Abstract: Example methods and systems for detecting weather conditions using vehicle onboard sensors are provided. An example method includes receiving laser data collected for an environment of a vehicle, and the laser data includes a plurality of laser data points. The method also includes associating, by a computing device, laser data points of the plurality of laser data points with one or more objects in the environment, and determining given laser data points of the plurality of laser data points that are unassociated with the one or more objects in the environment as being representative of an untracked object. The method also includes based on one or more untracked objects being determined, identifying by the computing device an indication of a weather condition of the environment.

Abstract: Methods, apparatuses, or computer program products provide for triggering component workflows within a multi-component system. An update to one or more component metadata records of a component metadata vector associated with a first component identifier may be received. The component metadata vector may include a plurality of records. Each record of the plurality of records may include a unique component metadata record identifier and a component metadata value. The component metadata vector associated with the first component identifier may be traversed after updating the one or more component metadata records. Based at least in part on detecting a component metadata condition associated with a component workflow trigger associated with the first component identifier, a first component workflow action of a first component workflow action series comprising a plurality of component workflow actions may be executed.

Abstract: An autonomous robotic vehicle includes a conveyance system, a securable compartment configured to autonomously lock and unlock, a customer identification reader, at least one processor, and a memory storing instructions which, when executed by the at least one processor, causes the autonomous robotic vehicle to, autonomously: travel to a destination location of a customer; capture, by the customer identification reader at the destination location, a customer identification object; determine that the captured customer identification object matches an identity of the customer; unlock the securable compartment based on the determination; capture, by the product identification reader, a product identifier; and accept a product to be returned by locking the securable compartment. The securable compartment contains a product identification reader.

Abstract: An autonomous robot vehicle includes a front side and an energy absorbing system. The front side includes a front bumper and a front face including a frame defining a cavity. The energy absorbing system includes an energy absorbing member mounted in the cavity of the frame, and an inflatable airbag. The energy absorbing member is configured to reduce impact on an object struck by the autonomous robot vehicle. The inflatable airbag is mounted on the front side of the autonomous robot vehicle such that when the inflatable airbag is deployed, the inflatable airbag is external to the autonomous robot vehicle.

Abstract: In accordance with aspects of the present disclosure, an autonomous robot vehicle is disclosed. In various embodiments, the autonomous robot vehicle includes a conveyance system, a securable compartment configured to autonomously lock and unlock where the securable compartment contains an item for delivery to a particular individual, a personal identification reader, at least one processor, and a memory storing instructions. The instructions, when executed by the processor(s), cause the autonomous robot vehicle to, autonomously, travel to a destination location of the particular individual, capture by the personal identification reader at the destination location a personal identification object, determine that the captured personal identification object matches an identity of the particular individual, and unlock the securable compartment based on the determination.

Abstract: Systems and methods are disclosed for providing transportation or delivery services using a fleet of mixed vehicles. A computer-implemented method of providing services using a fleet of mixed vehicles includes receiving at a server a request for a service, determining parameters for the service, selecting by the server a vehicle from a fleet of mixed vehicles to perform at least a portion of the service based on the determined parameters, and transmitting a message to the selected vehicle to perform the at least a portion of the service. The fleet of mixed vehicles includes at least two of: a semi-autonomous vehicle, a fully-autonomous vehicle, a vehicle remotely operated by a human, or a human driven vehicle.

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: According to one aspect, a method includes obtaining a request for a first vehicle from a customer, and dispatching the first vehicle to a first location identified in the request. Dispatching the first vehicle to the first location includes causing the first vehicle to drive in an autonomous mode. The method also includes determining when the first vehicle arrives at the first location, and providing the customer with access to enter the first vehicle.

Abstract: A system and method include scanning a light detection and ranging (LIDAR) device through a range of orientations corresponding to a scanning zone while emitting light pulses from the LIDAR device. The method also includes receiving returning light pulses corresponding to the light pulses emitted from the LIDAR device and determining initial point cloud data based on time delays between emitting the light pulses and receiving the corresponding returning light pulses and the orientations of the LIDAR device. The initial point cloud data has an initial angular resolution. The method includes identifying, based on the initial point cloud data, a reflective feature in the scanning zone and determining an enhancement region and an enhanced angular resolution for a subsequent scan to provide a higher spatial resolution in at least a portion of subsequent point cloud data from the subsequent scan corresponding to the reflective feature.

Abstract: Methods and devices for actively modifying a field of view of an autonomous vehicle in view of constraints are disclosed. In one embodiment, an example method is disclosed that includes causing a sensor in an autonomous vehicle to sense information about an environment in a first field of view, where a portion of the environment is obscured in the first field of view. The example method further includes determining a desired field of view in which the portion of the environment is not obscured and, based on the desired field of view and a set of constraints for the vehicle, determining a second field of view in which the portion of the environment is less obscured than in the first field of view. The example method further includes modifying a position of the vehicle, thereby causing the sensor to sense information in the second field of view.

