Driving App Feature Adaptation Based on Hazardous Vehicle Events
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Smartphone usage in vehicles can lead to accidents due to driver distraction, with users often unaware of the correlation between application features and hazardous driving events, and existing safety features may inadvertently increase risk.
Innovation Solution
Implementing a system that correlates vehicle events with application features using sensors to detect hazardous driving maneuvers and suggests or disables non-driving-optimized features, promoting driving-optimized alternatives to reduce risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicle-optimized application features are implemented to mitigate accident risk, then safety is improved, but users may be apprehensive about adopting these features
Solution Approach 1:
The system monitors driving events and application feature usage, then provides feedback to users about correlations between specific features and hazardous events. This evidence-based feedback helps users understand the safety benefits objectively, reducing apprehension and encouraging adoption of driving-optimized features.
Solution Approach 2:
The system proactively suggests driving-optimized application features before hazardous events occur, based on analysis of driving patterns and event correlations. By preparing users in advance with relevant safety information and feature recommendations, the system facilitates smoother adoption without requiring users to react to crises.
2Loss of information
If users manually monitor their driving behavior to assess safety, then awareness is improved, but users are ineffective at gauging whether application features mitigate risk
Solution Approach 1:
The system acts as an intermediary between the complex data of driving behavior and application usage, and the user's understanding. It automatically collects, analyzes, and presents processed information about correlations between specific application features and hazardous events, eliminating the need for users to manually track and interpret raw data themselves.
Solution Approach 2:
The system replaces manual human monitoring and assessment with automated sensor-based detection and algorithmic analysis. Sensors objectively detect driving events, and the system precisely measures correlations between application features and events, providing accurate risk assessment without relying on imperfect human memory and judgment.
3Measurement precision
If sensors are used to detect vehicle events, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The system uses a multi-functional sensor platform where the same sensors serve multiple purposes: detecting driving events, monitoring application usage patterns, and providing data for correlation analysis. This universal approach improves detection accuracy without proportionally increasing complexity, as the sensor infrastructure supports multiple safety functions simultaneously.
Data Source
AI summary
Methods and apparatus for detecting hazardous vehicle events and encouraging usage of driving optimized application features to mitigate occurrence of the hazardous vehicle events. The driving optimized application features can address unsafe driving events that are determined to be correlated with certain distracting application features. For example, an application of a computing device can determine that a user is occupying a vehicle and is driving toward a destination. While driving, data available to the application can indicate that an unsafe driving event, such as a hard braking event, has occurred while the user was interacting with another application. Thereafter, and based on this data, the application can render an output characterizing the correlation between the hard braking event and the other application, and/or provide the user with an option to interact with the other application via driving optimized feature(s).