Abstract: Systems and methods can be used for triggering traffic light sensors. A vehicle can detect a condition indicative of a failure of a traffic light to transition (e.g., due to a failure to activate a traffic light sensor) and take action in response. In some examples, the condition can be detected based on the state of the traffic light facing the vehicle and/or the state of one or more traffic lights controlling traffic perpendicular to the vehicle. In some examples, the condition can be detected based on a duration of a state of the traffic lights. In response to detecting the condition, the vehicle can take action. In some examples, the autonomous driving system of the vehicle can automatically adjust the vehicle's position to trigger the sensor. In some examples, the vehicle can notify the driver of the condition. In some examples, the autonomous driving system of the vehicle can reroute the vehicle.

Abstract: The disclosure includes implementations for executing one or more computations for a vehicle. Some implementations of a method for a vehicle may include identifying one or more computations as being un-executable by any processor-based computing device of the vehicle. The method may include generating a query including query data describing the one or more computations to be executed for the vehicle. The method may include providing the query to a network. The method may include receiving a response from the network. The response may include solution data describing a result of executing the one or more computations. The response may be provided to the network by a processor-based computing device included in a hierarchy of processor-based computing devices that have greater computational ability than any processor-based computing devices of the vehicle.

Abstract: Features of a vehicle navigation system are discussed in this disclosure. In particular, systems and methods for identifying glare-prone areas and establishing a route that avoids one or more of the identified glare-prone areas that are determined to be likely to degrade visibility of an environment outside of the vehicle. In some embodiments, the navigation system can be configured to calculate the likely duration of a trip and then based on sun angle data identify locations where glare is likely to be problematic. In some embodiments, the navigation system can also be configured to choose routes that avoid bright sources of light that could adversely affect visual acuity at night.

Abstract: The disclosure includes implementations for executing one or more computations for a vehicle. Some implementations of a method for a vehicle may include identifying one or more computations as being un-executable by any processor-based computing device of the vehicle. The method may include generating a query including query data describing the one or more computations to be executed for the vehicle. The method may include providing the query to a network. The method may include receiving a response from the network. The response may include solution data describing a result of executing the one or more computations. The response may be provided to the network by a processor-based computing device included in a hierarchy of processor-based computing devices that have greater computational ability than any processor-based computing devices of the vehicle.

Abstract: This disclosure relates to a method of safely and automatically navigating in the presence of emergency vehicles. A first vehicle may receive, via communication hardware, a message indicating presence of the emergency vehicle. Such a message may originate from the emergency vehicle itself and/or from infrastructure such as a smart traffic light that can sense the presence of the emergency vehicle. The first vehicle may then determine the relative location of the emergency vehicle and automatically respond appropriately by determining a safe trajectory and navigating according to that trajectory until the emergency vehicle is out of range. In some examples, the first vehicle may detect the presence of an emergency vehicle using on-board sensors such as distance measuring sensors, depth sensors, and cameras, in addition to receiving a message via communication hardware.

Abstract: The disclosure includes a method that includes assigning a classification to a travel route followed by a first client device based on data associated with when the first client device followed the travel route. The method may further include recommending the travel route to a second client device based on a request from the second client device for a desired travel route with the classification.

Abstract: The disclosure includes a system and method for providing a heads-up display in a vehicle for alerting users to roadway objects. The system includes a processor and a memory storing instructions that, when executed, cause the system to: monitor, with the one or more processors, for a roadway object; detect, with the one or more processors, the roadway object; generate graphical data configured to emphasize the roadway object on a heads-up display; determine whether a user sees the roadway object; responsive to the user failing to see the roadway object, determine whether the roadway object is critical; and responsive to the roadway object being critical, enhance a graphic output on the heads-up display to get the user's attention.

Abstract: The disclosure includes a method that includes assigning a classification to a travel route followed by a first client device based on data associated with when the first client device followed the travel route. The method may further include recommending the travel route to a second client device based on a request from the second client device for a desired travel route with the classification.

Abstract: The disclosure includes a system and method for providing a heads-up display in a vehicle for alerting users to roadway objects. The system includes a processor and a memory storing instructions that, when executed, cause the system to: monitor, with the one or more processors, for a roadway object; detect, with the one or more processors, the roadway object; generate graphical data configured to emphasize the roadway object on a heads-up display; determine whether a user sees the roadway object; responsive to the user failing to see the roadway object, determine whether the roadway object is critical; and responsive to the roadway object being critical, enhance a graphic output on the heads-up display to get the user's attention.

Abstract: The disclosure includes a method that includes determining a location that corresponds to a problematic travel condition based on data associated with when a first client device is at the location. The method may further include notifying, a second client device with a possible travel route that includes the location, that the location includes the problematic travel condition.

Abstract: The disclosure describes novel technology for inferring scenes from images. In one example, the technology includes a system that can determine partition regions from one or more factors that are independent of the image data, for an image depicting a scene; receive image data including pixels forming the image; classify pixels of the image into one or more pixel types based on one or more pixel-level features; determine, for each partition region, a set of pixel characteristic data describing a portion of the image included in the partition region based on the one or more pixel types of pixels in the partition region; and classify a scene of the image based on the set of pixel characteristic data of each of the partition regions.

Abstract: The disclosure describes novel technology for inferring scenes from images. In one example, the technology includes a system that can determine partition regions from one or more factors that are independent of the image data, for an image depicting a scene; receive image data including pixels forming the image; classify pixels of the image into one or more pixel types based on one or more pixel-level features; determine, for each partition region, a set of pixel characteristic data describing a portion of the image included in the partition region based on the one or more pixel types of pixels in the partition region; and classify a scene of the image based on the set of pixel characteristic data of each of the partition regions.