Aspects of the disclosure provide for a method for identifying speed limit signs and controlling an autonomous vehicle in response to detected speed limit signs. The autonomous vehicle's computing devices identifies a speed limit sign in a vehicle's environment and a location and orientation corresponding to the speed limit sign. Then, the and orientation location of the speed limit sign is determined to not correspond to a pre-stored location and a pre-stored orientation of a speed limit sign that is pre-stored in map information. An effect zone of the speed limit sign is determined based on the location and orientation of the speed limit sign and characteristics of surrounding areas or other detected object before or after the speed limit sign. The autonomous vehicle's computing devices determines a response of the vehicle based on the determined effect zone, and controls the autonomous vehicle based on the determined response.

Aspects of the disclosure provide for a method for identifying speed limit signs and controlling an autonomous vehicle in response to detected speed limit signs. The autonomous vehicle's computing devices identifies a speed limit sign in a vehicle's environment and a location and orientation corresponding to the speed limit sign. Then, the and orientation location of the speed limit sign is determined to not correspond to a pre-stored location and a pre-stored orientation of a speed limit sign that is pre-stored in map information. An effect zone of the speed limit sign is determined based on the location and orientation of the speed limit sign and characteristics of surrounding areas or other detected object before or after the speed limit sign. The autonomous vehicle's computing devices determines a response of the vehicle based on the determined effect zone, and controls the autonomous vehicle based on the determined response.

Aspects of the subject disclosure may include, for example, determining, by a system comprising a processor, a driver profile according to a driver identity for a driver of a vehicle, selecting a driver-specific enforcement scenario for the vehicle according to the driver profile and traffic enforcement information that is associated with a vehicle location, and presenting an in-vehicle alert to convey the driver-specific enforcement scenario to the driver. Other embodiments are disclosed.

Aspects of the subject disclosure may include, for example, determining, by a system comprising a processor, a driver profile according to a driver identity for a driver of a vehicle, selecting a driver-specific enforcement scenario for the vehicle according to the driver profile and traffic enforcement information that is associated with a vehicle location, and presenting an in-vehicle alert to convey the driver-specific enforcement scenario to the driver. Other embodiments are disclosed.

A system for repositioning at least one battery of an electric-powered vehicle relative to a drive axle of the vehicle to increase the weight carried by the axle as the vehicle attains a predetermined speed.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Systems and methods for self-driving collision prevention are presented. The system comprises a self-driving vehicle safety system, having one or more sensors in communication with a control system. The control system is configured determine safety fields and instruct the sensors to scan a region corresponding to the safety fields. The control system determines exclusion regions, and omits the exclusion regions from the safety field. The safety system may also include capability reduction parameters that can be used to constrain the drive system of the vehicle, for example, by restricting turning radius and speed in accordance with the safety fields.

Systems and methods for self-driving collision prevention are presented. The system comprises a self-driving vehicle safety system, having one or more sensors in communication with a control system. The control system is configured determine safety fields and instruct the sensors to scan a region corresponding to the safety fields. The control system determines exclusion regions, and omits the exclusion regions from the safety field. The safety system may also include capability reduction parameters that can be used to constrain the drive system of the vehicle, for example, by restricting turning radius and speed in accordance with the safety fields.

A vehicle speed and/or slip of a vehicle is determined. At least first and second images of a traveling surface captured by an image sensor using an optical lens are received by a processor. The images are used to determine the distance travelled by one or more pixels in first and second directions. These distances, along with the sampling rate of the image sensor, determine pixel speed in the first and second directions. The pixel speeds in the first direction, the second direction, or both, may be used to calculate the vehicle speed, a side slip angle, or a longitudinal slip. A tire speed may also be similarly determined using a second image sensor, a second optical lens, and a second processor capturing images of the tire surface. These vehicle parameters may be used for testing or operating the vehicle, including modifying vehicle behavior during operation.