Rivian ip holdings, llc (20240219198). DATA-INTENSIVE ELECTRONIC MAP DATA STRUCTURES simplified abstract
DATA-INTENSIVE ELECTRONIC MAP DATA STRUCTURES
Organization Name
Inventor(s)
Philipp W. Beisel of San Jose CA (US)
DATA-INTENSIVE ELECTRONIC MAP DATA STRUCTURES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240219198 titled 'DATA-INTENSIVE ELECTRONIC MAP DATA STRUCTURES
Simplified Explanation
The patent application focuses on receiving sensor data from vehicles traveling on a road, detecting when the data exceeds a threshold, and using this information to modify vehicle operating conditions.
- Sensor data is collected from vehicles on a road.
- Data exceeding a threshold is identified for specific road segments.
- Geo-coordinates for these segments are detected.
- A data structure is created to indicate the segments with data exceeding the threshold.
- When a vehicle is detected on the road, the data structure is updated.
- Vehicle operating conditions can be adjusted based on the data in the structure.
Key Features and Innovation
- Collection and analysis of sensor data from vehicles.
- Identification of data exceeding a threshold for specific road segments.
- Real-time monitoring and modification of vehicle operating conditions.
- Integration of geo-coordinates to track vehicles on the road.
- Adaptive system to improve vehicle safety and efficiency.
Potential Applications
This technology can be applied in:
- Fleet management systems.
- Traffic monitoring and control.
- Autonomous vehicle navigation.
- Predictive maintenance for vehicles.
- Insurance telematics.
Problems Solved
- Enhances road safety by monitoring vehicle data.
- Improves efficiency by adjusting vehicle operating conditions.
- Enables proactive maintenance based on sensor data.
- Facilitates real-time decision-making for vehicle management.
- Enhances overall transportation system performance.
Benefits
- Increased safety for vehicles and road users.
- Optimized vehicle performance and fuel efficiency.
- Reduced maintenance costs through proactive monitoring.
- Enhanced data-driven decision-making for vehicle management.
- Improved overall transportation system efficiency.
Commercial Applications
Title: Real-time Vehicle Monitoring and Control System This technology can be used in:
- Automotive industry for vehicle tracking and optimization.
- Transportation companies for fleet management.
- Smart city initiatives for traffic control and monitoring.
- Insurance companies for usage-based policies.
- Research institutions for data analysis and transportation studies.
Questions about the Technology
How does this technology improve road safety?
This technology enhances road safety by monitoring vehicle data in real-time, allowing for proactive adjustments to vehicle operating conditions to prevent accidents and improve overall safety on the road.
What are the potential applications of this technology beyond vehicle management?
This technology can also be applied in traffic monitoring and control systems, autonomous vehicle navigation, predictive maintenance for vehicles, and insurance telematics, showcasing its versatility and wide range of potential uses.
Original Abstract Submitted
aspects herein are directed to sensor data being received, via one or more sensors coupled to one or more vehicles, based on the one or more vehicles traversing a road in a geographical area. a portion of the sensor data is determined to exceed a threshold. the portion of the sensor data being associated with a segment of the road. geo-coordinates associated with the segment of the road are detected. based at least in part on the detecting of the geo-coordinates, a data structure that indicates the segment and the portion of the sensor data exceeding the threshold is populated. an indication that a first vehicle is traversing the road or that traversing the road is part of a route plan for the first vehicle is received. in response to the receiving of the indication, the data structure is derived. a modification of a vehicle operating condition is facilitated based on the segment and the sensor data in the derived data structure.