Vehicle Tracking Detection and Alarm Method
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle monitoring systems for detecting driver fatigue or alertness are either invasive, prone to errors, or inconvenient, failing to effectively alert drivers of unsafe driving conditions.
Innovation Solution
A vehicle tracking detection and alarm method using GPS data to calculate deflections and average speeds, determining unsafe driving by comparing these values against preset thresholds, and activating an alarm if unsafe driving instances exceed a predetermined frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an infrared eyeball scanner is used to detect driver fatigue, then driver alertness can be monitored, but the infrared rays may damage the eyeballs
Solution Approach 1:
The patent extracts the detection function from the harmful infrared scanning method and implements it through GPS trajectory analysis instead. The system monitors driver alertness by analyzing driving behavior patterns (trajectory smoothness, speed variations, steering patterns) rather than directly scanning the driver's eyes with infrared rays, thus eliminating the harmful effect while preserving the detection capability
Solution Approach 2:
The patent introduces GPS trajectory data as an intermediary indicator to indirectly assess driver alertness. Instead of directly observing the driver's physiological state (which requires harmful infrared exposure), the system uses the driver's driving behavior manifested in GPS data as a mediator to infer alertness levels, thereby avoiding direct contact with the driver
2Reliability
If an image identification device is used to locate driver eyes, then driver fatigue can be determined, but the system is prone to errors
Solution Approach 1:
The patent employs the vehicle's existing GPS navigation system to serve the additional function of driver alertness monitoring. The GPS device already captures trajectory data for navigation purposes, and this same data is now utilized to assess driver alertness through behavioral analysis, eliminating the need for separate image identification hardware and reducing system complexity and error sources
Solution Approach 2:
The patent replaces the mechanical/optical image identification system with a computational analysis method based on GPS trajectory data. Instead of using cameras and image processing algorithms to locate eyes, the system uses mathematical analysis of trajectory patterns (deflections, average speeds, angular changes) to detect driver alertness, thereby improving precision and eliminating the errors associated with image-based methods
3Reliability
If a blood-pressure detection device is used to assess driver fitness, then driver fitness can be determined, but the device is inconvenient to attach and errors are common
Solution Approach 1:
The patent makes the GPS navigation device multi-functional by adding driver alertness monitoring capability to its existing navigation functions. The same GPS hardware and data collection system serve both navigation and safety monitoring purposes, eliminating the need for separate blood-pressure detection devices and improving ease of operation while maintaining assessment capability
Solution Approach 2:
The GPS system monitors driver alertness using data that is already being collected for navigation purposes (location, speed, trajectory). The driver does not need to attach any additional devices or consciously participate in the monitoring process - the system passively analyzes the driving behavior reflected in the GPS data, thereby maximizing convenience while maintaining reliable assessment
Data Source
AI summary
A tracking detection and alarm method which is applied to a navigation device use a number of positioning data points retrieved from a navigation module of the navigation device. A number of deflections and a number of average speeds that correspond to the position data points are calculated and generated. A number of maximum deflections are calculated and generated according to the average speeds. When a deflection of a positioning data point is greater than a maximum safe deflection thereof, one is added to a frequency of unsafe driving instances. When the frequency of unsafe driving instances is greater than a preset threshold value, an unsafe driving alarm is activated.