Vehicle Localization Using Mobile Beacon Trilateration
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Solution Overview
Problem
Autonomous vehicles face significant challenges in maintaining accurate localization when traveling through areas with denied line-of-sight to fixed beacons or satellite signals, such as tunnels or dense urban environments, leading to loss of position accuracy.
Innovation Solution
The system employs a method where autonomous vehicles scan for and utilize nearby vehicles as mobile beacons, which broadcast their localization data, allowing the vehicle to estimate its position using trilateration or other algorithms, even in GNSS-denied areas, by selecting a subset of beacons based on their uncertainty values and geometric spread to achieve the most accurate position estimate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed terrestrial beacons and satellite-based navigation systems are used for localization, then position accuracy is improved, but the system fails in areas with denied line-of-sight such as tunnels and dense urban environments
Solution Approach 1:
The patent introduces mobile beacons (other vehicles) as intermediary elements that relay localization information. When fixed beacons and satellites are unavailable, the vehicle uses wireless communication to receive localization data from mobile beacons in its vicinity, enabling position estimation in GNSS-denied environments through this intermediary communication channel
Solution Approach 2:
The system creates virtual copies of beacon functionality by enabling ordinary vehicles to act as mobile beacons. Each vehicle broadcasts its estimated position and identity, effectively copying the beacon function from fixed infrastructure to mobile platforms, allowing any vehicle to serve as a localization reference for others
2Adaptability or versatility
If equations of motion are used for calculation of localization state in areas without external signals, then the vehicle can maintain navigation, but position accuracy is quickly lost
Solution Approach 1:
The system implements feedback by continuously receiving updated localization data from mobile beacons through wireless communication. Instead of relying solely on open-loop equations of motion that accumulate errors, the vehicle periodically receives corrected position information from nearby beacons, creating a feedback mechanism that resets and maintains positioning accuracy in GNSS-denied environments
3Measurement precision
If stationary beacons are deployed to provide localization data, then position accuracy in tunnels and dense urban areas is improved, but infrastructure costs and complexity increase
Solution Approach 1:
The system enables vehicles to serve themselves for localization by equipping them with beacon capabilities. Each vehicle broadcasts its own estimated position and identity, allowing other vehicles to use this information for localization without requiring any external stationary beacon infrastructure. The vehicles self-generate the localization references they need
Solution Approach 2:
The patent makes vehicles multi-functional by combining their navigation systems with beacon transmission capabilities. Vehicles not only navigate using localization data but also serve as localization sources for other vehicles, eliminating the need for dedicated stationary beacon infrastructure and reducing system complexity
Data Source
AI summary
Embodiments are disclosed for localization of vehicles using beacons. In an embodiment, a method comprises: determining, using at least one processor of a vehicle, that the vehicle has lost external signals (or is receiving degraded external signals) that are used for estimating a position of the vehicle; determining, using the at least one processor, a set of mobile beacons that are available to assist in estimating the position of the vehicle; receiving, using a communication device of the vehicle, broadcast signals from the set of mobile beacons, the broadcast signals including localization data for the set of mobile beacons; selecting, using the at least one processor, a subset of localization data from the set of mobile beacons for assisting in the position estimation of the vehicle; and estimating, using the at least one processor, the position of the vehicle using the subset of localization data.