Distributed Cooperative Localization for Connected Vehicles
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Solution Overview
Problem
Conventional cooperative localization systems in vehicles rely on centralized architectures that require powerful computational capabilities and seamless communication, which are inadequate for accurate localization in urban environments and future autonomous driving applications, especially where GPS accuracy is compromised.
Innovation Solution
A distributed cooperative localization system where sensor-rich vehicles communicate directly to share location estimates and confidence levels, allowing for decentralized optimization and leveraging the sensors of sensor-rich vehicles to assist both sensor-rich and legacy vehicles, without relying on central edge nodes or cloud servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized cooperative localization system is used, then coordination among vehicles is achieved, but computational burden and communication dependency increase
Solution Approach 1:
The patent divides the centralized localization system into multiple distributed sensor-rich vehicles, each independently performing localization computations for itself and assigned legacy vehicles. This segmentation eliminates the need for a single centralized entity, reducing system complexity and communication bottlenecks while maintaining coordination through peer-to-peer interactions.
Solution Approach 2:
The patent introduces a distributed coordination mechanism where sensor-rich vehicles act as intermediaries for legacy vehicles. Each sensor-rich vehicle that accepts an assignment to perform localization for a legacy vehicle serves as a local mediator, eliminating the need for centralized coordination while ensuring legacy vehicles receive accurate localization services.
2Measurement precision
If GPS is used for vehicle navigation, then cost-effective localization is achieved, but accuracy deteriorates in urban canyons
Solution Approach 1:
The patent combines GPS data with sensor data from multiple sensor-rich vehicles to create a fused localization estimate. By merging information from multiple sources (GPS receivers, sensors, and other vehicles' data), the system compensates for GPS signal blockage in urban canyons and achieves higher accuracy than GPS alone.
Solution Approach 2:
The patent implements a feedback mechanism where vehicles exchange location estimates and confidence levels, and each vehicle uses this feedback to refine its own localization. The distributed optimization algorithm iteratively adjusts location estimates based on feedback from neighboring vehicles, improving accuracy in environments where GPS is unreliable.
3Productivity
If sensor-rich vehicles perform distributed localization, then computational load is balanced, but communication requirements increase
Solution Approach 1:
The patent applies local quality by having each sensor-rich vehicle perform computations primarily for itself and its assigned legacy vehicles, rather than all vehicles contributing to all localizations. This localized computation approach balances the computational load across the network while reducing the amount of data that needs to be communicated, as each vehicle processes local sensor data and exchanges only necessary location estimates and confidence levels with neighbors.
Data Source
AI summary
Systems and methods for distributed cooperative localization in a connected vehicular platform are disclosed herein. At a first sensor-rich vehicle, one embodiment receives, from a second sensor-rich vehicle via direct vehicle-to-vehicle (V2V) communication, an estimated location of the first sensor-rich vehicle and an associated confidence level; estimates a location of the second sensor-rich vehicle based on first sensor data and assigns a confidence level to the estimated location; transmits to the second sensor-rich vehicle via direct V2V communication, the estimated location of the second sensor-rich vehicle and the assigned confidence level; accepts, based on communication between the first and second sensor-rich vehicles and predetermined acceptance criteria, an assignment to perform localization for a legacy vehicle; estimates a location of the legacy vehicle based on second sensor data; and transmits, to the legacy vehicle, the estimated location of the legacy vehicle.