Multi-Vehicle Safety Data Sharing for Light Mobility Groups
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Solution Overview
Problem
Light mobility vehicles face increased collision risks due to varying safety conditions based on user behavior and route choices, with existing systems failing to effectively leverage multi-source safety-related data for improved road user safety and visibility.
Innovation Solution
A safety system for light mobility vehicles that integrates sensors, processors, and connectivity modules to dynamically process and share safety-related data among vehicles in a group, adjusting data ingestion and transmission based on situational awareness and user context, including pedestrian mode or vehicle integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If safety systems collect and process data from multiple sensors and sources, then safety monitoring capability is improved, but device complexity increases
Solution Approach 1:
The patent segments the safety system into multiple independent functional modules: sensor modules (cameras, LIDAR, radar), data processing modules, communication modules, and control modules. Each module performs a specific function and can be independently configured or replaced, reducing overall system complexity while maintaining comprehensive safety monitoring capability through multi-source data integration.
Solution Approach 2:
The patent implements universal data processing algorithms that can handle multiple types of sensor data (visual, depth, radar) and multiple threat scenarios (pedestrians, vehicles, obstacles) using the same computational framework. This multi-functional approach allows the system to process diverse data sources through unified processing pipelines, reducing complexity compared to having separate processing systems for each sensor type.
2Speed
If the system processes and transmits safety data in real-time, then responsiveness to threats is improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic data processing cycles where sensors collect data continuously but processing occurs at optimized intervals based on threat level. During normal conditions, processing occurs at lower frequencies to conserve energy. When threats are detected or risk levels increase, the system transitions to higher-frequency processing modes, achieving real-time responsiveness only when necessary while minimizing overall energy consumption.
Solution Approach 2:
The system processes only the most critical safety data in real-time while using lower processing priorities for less urgent information. The patent implements a hierarchical processing approach where essential threat detection and navigation data receive full real-time processing resources, while secondary data such as environmental mapping or non-critical sensor inputs are processed at reduced rates or asynchronously, balancing responsiveness with energy efficiency.
3Reliability
If the system shares safety data among multiple vehicles in a group, then group safety is improved, but data transmission requirements increase
Solution Approach 1:
The patent extracts and transmits only the essential safety-critical data elements among group vehicles, filtering out redundant or non-essential information. The system identifies and transmits only key parameters such as threat locations, collision risks, and critical navigation data, while omitting extraneous sensor details or duplicate information already known to receiving vehicles. This extraction approach reduces data transmission volume while maintaining group safety through sharing of essential safety information.
4Productivity
If the system adjusts data ingestion based on situational awareness, then efficiency is improved, but measurement precision requirements increase
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors its own situational awareness accuracy and adjusts data ingestion rates accordingly. When measurement precision and confidence levels are high, the system reduces data ingestion to optimize efficiency. When uncertainty increases or situational awareness degrades, the system automatically increases data sampling rates and processing intensity to maintain safety, creating a self-regulating system that balances efficiency with precision requirements.
Data Source
AI summary
The present disclosure relates to safety devices and systems for light mobility vehicles. In one example, a light mobility vehicle safety system includes one or more sensors and a processor coupled to a light mobility vehicle. The processor may be configured to determine that the light mobility vehicle is part of a group of two or more light mobility vehicles; determine a position of the light mobility vehicle relative to one or more other light mobility vehicles in the group; determine one or more relevant sensors of the one or more sensors based on the position of the light mobility vehicle and positioning of the one or more sensors on the light mobility vehicle; receive first relevant safety-related data from the one or more relevant sensors; and transmit the first relevant safety-related data to one or more other light mobility vehicles in the group.