AI Vehicle Routing Using Biometric Data to Reduce Driver Stress
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Solution Overview
Problem
Existing vehicle navigation systems fail to consider occupant health and stress levels, leading to increased driving stress and potential safety risks due to traffic congestion and other factors.
Innovation Solution
An AI system integrated into vehicle navigation that monitors biometric health data to assess stress levels and reroutes the vehicle to alternate paths that reduce stress, incorporating additional stops for relaxation, using machine learning to optimize routes based on health benefits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the vehicle follows the fastest or most direct route, then travel time is reduced, but occupant stress and health risks increase due to traffic congestion and other factors
Solution Approach 1:
The system changes the routing parameters from purely time-based optimization to health-based optimization. The AI model evaluates multiple routes by predicting health outcomes for each, selecting the route that maximizes occupant health even if it requires additional travel time. This transforms the decision-making parameter from speed to health benefit.
Solution Approach 2:
The patent introduces an intermediary AI health prediction model that acts as a mediator between the navigation system and route selection. This intermediary processes biometric data, evaluates multiple alternate routes, predicts health outcomes for each route, and recommends the optimal route based on health benefits rather than just travel time.
2Reliability
If the navigation system monitors biometric data and selects alternate routes, then occupant health improves, but device complexity increases
Solution Approach 1:
The navigation system is enhanced with multi-functionality by integrating biometric monitoring capabilities and AI-based health prediction. The system simultaneously performs traditional navigation functions and new health monitoring functions, using a unified platform that processes both location data and biometric data to make routing decisions.
Solution Approach 2:
The system employs self-service by automatically monitoring biometric data, evaluating alternate routes, predicting health outcomes, and selecting the optimal route without requiring manual user input. The AI model autonomously processes sensor data and makes routing decisions based on predicted health benefits.
3Object-affected harmful factors
If additional stops are added for relaxation, then stress reduction increases, but travel time increases
Solution Approach 1:
The system applies partial action by selectively adding relaxation stops only when and where they provide net health benefit. The AI model evaluates whether the stress reduction from a relaxation stop outweighs the additional travel time required, implementing stops only in situations where the health benefit justifies the time cost.
Data Source
AI summary
An example operation includes one or more of receiving sensor data from one or more sensors within a vehicle that is travelling on a route, the sensor data comprising biometric measurements of an occupant of the vehicle, determining that the occupant matches a predefined health status based on the biometric measurements of the occupant, in response, identifying a plurality of alternate routes for the vehicle and current travel attributes of the plurality of alternate routes, predicting a health value of the occupant on each of the plurality of alternate routes based on execution of an artificial intelligence (AI) model on the current travel attributes of the plurality of alternate routes, selecting an alternate route from among the plurality of alternate routes that raises a health of the occupant from the predefined health status, based on the predicted health value, and rerouting the vehicle along the alternate route.