Preemptive Collision Mitigation via Neural Data Analysis
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Solution Overview
Problem
Current collision risk mitigation technologies fail to predict and prevent unsafe driving events in real-time, often notifying nearby drivers only after a collision has occurred, and are limited by focusing on single-vehicle data, lacking the ability to detect risks before incidents happen.
Innovation Solution
A system that calculates future vehicle positions using carprobe data, including neural data from EEGs, to determine potential collisions and alert nearby drivers and pedestrians, enabling preemptive action to avoid accidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If notification is made after collision occurs, then drivers are informed of unsafe activity, but safety of nearby drivers and pedestrians is not secured
Solution Approach 1:
The system performs preliminary action by detecting unsafe driving behavior and notifying nearby drivers before a collision actually occurs. The notification system sends alerts to other vehicles in the vicinity when dangerous driving patterns are identified, enabling preventive measures to be taken in advance rather than reacting after an accident happens.
Solution Approach 2:
The system applies preliminary anti-action by taking countermeasures against potential collision risks before they materialize. When unsafe driving behavior is detected, the system proactively notifies other drivers to take evasive action, creating a preventive counter-force against the potential harmful collision outcome.
2Reliability
If data is limited to single vehicle, then system complexity is reduced, but determination of safety cannot be made without additional surrounding data
Solution Approach 1:
The system merges data from multiple vehicles and surrounding environment into a unified safety assessment model. By combining information from carprobe data, map data, and neural data across multiple vehicles, the system creates a comprehensive view of the driving environment that enables more accurate safety determination than single-vehicle systems could achieve alone.
Solution Approach 2:
The system achieves universality by creating a multi-functional platform that not only monitors individual vehicle safety but also assesses overall environmental safety conditions. The same infrastructure serves multiple purposes: individual driver monitoring, collision prediction, and area-wide safety assessment, making the system adaptable to various safety determination needs.
3Reliability
If real-time driver state measurement is implemented, then driver condition is detected, but ability to detect risk in advance or before incident occurs is not achieved
Solution Approach 1:
The system performs preliminary detection of unsafe driving events by analyzing patterns in neural data and carprobe information before actual incidents occur. By continuously monitoring driver state and vehicle parameters in advance, the system can predict potential collisions and notify drivers proactively, rather than merely detecting conditions after they manifest.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring driver state through neural data and comparing it against safety thresholds. When deviations indicating potential unsafe behavior are detected, the system provides feedback through notifications to the driver and alerts to nearby vehicles, creating a closed-loop system that enables preventive intervention based on real-time analysis.
Data Source
AI summary
A method, computer system, and a computer program product for preemptive collision mitigation is provided. The present invention may include calculating a future position of a first vehicle based on carprobe data from a first vehicle, wherein the carprobe data contains neural data of an operator of the first vehicle. The present invention may also include calculating a distance between the future position of the first vehicle and a future position of a second vehicle. The present invention may then include determining the calculated distance between the future position of the first vehicle and the future position of the second vehicle is below a threshold distance.