Adaptive Speed Recommendation in Vehicle Vigilance Zones
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Solution Overview
Problem
Existing driving assistance systems do not provide adequate support to drivers in adjusting their vehicle speed within vigilance areas, relying solely on the driver's judgment and experience.
Innovation Solution
A system that collects and analyzes travel speed data to calculate statistical speed values and recommend adjusted speeds based on driver, vehicle, and environmental data, using a remote server and on-board device to generate location data defining vigilance areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed threshold alert system is used, then the device complexity is reduced, but the adaptability to different driving conditions deteriorates
Solution Approach 1:
The patent implements dynamic speed limits that automatically adjust based on real-time environmental conditions (weather, traffic, road geometry) and vehicle characteristics, replacing fixed threshold systems with adaptive algorithms that recalculate recommended speeds continuously
Solution Approach 2:
The system changes the parameter of speed limits from fixed values to dynamically variable values based on multiple input factors including weather conditions, traffic density, road curvature, and vehicle performance characteristics, allowing the alert threshold to adapt to varying driving contexts
2Measurement precision
If real-time speed monitoring and analysis is implemented, then the measurement precision of speed data is improved, but the use of energy increases
Solution Approach 1:
The system continuously collects and processes speed data from multiple vehicles in real-time throughout the day, accumulating precise measurements that feed into statistical models, maintaining continuous monitoring rather than periodic sampling to ensure data accuracy
Solution Approach 2:
The system implements feedback loops where collected speed data is analyzed statistically, and the results are used to update and refine speed recommendations, creating a self-improving system that becomes more accurate over time while optimizing energy usage based on learned patterns
3Reliability
If statistical analysis of multiple vehicles' speed data is performed, then the reliability of speed recommendations is improved, but the loss of time for data processing increases
Solution Approach 1:
The system performs preliminary statistical analysis on speed data as it is collected, calculating mean speeds, standard deviations, and other statistical parameters in real-time rather than waiting to accumulate large datasets, enabling immediate generation of reliable recommendations
Solution Approach 2:
The system uses the speed data from vehicles themselves to generate recommendations for those same vehicles, with each vehicle contributing to and benefiting from the collective statistical analysis, reducing the need for external processing infrastructure
Data Source
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Figure 3
AI summary
Driving assistance device (2) intended to be on board a vehicle (1) and configured for detecting the presence of the device in a predefined vigilance zone (4); identifying a speed profile associated with the vigilance zone, said speed profile relating to a recommended speed at a given position in the vigilance zone; determining the position of the device in the vigilance zone; determining a moving speed of the device substantially at the determined position; determining from the speed profile a recommended speed relating to the determined position; calculating a difference between the determined moving speed and the determined recommended speed; triggering an alert at least when the calculated difference is greater than a predefined threshold alert value.