Abstract:
A vehicle configured to operate in an autonomous mode could determine a current state of the vehicle and the current state of the environment of the vehicle. The environment of the vehicle includes at least one other vehicle. A predicted behavior of the at least one other vehicle could be determined based on the current state of the vehicle and the current state of the environment of the vehicle. A confidence level could also be determined based on the predicted behavior, the current state of the vehicle, and the current state of the environment of the vehicle. In some embodiments, the confidence level may be related to the likelihood of the at least one other vehicle to perform the predicted behavior. The vehicle in the autonomous mode could be controlled based on the predicted behavior, the confidence level, and the current state of the vehicle and its environment.
Abstract:
A roadgraph may include a graph network of information such as roads, lanes, intersections, and the connections between these features. The roadgraph may also include one or more zones associated with particular rules. The zones may include locations where driving is typically challenging such as merges, construction zones, or other obstacles. In one example, the rules may require an autonomous vehicle to alert a driver that the vehicle is approaching a zone. The vehicle may thus require a driver to take control of steering, acceleration, deceleration, etc. In another example, the zones may be designated by a driver and may be broadcast to other nearby vehicles, for example using a radio link or other network such that other vehicles may be able to observer the same rule at the same location or at least notify the other vehicle's drivers that another driver felt the location was unsafe for autonomous driving.
Abstract:
Methods and systems are disclosed for cross-validating a second sensor with a first sensor. Cross-validating the second sensor may include obtaining sensor readings from the first sensor and comparing the sensor readings from the first sensor with sensor readings obtained from the second sensor. In particular, the comparison of the sensor readings may include comparing state information about a vehicle detected by the first sensor and the second sensor. In addition, comparing the sensor readings may include obtaining a first image from the first sensor, obtaining a second image from the second sensor, and then comparing various characteristics of the images. One characteristic that may be compared are object labels applied to the vehicle detected by the first and second sensor. The first and second sensors may be different types of sensors.
Abstract:
Systems and methods are provided for controlling a vehicle. A safe envelope driving pattern is determined to control the vehicle in an autonomous mode. User identification data and sensor data are received from one or more sensors associated with the vehicle. A driver-specific driving pattern is determined based on the received sensor data and the user identification data. Operation of the vehicle is controlled in the autonomous mode based on the identification of the user in the driver's seat, the safe envelope driving pattern, and the user-specific driving pattern.
Abstract:
Aspects of the disclosure relate generally to detecting discrete actions by traveling vehicles. The features described improve the safety, use, driver experience, and performance of autonomously controlled vehicles by performing a behavior analysis on mobile objects in the vicinity of an autonomous vehicle. Specifically, an autonomous vehicle is capable of detecting and tracking nearby vehicles and is able to determine when these nearby vehicles have performed actions of interest by comparing their tracked movements with map data.
Abstract:
Aspects of the disclosure relate generally to notifying a pedestrian of the intent of a self-driving vehicle. For example, the vehicle may include sensors which detect an object such as a pedestrian attempting or about to cross the roadway in front of the vehicle. The vehicle's computer may then determine the correct way to respond to the pedestrian. For example, the computer may determine that the vehicle should stop or slow down, yield, or stop if it is safe to do so. The vehicle may then provide a notification to the pedestrian of what the vehicle is going to or is currently doing. For example, the vehicle may include a physical signaling device, an electronic sign or lights, a speaker for providing audible notifications, etc.