Abstract: An autonomous vehicle (AV) is described herein. The AV is configured to identify an occluded region where a portion of a field of view of a sensor is occluded by an object. The AV is further configured to hypothesize that an object exists in the occluded region and is moving in the occluded region. The AV is still further configured to perform a driving maneuver based upon the hypothesized object existing in the occluded region.

Abstract: Approaches for top speed dependent operational parameter configuration are disclosed. An operational parameter to be used by an autonomous vehicle is received. Operational modes and corresponding operational regions are determined based on the received operational parameter. A first set of autonomous vehicle parameters are determined and set based on the received operational parameter. A second set of autonomous vehicle parameters are determined and set based on the first set of autonomous vehicle parameters.

Abstract: Systems and techniques are provided for determining a directionality of temporary traffic lanes. An example method can include detecting, based on sensor data from sensors of a vehicle, a temporary traffic lane on a road configured for use by traffic to navigate the road in lieu of a pre-existing traffic lane on the road, wherein a boundary of the temporary traffic lane is defined by objects on the road; detecting, based on the sensor data, cues indicating a directionality of the temporary traffic lane based on a first indication of a direction of travel of a vehicle traveling through the temporary traffic lane or an adjacent temporary traffic lane, a second indication of directionality provided by a human traffic controller in the road, and/or a third indication of directionality predicted based on objects on the road; and detecting the directionality of the temporary traffic lane based on the cues.

Abstract: The present disclosure generally relates systems and techniques for classification of signs and gestures pertaining to traffic and, more specifically, to autonomous vehicle based classification of signs and gestures of humans controlling traffic (HCTs). In some aspects, the present disclosure provides a process for identifying, using one or more sensors of an autonomous vehicle (AV), a human controlling traffic (HCT) and recognizing a set of instructions from the HCT, wherein the set of instructions comprises a set of sensory data. In some aspects, the process can further include operations for modifying a trajectory of the AV based on the set of instructions received from the HCT and based on a determination on whether the set of instructions are intended for the AV.

Abstract: Systems and techniques are provided for detecting construction zones by an autonomous vehicle. An example method includes detecting, by an autonomous vehicle, a first construction object and a second construction object; determining an association between the first construction object and the second construction object, wherein the association is based on at least one distance between the first construction object and the second construction object; identifying, based on the association, at least one temporary traffic restriction corresponding to the first construction object and the second construction object; and configuring a route of the autonomous vehicle based on the at least one temporary traffic restriction.

Abstract: Various technologies described herein pertain to controlling an autonomous vehicle to provide indicators to distinguish the autonomous vehicle from other autonomous vehicles in a fleet. The autonomous vehicle includes a vehicle propulsion system, a braking system, a notification system, and a computing system. The notification system outputs an indicator that is perceivable external to the autonomous vehicle. The computing system receives data specifying an identity of a passenger to be picked up by the autonomous vehicle. Moreover, the computing system controls at least one of the vehicle propulsion system or the braking system to stop the autonomous vehicle for passenger pickup. Further, the computing system controls the notification system to output the indicator; a characteristic of the indicator outputted by the notification system is controlled based on the identity of the passenger to be picked up and whether the autonomous vehicle is stopped for passenger pickup.

Abstract: An autonomous vehicle is described herein. The autonomous vehicle comprises a first sensor and a second sensor having limited fields of view, an articulation system, and a computing system. The computing system determines a first region and a second region external to the autonomous vehicle based on a sensor prioritization scheme comprising a ranking of regions surrounding the autonomous vehicle. The computing system then causes the articulation system to orient the first sensor towards the first region and the second region towards the second region. Responsive to receiving a sensor signal from the first sensor indicating that an object has entered a field of view of the first sensor, the computing system determines a third region having a higher ranking than the second region within the sensor prioritization scheme. The computing system then causes the articulation system to orient the second sensor towards the third region.

Abstract: Approaches for top speed dependent operational parameter configuration are disclosed. An operational parameter to be used by an autonomous vehicle is received. Operational modes and corresponding operational regions are determined based on the received operational parameter. A first set of autonomous vehicle parameters are determined and set based on the received operational parameter. A second set of autonomous vehicle parameters are determined and set based on the first set of autonomous vehicle parameters.

Abstract: An autonomous vehicle (AV) is described herein. The AV is configured to identify an occluded region where a portion of a field of view of a sensor is occluded by an object. The AV is further configured to hypothesize that an object exists in the occluded region and is moving in the occluded region. The AV is still further configured to perform a driving maneuver based upon the hypothesized object existing in the occluded region.

Abstract: An autonomous vehicle (AV) is described herein. The AV is configured to identify an occluded region where a portion of a field of view of a sensor is occluded by an object. The AV is further configured to hypothesize that an object exists in the occluded region and is moving in the occluded region. The AV is still further configured to perform a driving maneuver based upon the hypothesized object existing in the occluded region.