Abstract: Example methods and systems for detecting weather conditions using vehicle onboard sensors are provided. An example method includes receiving laser data collected for an environment of a vehicle, and the laser data includes a plurality of laser data points. The method also includes associating, by a computing device, laser data points of the plurality of laser data points with one or more objects in the environment, and determining given laser data points of the plurality of laser data points that are unassociated with the one or more objects in the environment as being representative of an untracked object. The method also includes based on one or more untracked objects being determined, identifying by the computing device an indication of a weather condition of the environment.

Abstract: Provided herein are platforms for determining a non-navigational quality of at least one infrastructure by a plurality of autonomous or semi-autonomous land vehicles through infrastructure recognition and assessment.

Abstract: A system and method include scanning a light detection and ranging (LIDAR) device through a range of orientations corresponding to a scanning zone while emitting light pulses from the LIDAR device. The method also includes receiving returning light pulses corresponding to the light pulses emitted from the LIDAR device and determining initial point cloud data based on time delays between emitting the light pulses and receiving the corresponding returning light pulses and the orientations of the LIDAR device. The initial point cloud data has an initial angular resolution. The method includes identifying, based on the initial point cloud data, a reflective feature in the scanning zone and determining an enhancement region and an enhanced angular resolution for a subsequent scan to provide a higher spatial resolution in at least a portion of subsequent point cloud data from the subsequent scan corresponding to the reflective feature.

Abstract: Provided herein are platforms for determining a real-time human behavior analysis of an unmanned vehicle by a plurality of autonomous or semi-autonomous land vehicles through infrastructure recognition and assessment. The platforms determine a real-time parking status for a plurality of parking locations, a platform for detecting a traffic violation by a manned vehicle at a roadway location, and a platform for monitoring security of a physical location.

Abstract: Provided herein is an autonomous or semi-autonomous vehicle fleet comprising a plurality of electric autonomous vehicles for apportioned display of a media, operating autonomously and a fleet management module for coordination of the autonomous vehicle fleet. Each autonomous or semi-autonomous vehicle comprising a screen configured to display the media. Activation, deactivation, brightness modification, in combination with specific media selection enables more efficient media display.

Abstract: A system and method include scanning a light detection and ranging (LIDAR) device through a range of orientations corresponding to a scanning zone while emitting light pulses from the LIDAR device. The method also includes receiving returning light pulses corresponding to the light pulses emitted from the LIDAR device and determining initial point cloud data based on time delays between emitting the light pulses and receiving the corresponding returning light pulses and the orientations of the LIDAR device. The initial point cloud data has an initial angular resolution. The method includes identifying, based on the initial point cloud data, a reflective feature in the scanning zone and determining an enhancement region and an enhanced angular resolution for a subsequent scan to provide a higher spatial resolution in at least a portion of subsequent point cloud data from the subsequent scan corresponding to the reflective feature.

Abstract: A method and apparatus is provided for controlling the operation of an autonomous vehicle. According to one aspect, the autonomous vehicle may track the trajectories of other vehicles on a road. Based on the other vehicle's trajectories, the autonomous vehicle may generate a pool of combined trajectories. Subsequently, the autonomous vehicle may select one of the combined trajectories as a representative trajectory. The representative trajectory may be used to change at least one of the speed or direction of the autonomous vehicle.

Abstract: A delivery system includes a database configured to store information of a customer where the information includes a default payment method, a communication system configured to communicate with an autonomous vehicle and with a device of the customer, where the device includes a display screen having a button to summon an autonomous vehicle, at least one processor, and a memory storing instructions. The instructions, when executed by the at least one processor, cause the delivery system to receive an indication via the communication system that the button on the device of the customer has been clicked, and instruct the autonomous vehicle to travel to a location of the customer.

Abstract: Provided herein is an autonomous or semi-autonomous vehicle fleet comprising a plurality of electric autonomous vehicle for apportioned display of a media, operating autonomously and a fleet management module for coordination of the autonomous vehicle fleet. Each autonomous or semi-autonomous vehicle comprising a screen configured to display the media. Activation, deactivation, brightness modification, in combination with specific media selection enables more efficient media display.

Abstract: Methods and systems are disclosed for determining sensor degradation by actively controlling an autonomous vehicle. Determining sensor degradation may include obtaining sensor readings from a sensor of an autonomous vehicle, and determining baseline state information from the obtained sensor readings. A movement characteristic of the autonomous vehicle, such as speed or position, may then be changed. The sensor may then obtain additional sensor readings, and second state information may be determined from these additional sensor readings. Expected state information may be determined from the baseline state information and the change in the movement characteristic of the autonomous vehicle. A comparison of the expected state information and the second state information may then be performed. Based on this comparison, a determination may be made as to whether the sensor has degraded.