Abstract:
An autonomous vehicle (AV) tracking and updating system tracks locations of AVs traveling throughout a given region. Using a stored network resource map, the system identifies a number of network-limited areas in the given region, and determines when respective AVs will enter one of the network-limited areas. In response, the system transmits a set of configuration commands to a number of proximate AVs to establish a mesh network with the respective AVs.
Abstract:
An autonomous vehicle (AV) tracking and updating system tracks locations of AVs traveling throughout a given region. Using a stored network resource map, the system identifies a number of network-limited areas in the given region, and determines when respective AVs will enter one of the network-limited areas. In response, the system transmits a set of configuration commands to a number of proximate AVs to establish a mesh network with the respective AVs.
Abstract:
Systems and methods for determining autonomous vehicle user boarding times are provided. In one example embodiment, a computer implemented method includes obtaining location data associated with a user device associated with a user. The method includes determining an estimated time until the user starts boarding the autonomous vehicle based at least in part on the location data associated with the user device. The method includes obtaining data associated with the user. The method includes determining an estimated time of boarding duration for the user based at least in part on the data associated with the user. The method includes determining an estimated time until the user completes boarding of the autonomous vehicle based at least in part on the estimated time until the user starts boarding the autonomous vehicle and the estimated time of boarding duration for the user.
Abstract:
A backend system can store a network resource map that indicates network coverages areas for a plurality of base stations over a given region. The system can receive a pick-up request from a requesting user seeking transportation from a pick-up location to a destination, and instruct an automated vehicle (AV) to service the pick-up request. The system can further determine a plurality of possible routes from the pick-up location to the destination, and perform an optimization operation to determine an optimal route by utilizing the network resource map. The system can then transmit route data for the optimal route to the selected AV.
Abstract:
An automated vehicle (AV) can be managed by a backend system and include an acceleration, braking, and steering system, an AV control system to maneuver the AV through road traffic throughout a given region, a memory to store a network resource map indicating locations of base stations and available network types providing coverage from the base stations throughout the given region, a communications array to transmit and receive communications from the backend system, and a communications system. The communications system can utilize the network resource map to dynamically select optimal network types from proximate base stations to communicate data with the backend system, and dynamically configure the communications array to connect with the optimal network types to transmit and receive data with the backend system.
Abstract:
An autonomous vehicle (AV) can include a communication system to communicate with a backend system, a sensor system to collect sensor data representing an operational environment of the AV, and a control system that can processes the sensor data to (i) perform a localization operation to determine a location and an orientation of the AV within a given region, and (ii) autonomously operate the AV's acceleration, braking, and steering system throughout the given region. Based on the localization operation, the AV can implement a set of configuration commands to configure the communication system to transmit and receive data with the backend system using a number of specified network nodes.
Abstract:
A backend system for a fleet of autonomous vehicles (AVs) for a given region can store a spectrum heat map indicating network coverage strength for a plurality of network types sourced at base stations located throughout the given region. The backend system can dynamically receive network quality data from the plurality of AVs traveling throughout the given region, and dynamically update the spectrum heat map based on the received network quality data.
Abstract:
A communication configuration system for a fleet of autonomous vehicles (AVs) stores a network resource map for a given region that indicates locations of base stations for connecting the fleet of AVs with a backend system. The communication configuration system receives localization information from a respective AV of the fleet which indicates location and orientation of the respective AV. Using the network resource map, the system selects a proximate base station relative to the respective AV transmits array configuration commands to the respective AV to cause the respective AV to direct an on-board communications array to transmit and receive data with the proximate base station.
Abstract:
Systems and methods for determining autonomous vehicle user boarding times are provided. In one example embodiment, a computer implemented method includes obtaining location data associated with a user device associated with a user. The method includes determining an estimated time until the user starts boarding the autonomous vehicle based at least in part on the location data associated with the user device. The method includes obtaining data associated with the user. The method includes determining an estimated time of boarding duration for the user based at least in part on the data associated with the user. The method includes determining an estimated time until the user completes boarding of the autonomous vehicle based at least in part on the estimated time until the user starts boarding the autonomous vehicle and the estimated time of boarding duration for the user.
Abstract:
Systems and methods for controlling autonomous vehicles are provided. In one example embodiment, a computer implemented method includes obtaining data indicative of a location associated with a user to which an autonomous vehicle is to travel. The autonomous vehicle is to travel along a first vehicle route that leads to the location. The method includes obtaining traffic data associated with a geographic area that includes the location. The method includes determining an estimated traffic impact of the autonomous vehicle on the geographic area based at least in part on the traffic data. The method includes determining vehicle action(s) based at least in part on the estimated traffic impact and causing the autonomous vehicle to perform the vehicle action(s) that include at least one of stopping the autonomous vehicle at least partially in a travel way within a vicinity of the location or travelling along a second vehicle route.