map of a parking lot for autonomous vehicle parking (AVP) is disclosed. The method including: a vehicle navigating in the parking lot using the HD map; the vehicle using one or more sensors to scan for objects in the parking lot; the vehicle augmenting the HD map using a simultaneous localization & mapping SLAM method; adding objects detected by the one or more sensors to the HD map; and contributing towards improving a learning score of the HD map.

Various aspects of a system and method for driving assistance along a path are disclosed herein. In accordance with an embodiment, a unique identifier is received from a communication device at an electronic control unit (ECU) of a first vehicle. The unique identifier is received when the first vehicle has reached a first location along a first portion of the path. A communication channel is established between the first vehicle and the communication device based on the received unique identifier. Data associated with a second portion of the path is received by the ECU from the communication device based on the established communication channel. Alert information associated with the second portion of the path is generated by the ECU based on the received data.

Disclosed are a device and a method of controlling a remote parking assist function capable of determining in advance whether to enter, adjustment, or cancel the remote parking assist function using direct or indirect environment information. The device for controlling a remote parking assist function may collect direct and indirect environment information on a location where a vehicle is to be parked from a surrounding-environment information source, analyze the collected information, and cause activation of at least one of an entry control function, an adjustment control function, or a cancellation control function.

Systems and methods are disclosed for determining, and displaying, the regulatory compliance status of a motorized vehicle, a driver of a motorized vehicle, or a non-vehicle machine. An authorized agent, such as a law enforcement officer, can perform a remotely-initiated safe stop of a motorized vehicle to prevent a high-speed chase. A system management center can receive, store, and transmit regulatory compliance records indicating the regulatory compliance status of drivers, motorized vehicles, and non-vehicle machines. A motorized vehicle can detect, and report, a driver “tail-gating” the motorized vehicle. The regulatory compliance history of drivers, motorized vehicles, and non-vehicle machines can be queried by authorized users.

Systems and methods for situational behavior of an autonomous vehicle are disclosed. In one aspect, an autonomous vehicle includes at least one perception sensor configured to generate perception data indicative of at least one other vehicle on a roadway, a non-transitory computer readable medium, and a processor. The processor is configured to determine that the other vehicle is violating one or more rules of the roadway based on the perception data, tag the other vehicle as a non-compliant driver, and modify control of the autonomous vehicle in response to tagging the other vehicle as a non-compliant driver.

In one embodiment, a control command is generated by an autonomous controller of the ADV. Feedback is sensed that corresponds to the control command. A difference is determined between a) the control command, and b) the feedback corresponding to the control command. If the difference is meets a threshold, then a fault response is generated.

An automated method of controlling a speed of a vehicle includes identifying parameters of a driving instance of the vehicle; identifying a predetermined profile that is applicable to the driving instance based on the identified parameters; identifying a predetermined speed policy applicable to the driving instance based on the identified profile; and implementing the identified speed policy during the driving instance. The method may be repeated during the driving instance, whereby the speed policy that is implemented is automatically updated when one or more changes in the identified parameters cause a different predetermined speed policy to be identified. Parameter may include driver parameters (e.g., driver age and driver experience); vehicle parameters (e.g., vehicle age, mileage, and tire wear) tire maintenance information); behavior parameters (e.g., speed, acceleration, hard braking of the vehicle, following distance, swerving, and cornering); and circumstance parameters (e.g., time of day, road information, inclement weather, and traffic congestion).

Disclosed herein is a technique for generating and providing an indication to an autonomous vehicle regarding the confidence level for the accuracy or quality of the map data in which the indication is determined from observation data received from other vehicles.