In-Vehicle Wireless Connection Density Management
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Solution Overview
Problem
In vehicles, high spatial density of wireless connections between passenger devices and in-vehicle systems leads to signal interference, reducing the reliability and quality of wireless connections.
Innovation Solution
A connection management system using tokens to dynamically manage wireless connections by defining density zones and assessing the current landscape of connections, selectively granting or denying new connections based on existing connection tokens to prevent interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple passenger devices wirelessly connect with in-vehicle systems in high spatial density, then the quantity of wireless connections increases, but signal interference occurs and connection reliability deteriorates
Solution Approach 1:
The system divides the vehicle space into multiple density zones with different connection capacity thresholds. Each zone independently manages its connection density, allowing high connections in low-interference areas while limiting connections in high-interference areas. This spatial segmentation resolves the contradiction by enabling overall high connection quantity while maintaining reliability through localized density control.
Solution Approach 2:
Different regions of the vehicle are assigned different connection density characteristics. The system dynamically adjusts connection acceptance criteria based on local conditions in each density zone, permitting higher connection densities in zones with better signal characteristics while enforcing stricter limits in zones prone to interference. This local differentiation allows the system to maximize total connections while preserving connection reliability in critical areas.
2Adaptability or versatility
If the system allows more wireless connections to improve passenger experience, then connection density increases, but signal interference and connection quality deteriorate
Solution Approach 1:
The system dynamically adjusts connection density thresholds and zone boundaries in real-time based on current connection patterns and interference levels. As connections are added or removed, the system recalculates density zones and modifies acceptance criteria accordingly. This dynamic adaptation enables the system to maintain optimal balance between connectivity versatility and interference prevention throughout changing operational conditions.
Solution Approach 2:
The system continuously monitors connection quality metrics and interference levels across all density zones, using this feedback to adjust connection acceptance decisions. When interference exceeds thresholds in specific zones, the system automatically tightens connection criteria in those zones while maintaining permissive criteria in unaffected zones. This feedback mechanism ensures versatility is maximized without compromising connection quality through interference.
3Reliability
If the system implements density zone management to reduce interference, then connection reliability improves, but system complexity increases
Solution Approach 1:
The density zone management system operates autonomously, automatically detecting connection requests, calculating density zone memberships, evaluating interference risks, and making connection acceptance decisions without external intervention. The system self-adjusts zone boundaries and thresholds based on real-time conditions, eliminating the need for manual configuration or complex external control mechanisms. This self-service approach achieves high reliability while keeping operational complexity manageable.
Solution Approach 2:
The connection management system performs multiple functions through a unified density zone framework: it simultaneously monitors connection density, evaluates interference risk, makes acceptance decisions, and dynamically adjusts zone parameters. This multi-functional approach consolidates what could be separate complex subsystems into a single integrated mechanism, achieving high reliability without proportionally increasing overall system complexity.
Data Source
AI summary
Embodiments described herein relate to managing wireless connections within a spatially-dense setting like a passenger vehicle, thereby improving quality and reliability of individual wireless connections. An example method includes detecting a connection request from a passenger device requesting a wireless connection with a seatback device in a first in-vehicle location. The method includes defining a density zone that includes other in-vehicle locations surrounding the first in-vehicle location. The density zone localizes an area within which other wireless connections may be disruptive to the wireless connection. The method includes determining, via a token server that stores connection tokens that each describe an existing connection, a number of particular tokens that describe existing connections located within the density zone. The method includes selectively granting or denying the requested wireless connection by comparing the number of particular tokens with a maximum number of connections or a capacity for the density zone.