Waymo LLC

Waymo L Lc

William Grossman

Pierre-yves Droz

Pierre-Yves Droz

Vijaysai Patnaik

Peter Strohm

Benjamin Pitzer

Mingcheng Chen

Matthew Carroll

Troy Scott Storz

David James Smith

A sensor (e.g., an optical sensor) is disposed in an enclosure that separates it from an external environment. The enclosure includes an aperture comprising a transparent material. A laminate comprising a plurality of transparent films is coupled to the aperture such that the sensor has a field of view of the external environment through the transparent material of the aperture and the plurality of transparent films. The laminate includes an exposed transparent film that is exposed to the external environment and that is removable to expose an underlying film in the laminate when dirt, debris, or other obscuring material has collected on it. A laminate module that includes the laminate, a laminate sensor, and a peeling mechanism may be removably mounted on the aperture. The laminate sensor can sense the number of transparent films remaining in the laminate. The peeling mechanism can peel away individual transparent films in the laminate.

Laminate structures for maintaining clear apertures

The technology relates to autonomous vehicles for transporting cargo and/or people between locations. Distributed sensor arrangements may not be suitable for vehicles such as large trucks, busses or construction vehicles. Side view mirror assemblies are provided that include a sensor suite of different types of sensors, including LIDAR, radar, cameras, etc. Each side assembly is rigidly secured to the vehicle by a mounting element. The sensors within the assembly may be aligned or arranged relative to a common axis or physical point of the housing. This enables self-referenced calibration of all sensors in the housing. Vehicle-level calibration can also be performed between the sensors on the left and right sides of the vehicle. Each side view mirror assembly may include a conduit that provides one or more of power, data and cooling to the sensors in the housing.

Sensor integration for large autonomous vehicles

The technology relates to assisting large self-driving vehicles, such as cargo vehicles, as they maneuver towards and/or park at a destination facility. This may include a given vehicle transitioning between different autonomous driving modes. Such a vehicles may be permitted to drive in a fully autonomous mode on certain roadways for the majority of a trip, but may need to change to a partially autonomous mode on other roadways or when entering or leaving a destination facility such as a warehouse, depot or service center. Large vehicles such as cargo truck may have limited room to maneuver in and park at the destination, which may also prevent operation in a fully autonomous mode. Here, information from the destination facility and/or a remote assistance service can be employed to aid in real-time semi-autonomous maneuvering.

Method for performing a vehicle assist operation

The technology relates to enhancing the operation of autonomous vehicles. Extendible sensors are deployed based on detected or predicted conditions around a vehicle while operating in a self-driving mode. When not needed, the sensors are fully retracted into the vehicle to reduce drag and increase fuel economy. When the onboard system determines that there is a need for a deployable sensor, such as to enhance the field of view of the perception system, the sensor is extended in a predetermined manner. The deployment may depend on one or more operating conditions and/or particular driving scenarios. These and other sensors of the vehicle may be protected with a rugged housing, for instance to protect against damage from the elements. And in other situations, deployable foils may extend from the vehicle's chassis to increase drag and enhance braking. This may be helpful for large trucks in steep descent situations.

Efficient autonomous trucks

A method includes identifying route data including a threshold arrival time for a route for an autonomous vehicle (AV) and calculating, based on the route data and a fuel-efficient speed value for each segment of the route, an estimated arrival time. Responsive to the estimated arrival time not meeting the threshold arrival time, the method includes identifying at least a subset of segments that each represent a candidate for speed increase, computing, for each segment in the subset and based on the fuel economy data, a correlation metric that indicates a correlation between a change in fuel economy and a change in speed for a corresponding segment in the subset, and increasing, for at least one segment from the subset and based on a respective correlation metric, a fuel-efficient speed value of the corresponding segment from the subset to provide a speed profile reflecting the increased fuel-efficient speed value.

Fuel-economy optimization for autonomous driving systems

The technology relates to autonomous vehicles having hitched or towed trailers for transporting cargo and other items between locations. Aspects of the technology provide a smart hitch connection between the fifth-wheel of a tractor unit and the kingpin of a trailer. This avoids requiring a person to make physical pneumatic and electrical connections between the fifth-wheel and kingpin using external hoses and cables. Instead, the necessary connections are made internally, autonomously. For instance, the fifth-wheel may provide air pressure via one or more slots arranged on a connection surface, and the trailer is configured to receive the air pressure through one or more openings on a contact surface of the kingpin. An electrical connection section of the fifth-wheel may also provide electrical signals and/or power to an electrical contact interface of the kingpin. Rotational information about relative alignment of the trailer to the tractor unit may also be provided.

Systems and methods for automatic air and electrical connections on autonomous cargo vehicles

Methods for transitioning between autonomous driving modes in large vehicles

The technology relates to cargo vehicles. National, regional and/or local regulations set requirements for operating cargo vehicles, including how to distribute and secure cargo, and how often the cargo should be inspected during a trip. However, such regulations have been focused on traditional human-driven vehicles. Aspects of the technology address various issues involved with securement and inspection of cargo before a trip, as well as monitoring during the trip so that corrective action may be taken as warranted. For instance, imagery and other sensor information may be used to enable proper securement of cargo before starting a trip. Onboard sensors along the vehicle monitor the cargo and securement devices/systems during the trip to identify issues as they arise. Such information is used by the onboard autonomous driving system (or a human driver) to take corrective action depending on the nature of the issue.

Cargo inspection, monitoring and securement in self-driving trucks

The technology relates to enhancing or extending the field of view of sensors for vehicles configured to operate in an autonomous driving mode. One or more mirrors are used to reflect or redirect beams emitted from onboard sensors that would otherwise be wasted, for instance due to obstruction by a portion of the vehicle or because they are emitted at high pitch angles to the side. The mirrors are also used to redirect incoming beams from the external environment toward one or more of the onboard sensors. Using mirrors for such redirection can reduce or eliminate blind spots around the vehicle. A calibration system may be employed to account for mirror movement due to vibration or wind drag. Each mirror may be a front surface mirror. The mirrors may be positioned on the vehicle body, on a faring, or extending from a sensor housing on the vehicle.

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East Palo Alto, CA, United States of America

William Grossman