Gm Cruise Holdings LLC

Samuel Harrison Glidden

Michael Frank Schmidt

Chase Brian Kaufman

Erik Birk Nielsen

Kenneth Ramon Ferguson

Maximilian Gerrit Euchenhofer

Jeffrey Brandon

Kyle Vogt

Sriram Salem Kannan

Jason Lee

Rajat Basu

Darren Hau

Systems and techniques are described for improving inspections of autonomous vehicles by utilizing a robotic arm with a modular hub that is configured to receive a plurality of peripherals for inspecting the autonomous vehicle. An example system can use a controller; a robotic arm; and a modular hub coupled to an end of the robotic arm to inspect an autonomous vehicle. The modular hub can include a plurality of ports for receiving a plurality of peripherals. Each port of the plurality of ports can be addressable, and each peripheral can be individually identified and controlled by the controller. In some cases, the system can include multiple modular hubs, with each modular hub configured to receive one or more peripherals for inspecting autonomous vehicles.

Multi-function robotic arm with modular hub for automated inspection and maintenance of autonomous vehicles

Systems and methods for dynamically suppressing noise at electric vehicle charging sites. In particular, systems and methods are provided for measuring the ambient noise at a charging site and adjusting electric vehicle chargers to reduce noise pollution. In some examples, electric vehicle charger cooling fans potentially generate a high level of noise, and the power output of a charger can be decreased to decrease the heat generated by the chargers, thereby reducing the need for fans. In various examples, reduction of noise pollution can be especially important in specified geographies (e.g., residential neighborhoods) and/or during selected timeframes (e.g., overnight). In various examples, the system interfaces with a central computer service (e.g., a dispatch service) to intelligently route autonomous vehicles to charging sites based on noise levels at various available charging sites.

System and method to dynamically suppress noise at electric vehicle charging sites

Systems and methods are provided for automated detection and disinfection of microbes in autonomous vehicles, to prevent possible transmission of diseases or illness to subsequent users. Automated detection and disinfection of a vehicle includes autonomously scanning various parts of the autonomous vehicle for microbes, selecting a disinfectant based on detected microbes, and autonomously disinfecting at least a portion of the autonomous vehicle.

System and method for automated detection and disinfection of a fleet of autonomous vehicles

The present disclosure provides a method comprising receiving a rideshare request from a user, the rideshare request including a destination; transporting the passenger to the destination using an autonomous vehicle (AV) having a plurality of windows comprising electrically switchable smart glass; during the transporting, monitoring a metric related to arrival of the AV at the destination; and untinting the windows when the monitored metric has a prescribed relationship to a threshold value.

Adjustable automatic window tinting for autonomous vehicles

Described herein is a system and method for detecting malodor within a cabin of an autonomous vehicle, wherein initiation of a remediation system and/or dispatch of the autonomous vehicle to a service hub for mitigating the malodor is based upon sensor signals that monitor the cabin of the autonomous vehicle. The remediation system can include devices such as an HVAC system or a window, which are operated to reduce the concentration of airborne molecules in the cabin of the autonomous vehicle when the concentration of airborne molecules exceeds an air quality threshold. A dispatch protocol may be initiated to dispatch the autonomous vehicle to a service hub when the malodor is associated with certain predefined incidents or when remediation fails to reduce the concentration of airborne molecules below the air quality threshold.

System and method for malodor detection and remediation

Predictive maintenance and diagnostics for an electronic module of an autonomous vehicle using modular condition monitoring is described herein. A computing system receives a signal from a data logger which monitors a condition of the electronic module of the autonomous vehicle, wherein the signal is indicative of damage accumulation information thereof. The computing system identifies a type of the electronic module and a damage accumulation threshold for the type of the electronic module to generate a predicted maintenance schedule for the electronic module of the autonomous vehicle. The damage accumulation information can be stored in a data store to define the damage accumulation threshold for the type of the electronic module.

Predictive maintenance and diagnostics using modular condition monitoring

Described herein is a server computing system that controls an autonomous vehicle to perform an operation to at least one of measure or isolate an effect of a variable on an actual power consumption by the autonomous vehicle. Data indicative of the actual power consumption, which is generated based on the operation, and data indicative of a projected power consumption, which is accumulated based on prior execution of the operation by a same or different autonomous vehicle, is received by the server computing system to determine whether an energy efficiency of the autonomous vehicle is degraded. The operation may be performed to identify a degraded vehicle system or component of the autonomous vehicle or to identify an autonomous vehicle in a fleet of autonomous vehicles for which further analysis is desirable. An output is generated by the server computing system that is indicative of the energy efficiency prognostics.

Growing community of inventors

Phoenix, AZ, United States of America

Samuel Harrison Glidden