Vehicle Control System for Individual Passenger Fall Risk Assessment
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Solution Overview
Problem
Conventional in-vehicle monitoring systems fail to accurately assess the falling risk of passengers, leading to either excessive driving restrictions or insufficient safety measures, as they do not individually track the state of each passenger within the vehicle compartment.
Innovation Solution
A vehicle control method and system that acquires attribute information for each passenger, determines their falling risk, and tracks high-risk passengers to implement tailored travel restrictions, ensuring smooth vehicle operation while preventing falls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional in-vehicle monitoring systems control braking and acceleration based on overall passenger occupancy rate, then vehicle safety can be maintained at a basic level, but the system cannot accurately assess individual falling risks leading to either excessive driving restrictions or insufficient safety measures
Solution Approach 1:
The patent segments the monitoring system to track each passenger individually rather than treating all passengers as a group. Each passenger is assigned a unique identifier and their state information is collected and managed separately, enabling precise individual risk assessment while using a standardized data collection framework that prevents system complexity from becoming unmanageable.
Solution Approach 2:
The system applies different monitoring and control strategies to different passengers based on their individual characteristics. High-risk passengers receive enhanced monitoring and more conservative vehicle control measures, while low-risk passengers do not trigger unnecessary restrictions. This localized approach optimizes safety measures for each passenger's actual risk level.
2Reliability
If the system tracks each passenger individually and implements tailored travel restrictions, then falling risk prevention is improved, but the complexity of acquiring and processing individual passenger data increases
Solution Approach 1:
The system collects and stores attribute information for each passenger in advance before the monitoring process begins. This preliminary data collection includes demographic information, health status, and other risk factors that are stored and ready for rapid processing when the passenger boards the vehicle, eliminating the need for complex real-time data gathering during critical moments.
Solution Approach 2:
The system continuously monitors passenger state information and provides feedback to adjust vehicle control in real-time. Sensors detect passenger movement, posture, and other dynamic parameters, and this feedback loop enables the system to automatically adjust acceleration, braking, and routing decisions to maintain passenger safety without requiring complex manual intervention.
3Reliability
If the system implements comprehensive individual monitoring and control, then falling prevention effectiveness is enhanced, but the processing time and computational resources required increase
Solution Approach 1:
The system focuses monitoring resources on high-risk passengers rather than applying equal computational effort to all passengers. By identifying passengers with elevated falling risk based on attribute information and real-time state data, the system concentrates processing power where it is most needed, reducing overall computational burden while maintaining high prevention effectiveness for vulnerable individuals.
Data Source
AI summary
A computer executable method for passengers boarding a vehicle includes: acquiring attribute information for each of passengers; determining a falling-down risk of each passenger individually based on the attribute information; tracking a high-risk person determined to have a high falling-down risk in a passenger compartment of the vehicle; and grasping a condition of the high-risk person individually in the passenger compartment.