Abstract: Various technologies described herein pertain to controlling an autonomous vehicle to provide indicators to distinguish the autonomous vehicle from other autonomous vehicles in a fleet. The autonomous vehicle includes a vehicle propulsion system, a braking system, a notification system, and a computing system. The notification system outputs an indicator that is perceivable external to the autonomous vehicle. The computing system receives data specifying an identity of a passenger to be picked up by the autonomous vehicle. Moreover, the computing system controls at least one of the vehicle propulsion system or the braking system to stop the autonomous vehicle for passenger pickup. Further, the computing system controls the notification system to output the indicator; a characteristic of the indicator outputted by the notification system is controlled based on the identity of the passenger to be picked up and whether the autonomous vehicle is stopped for passenger pickup.

Abstract: Various technologies described herein pertain to controlling an autonomous vehicle to provide indicators to distinguish the autonomous vehicle from other autonomous vehicles in a fleet. The autonomous vehicle includes a vehicle propulsion system, a braking system, a notification system, and a computing system. The notification system outputs an indicator that is perceivable external to the autonomous vehicle. The computing system receives data specifying an identity of a passenger to be picked up by the autonomous vehicle. Moreover, the computing system controls at least one of the vehicle propulsion system or the braking system to stop the autonomous vehicle for passenger pickup. Further, the computing system controls the notification system to output the indicator; a characteristic of the indicator outputted by the notification system is controlled based on the identity of the passenger to be picked up and whether the autonomous vehicle is stopped for passenger pickup.

Abstract: An autonomous vehicle (AV) is described herein. The AV is configured to identify an occluded region where a portion of a field of view of a sensor is occluded by an object. The AV is further configured to hypothesize that an object exists in the occluded region and is moving in the occluded region. The AV is still further configured to perform a driving maneuver based upon the hypothesized object existing in the occluded region.

Abstract: An autonomous vehicle is described herein. The autonomous vehicle comprises a first sensor and a second sensor having limited fields of view, an articulation system, and a computing system. The computing system determines a first region and a second region external to the autonomous vehicle based on a sensor prioritization scheme comprising a ranking of regions surrounding the autonomous vehicle. The computing system then causes the articulation system to orient the first sensor towards the first region and the second region towards the second region. Responsive to receiving a sensor signal from the first sensor indicating that an object has entered a field of view of the first sensor, the computing system determines a third region having a higher ranking than the second region within the sensor prioritization scheme. The computing system then causes the articulation system to orient the second sensor towards the third region.

Abstract: An autonomous vehicle (AV) is described herein. The AV is configured to identify an occluded region where a portion of a field of view of a sensor is occluded by an object. The AV is further configured to hypothesize that an object exists in the occluded region and is moving in the occluded region. The AV is still further configured to perform a driving maneuver based upon the hypothesized object existing in the occluded region.

Abstract: An autonomous vehicle (AV) is described herein. The AV is configured to identify an occluded region where a portion of a field of view of a sensor is occluded by an object. The AV is further configured to hypothesize that an object exists in the occluded region and is moving in the occluded region. The AV is still further configured to perform a driving maneuver based upon the hypothesized object existing in the occluded region.

Abstract: An autonomous vehicle (AV) is described herein. The AV is configured to identify an occluded region where a portion of a field of view of a sensor is occluded by an object. The AV is further configured to hypothesize that an object exists in the occluded region and is moving in the occluded region. The AV is still further configured to perform a driving maneuver based upon the hypothesized object existing in the occluded region.

Abstract: An autonomous vehicle is described herein. The autonomous vehicle comprises a first sensor and a second sensor having limited fields of view, an articulation system, and a computing system. The computing system determines a first region and a second region external to the autonomous vehicle based on a sensor prioritization scheme comprising a ranking of regions surrounding the autonomous vehicle. The computing system then causes the articulation system to orient the first sensor towards the first region and the second region towards the second region. Responsive to receiving a sensor signal from the first sensor indicating that an object has entered a field of view of the first sensor, the computing system determines a third region having a higher ranking than the second region within the sensor prioritization scheme. The computing system then causes the articulation system to orient the second sensor towards the third region.

Abstract: Various technologies described herein pertain to controlling an autonomous vehicle to provide indicators that signal a driving intent of the autonomous vehicle. The autonomous vehicle includes a plurality of sensor systems that generate a plurality of sensor signals, a notification system, and a computing system. The computing system determines that the autonomous vehicle is to execute a maneuver that will cause the autonomous vehicle to traverse a portion of a driving environment of the autonomous vehicle. The computing system predicts that a person in the driving environment is to traverse the portion of the driving environment based upon the plurality of sensor signals. The computing system then controls the notification system to output a first indicator indicating that the autonomous vehicle plans to yield to the person or a second indicator indicating that the autonomous vehicle plans to execute the maneuver prior to the person traversing the portion of the driving environment.

Abstract: Various technologies described herein pertain to controlling an autonomous vehicle to provide indicators to distinguish the autonomous vehicle from other autonomous vehicles in a fleet. The autonomous vehicle includes a vehicle propulsion system, a braking system, a notification system, and a computing system. The notification system outputs an indicator that is perceivable external to the autonomous vehicle. The computing system receives data specifying an identity of a passenger to be picked up by the autonomous vehicle. Moreover, the computing system controls at least one of the vehicle propulsion system or the braking system to stop the autonomous vehicle for passenger pickup. Further, the computing system controls the notification system to output the indicator; a characteristic of the indicator outputted by the notification system is controlled based on the identity of the passenger to be picked up and whether the autonomous vehicle is stopped for passenger pickup.