Vehicle Trajectory Load Calculation for Dangerous Driving Index
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Solution Overview
Problem
Existing autonomous driving systems struggle to accurately reflect a driver's habits in real-time, leading to potential safety issues due to reliance on learned past driving patterns, especially in sudden or abnormal situations.
Innovation Solution
A system that utilizes internal and external sensors to generate and compare driving trajectories, calculating a dangerous driving index by considering trajectory loads, peripheral vehicle loads, and road conditions, providing real-time feedback to the driver and vehicle control systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If autonomous driving control system uses learned past driving patterns to control vehicle, then driving assistance and comfort are improved, but accuracy in reflecting actual driving habits deteriorates when abnormal situations occur
Solution Approach 1:
The system pre-calculates multiple possible driving trajectories (first trajectory from driver's habit, second trajectory from autonomous control) and prepares comparison metrics before the driving situation unfolds. This allows real-time comparison without relying solely on learned patterns, improving accuracy in abnormal situations while maintaining driving assistance benefits
Solution Approach 2:
The system continuously compares the driver's actual vehicle trajectory with the autonomous driving trajectory in real-time, providing feedback on the degree of coincidence. This feedback mechanism allows the system to adapt and accurately reflect actual driving habits dynamically, rather than relying on static learned patterns, resolving the contradiction between driving assistance and measurement precision
2Reliability
If autonomous vehicle provides larger repulsion to driver based on abnormally collected past driving data, then safety warning is strengthened, but driver comfort and acceptance deteriorate
Solution Approach 1:
The system dynamically adjusts the dangerous driving index based on real-time trajectory comparison rather than static past data. When the driver's trajectory deviates from the autonomous trajectory, the system adaptively generates appropriate warnings, ensuring safety warnings are reliable while maintaining driver comfort through contextual appropriateness
Solution Approach 2:
The system changes the parameter for safety assessment from static past driving patterns to dynamic real-time trajectory coincidence degree. This allows the system to provide reliable safety warnings based on actual current driving behavior while avoiding unnecessary warnings that would reduce driver comfort and acceptance
3Measurement precision
If system compares driver's vehicle trajectory with peripheral vehicle trajectory using multiple sensors, then measurement precision of driving habit is improved, but device complexity increases
Solution Approach 1:
The system uses existing vehicle sensors (cameras, radar, GPS) for multiple purposes: both for autonomous trajectory generation and for comparing driver's actual trajectory. This multi-functionality approach improves measurement precision without significantly increasing device complexity, as the same hardware serves dual purposes
Solution Approach 2:
The system creates a virtual copy of the driver's vehicle trajectory by processing sensor data, and compares it with the autonomous driving trajectory. This copying approach allows precise comparison without adding physical sensors, maintaining measurement precision while avoiding increased device complexity
Data Source
AI summary
Provided are a system and method for managing dangerous driving index for vehicle. The system includes a driver's vehicle driving trajectory generator configured to generate a driver's vehicle driving trajectory, based on driver's vehicle driving information input from an internal sensor which senses a driving situation of the driver's vehicle, a peripheral vehicle trajectory generator configured to generate a peripheral vehicle trajectory, based on ambient environment information input from an external sensor which senses the driving situation of the driver's vehicle, a trajectory load calculator configured to calculate a trajectory load representing a comparison result which is obtained by comparing a predetermined threshold value with a trajectory distance which is a difference between the peripheral vehicle trajectory and the driver's vehicle driving trajectory, and a dangerous index manager configured to generate a dangerous driving index corresponding to the calculated trajectory load.