Adaptive Curve Guidance Using Real-Time Centrifugal Force
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Solution Overview
Problem
Current navigation systems face challenges in providing accurate real-time risk guidance for curve sections, as they often rely on pre-surveyed data and do not account for the vehicle's current speed, leading to increased accident risks and unnecessary guidance.
Innovation Solution
An adaptive curve guidance method that utilizes link information and vehicle speed to predict future positions and calculate centrifugal force, comparing it to threshold values to assess the risk level of curve sections, thereby providing safe driving speed guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-surveyed data is used for curve guidance, then curve sections can be identified in advance, but the system cannot respond adequately to real-time road situations and provides incorrect information
Solution Approach 1:
The system dynamically adjusts curve guidance by continuously monitoring real-time vehicle speed and recalculating risk levels based on current conditions rather than relying on static pre-surveyed data. The risk level is updated in real-time as the vehicle progresses through the curve section.
Solution Approach 2:
The system incorporates feedback loops where vehicle speed information is continuously fed back to the risk calculation module, allowing the system to adjust guidance information based on actual driving conditions and provide corrected real-time assessments.
2Ease of operation
If curve guidance is provided without considering vehicle speed, then all curve sections are guided uniformly, but accident risk increases due to lack of speed-aware risk assessment
Solution Approach 1:
The system applies different risk levels and guidance strategies to different curve sections based on local conditions such as vehicle speed, curve radius, and road characteristics. Each curve section receives customized risk assessment rather than uniform guidance.
Solution Approach 2:
The system changes the risk assessment parameters dynamically based on vehicle speed and other real-time conditions. The risk level is not fixed but varies according to the parameters measured, allowing speed-aware risk assessment.
3Loss of information
If pre-surveying of all areas is performed, then comprehensive curve data is available, but high costs are incurred
Solution Approach 1:
The system uses the vehicle's own sensors and onboard computer to perform real-time curve detection and risk assessment, eliminating the need for external pre-surveying operations. The vehicle serves its own information needs through self-contained detection capabilities.
Solution Approach 2:
The system replaces mechanical pre-surveying methods with electronic sensing and computational algorithms. Instead of physical surveys, the system uses sensors, GPS, and computer processing to detect and assess curve sections in real-time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances safety by providing accurate real-time risk assessments for curve sections, reducing accidents and minimizing unnecessary guidance, while also eliminating the need for costly pre-surveying of all areas.
Implementation Method 1
calculating centrifugal force to be applied to the vehicle in the curve section using a plurality of determined positions and a speed of the vehicle
Data Source
AI summary
A road curve guidance method is provided. The road curve guidance method includes: obtaining link information corresponding to a road on which a vehicle is being driven; determining a position of the vehicle on a link at a future time point based on the obtained link information; and judging a degree of risk of a curve section in which the vehicle is to be driven after a predetermined time using the determined position and speed of the vehicle at a reference time point.