Non-Autonomous Vehicle Integration Device for Autonomous Networks
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Solution Overview
Problem
The slow adoption of autonomous vehicles is hindered by the presence of non-autonomous vehicles on the roads and the high costs associated with implementing autonomous technology, necessitating an aftermarket solution to integrate non-autonomous vehicles into autonomous vehicle networks for improved safety and efficiency.
Innovation Solution
The method involves activating an autonomous vehicle network integration application on a mobile device within a primary vehicle, using on-board diagnostics data and environmental sensors to calculate influence vectors and ranges, allowing seamless communication and guidance between non-autonomous and autonomous vehicles, enabling continuous route navigation and hazard avoidance guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicle technology is implemented with sophisticated sensors and redundant systems, then safety and performance are improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent divides the autonomous vehicle system into multiple functional modules: sensor modules (RADAR, LIDAR, cameras), processing modules, communication modules, and control modules. Each module operates semi-independently, allowing the system to achieve high reliability through redundancy while managing complexity through modular architecture. The segmentation enables selective deployment of features based on cost and performance requirements.
Solution Approach 2:
The patent implements universal communication protocols and data formats that allow different sensor types and vehicle systems to interoperate through a common interface. The processing system can handle multiple sensor inputs and output types through standardized modules, reducing overall system complexity while maintaining safety through comprehensive monitoring.
2Reliability
If autonomous vehicle networks are established to improve safety and efficiency, then traffic management and hazard detection are enhanced, but the presence of non-autonomous vehicles limits network integration and adoption
Solution Approach 1:
The patent introduces communication intermediaries that enable non-autonomous vehicles to participate in the autonomous vehicle network. These intermediaries translate between traditional vehicle systems and autonomous network protocols, allowing legacy vehicles to receive safety alerts and share hazard information without requiring full autonomous capabilities. This mediator layer expands network adaptability while maintaining safety benefits.
Solution Approach 2:
The patent implements dynamic integration strategies where vehicles can adjust their level of network participation based on capabilities and environmental conditions. Non-autonomous vehicles can dynamically receive safety-critical information from the network while autonomous vehicles provide comprehensive data sharing. This dynamic approach optimizes safety benefits across mixed-technology traffic streams.
3Reliability
If sophisticated sensor suites and redundant systems are deployed in autonomous vehicles, then safety and monitoring capabilities are improved, but implementation costs become prohibitive for widespread adoption
Solution Approach 1:
The patent implements a tiered sensor deployment strategy where critical safety functions use redundant sophisticated sensors, while less critical functions use simpler or fewer sensors. For example, collision avoidance uses multiple redundant sensors, while monitoring functions may use fewer sensors. This partial application of redundancy achieves acceptable safety levels while reducing manufacturing costs for mass-market adoption.
Solution Approach 2:
The patent employs parameter optimization to reduce sensor specifications while maintaining safety performance. By carefully selecting sensor ranges, update rates, and detection thresholds, the system achieves required safety levels with less expensive sensors. For instance, using sensors with adequate but not excessive range and resolution reduces cost while maintaining safety margins through software-based compensation and fusion algorithms.
Data Source
AI summary
A method, apparatus, and system for integrating a non-autonomous vehicle into a transit environment populated with autonomous vehicles. An autonomous vehicle network integration apparatus is disclosed which collects data over a wireless network regarding a vehicle's route and surroundings, including nearby fully and partially autonomous vehicles. The apparatus is configured to analyze data and dynamically determine a range of influence, within which it communicates with vehicles to suggest driver actions and inform self-driving vehicle behavior.