Automated Driving Risk Control Using Speed-Based Perceived Risk
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Solution Overview
Problem
Current automated driving systems fail to accurately represent the perceived risk levels experienced by human drivers, leading to inadequate control methods that do not accurately replicate human driving behavior, especially across varying speed ranges and geographical regions.
Innovation Solution
A control method that calculates the perceived risk level as a function of the host vehicle's speed, relative speed, and relative distance, incorporating parameters such as the product of the host vehicle speed and relative speed, and the square of the host vehicle speed, to provide a more accurate representation of the risk perceived by a human driver, allowing for better control of vehicle devices such as brakes and actuators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the perceived risk level is calculated using only linear functions of vehicle speed and relative speed, then the calculation is simple, but the accuracy of representing human driver perception deteriorates
Solution Approach 1:
The patent changes the mathematical parameters used in risk calculation from linear functions to include quadratic terms (Vx²) and interaction terms (Vx×Vr). This transforms the calculation from a simple linear model to a more complex polynomial model that better captures human driver perception patterns across different speed ranges, thereby improving measurement precision while accepting increased calculation complexity.
2Ease of operation
If the control system uses a simplified risk model, then the system is easier to operate, but the ability to replicate human driving behavior deteriorates
Solution Approach 1:
The patent modifies the risk calculation parameters to include squared velocity terms and velocity product terms, creating a more sophisticated model that accurately replicates human driver behavior across varying speed conditions. This enhances the reliability of behavior replication while maintaining system operability through automated calculation.
3Device complexity
If the automated driving system uses a basic risk assessment model, then the device complexity is reduced, but the adaptability to different speed ranges and geographical regions deteriorates
Solution Approach 1:
The patent enhances model adaptability by incorporating quadratic and interaction terms into the risk assessment formula. These parameter changes enable the system to accurately represent human driver behavior across a broad spectrum of speed ranges (from 10 km/h to 120 km/h) and different geographical regions, while the automated calculation maintains manageable device complexity.
Data Source
AI summary
A control method for a host vehicle (100), comprisinga) acquiring a speed (Vx) of the host vehicle, a relative speed (Vr) and distance (Dr) between a preceding vehicle (200) and the host vehicle (100);b) calculating a perceived risk level (PRL) as a function of said speed Vx of the host vehicle, said relative speed Vr, said relative distance Dr, and at least one of variables Vx*Vr and Vx2; andc) controlling at least one vehicle device (32, 34, 36, 38) of the host vehicle as a function of the perceived risk level (PRL).A computer program, a non-transitory computer-readable medium, and an automated driving system for implementing the above method.