Vehicular Micro Clouds for Predictive Road Conflict Coordination
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Solution Overview
Problem
Drivers exhibit selfish behavior that leads to negative impacts on others, causing conflicts in roadway environments, which existing vehicle control systems fail to address effectively.
Innovation Solution
A management system forms vehicular micro clouds to predict and obviate future conflicts by coordinating vehicles and infrastructure devices through altruistic action plans, using sensor data and V2X messages to synchronize driving maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If drivers act selfishly to maximize their own interests, then individual driving efficiency is improved, but road safety and overall traffic efficiency deteriorate due to conflicts between drivers
Solution Approach 1:
The patent introduces a mediator system that receives V2X messages from multiple vehicles, predicts potential conflicts using sensor data and machine learning models, and generates altruistic action plans to resolve conflicts before they occur. This intermediary system enables selfish drivers to achieve their individual goals while maintaining overall road safety through coordinated intervention.
Solution Approach 2:
The system performs preliminary conflict prediction and resolution by analyzing V2X messages and sensor data to identify potential conflicts before they materialize. By generating and implementing altruistic action plans in advance, the system prevents conflicts from occurring, allowing drivers to maintain their selfish driving patterns without actually causing safety issues.
2Device complexity
If existing vehicle control systems operate independently without coordination, then system complexity is reduced, but ability to prevent future conflicts deteriorates
Solution Approach 1:
The patent segments the conflict prevention system into independent vehicular micro clouds, where each cloud processes V2X messages and sensor data locally to predict conflicts among its member vehicles. This segmentation allows distributed conflict prediction without requiring a centralized complex system, maintaining相对较低的系统复杂度 while improving conflict prevention capability through localized coordination.
Solution Approach 2:
The system merges multiple data sources including V2X messages, sensor data from various vehicles, and machine learning models into a unified conflict prediction and resolution framework. By combining these elements into integrated vehicular micro clouds, the system achieves enhanced conflict prevention capability while managing complexity through modular architecture.
Data Source
AI summary
The disclosure includes embodiments for providing altruistic mobility by one or more vehicular micro clouds. The method includes predicting, by a processor, based on sensor data describing a roadway environment that a future conflict of interest between a first set of vehicles and a second set of vehicles will occur in the roadway environment that includes the connected roadway infrastructure device. The method includes forming a first vehicular micro cloud including the first set of vehicles and the connected roadway infrastructure device. The method includes forming a second vehicular micro cloud including the second set of vehicles. The method includes determining steps included in an altruistic action plan that is operable to obviate the future conflict of interest. The method includes instructing the first set of vehicles and the connected roadway infrastructure device to execute the steps of the altruistic action plan to obviate the conflict of interest.