Connected Driving Risk Analysis for Safer Route Guidance
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Solution Overview
Problem
Current GPS devices and navigation systems do not effectively reduce the likelihood of accidents and lack the ability to provide real-time risk assessments and safer route recommendations based on dynamic environmental and vehicle data.
Innovation Solution
A system comprising sensors and processors that detect and analyze various data types, including accident, geographic, environmental, and vehicle information, to calculate a dynamic risk assessment and provide alerts and recommendations for safer routes, enabling or disabling mobile device features based on safety conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If GPS devices provide location information and accident history information, then drivers can see danger levels of routes, but this information alone does not significantly reduce the likelihood of accidents occurring
Solution Approach 1:
The system continuously collects real-time sensor data from the vehicle (speed, acceleration, steering angle, brake pressure) and mobile device (GPS location, route information) and feeds this information back to dynamically update risk assessments. This closed-loop feedback mechanism transforms static accident history information into dynamic, actionable risk mitigation guidance that adapts to current driving conditions, thereby significantly reducing accident likelihood
Solution Approach 2:
The system performs preliminary risk assessments by analyzing historical accident data and current sensor information before accidents occur. By identifying high-risk routes and conditions in advance and providing proactive warnings to drivers, the system enables preventive action rather than merely reporting dangers after they materialize, thus significantly reducing accident occurrence
2Reliability
If the system calculates dynamic risk assessment using multiple data sources, then safer route recommendations can be provided, but the system complexity increases
Solution Approach 1:
The system segments the complex risk assessment task into distinct functional modules: a data collection module that gathers sensor and mobile device information, a risk calculation module that processes the collected data using predefined algorithms, and a recommendation module that generates safer route suggestions. This segmentation allows each module to handle specific data processing responsibilities independently, managing system complexity while maintaining comprehensive risk assessment accuracy
Solution Approach 2:
The system employs a multi-functional processing architecture where the same hardware processors and communication interfaces handle multiple data types (sensor data, GPS information, accident history) and perform various functions (data collection, risk calculation, route recommendation). This universal approach reduces overall system complexity compared to having dedicated specialized components for each function, while still achieving reliable dynamic risk assessment
Data Source
AI summary
Systems including one or more sensors, coupled to a vehicle, may detect sensor information and provide the sensor information to another computing device for processing. A system includes one or more sensors, coupled to a vehicle and configured to detect sensor information, and a computing device configured to communicate with one or more mobile sensors to receive the mobile sensor information, communicate with the one or more sensors to receive the sensor information, and analyze the sensor information and the mobile sensor information to identify one or more risk factors.