Vehicle Driving Control with Dynamic Weighting for Lane and Speed Deviations
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Solution Overview
Problem
Conventional travel control devices fail to ensure safe vehicle travel when there is a significant difference between the vehicle's advancing direction and the target route direction or when the distance to a preceding vehicle changes significantly.
Innovation Solution
A driving control device that calculates acceleration/deceleration and steering angle instructions using an evaluation function with dynamically adjusted weighting coefficients based on lateral, speed, and azimuth deviations, considering factors like proximity to preceding vehicles and lane boundaries, to optimize vehicle control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the same target speed is calculated based on curvature and lateral deviation, then the vehicle can travel at a speed suited for the road surface, but the vehicle cannot travel safely when the difference between advancing direction and target route direction is large or when distance to preceding vehicle changes significantly
Solution Approach 1:
The patent applies dynamics by making the weighting coefficients in the evaluation function variable rather than fixed. The deciding section dynamically adjusts the first weighting coefficient (for speed deviation) and second weighting coefficient (for lateral deviation) based on real-time situational factors such as distance to preceding vehicles and azimuth deviation. This allows the control system to adapt its priorities - for example, increasing the weight of speed deviation when a preceding vehicle is detected, or increasing lateral deviation weight when azimuth deviation is large - thereby resolving the contradiction between maintaining safe travel and adapting to diverse situational changes
Solution Approach 2:
The patent implements parameter changes by modifying the weighting coefficients in the evaluation function based on detected situational parameters. The acquiring section detects parameters such as distance to preceding vehicles, azimuth deviation, and lateral deviation. The deciding section then changes the weighting coefficients according to these parameters - for instance, increasing the first weighting coefficient when distance to preceding vehicle is short, or increasing the second weighting coefficient when azimuth deviation exceeds a threshold. This dynamic parameter adjustment enables the system to prioritize different control objectives based on the current situation, improving both safety and adaptability
2Reliability
If weighting coefficients are adjusted based on multiple situational factors, then vehicle safety is improved, but the device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the control system into distinct functional sections: an acquiring section that detects situational parameters, a deciding section that determines weighting coefficients, and a calculating section that computes control commands. This segmentation allows each section to perform its specific function independently, managing complexity through modular organization. The deciding section further segments the decision-making process by establishing different weighting coefficient adjustment rules for different situations (e.g., one rule when preceding vehicle distance is short, another when azimuth deviation is large), making the complex control logic more manageable and implementable
Solution Approach 2:
The patent implements feedback by using the detected situational parameters (distance to preceding vehicle, azimuth deviation, lateral deviation) to continuously adjust the weighting coefficients in real-time. The acquiring section monitors the environment, feeds this information to the deciding section, which then adjusts the weighting coefficients accordingly. This closed-loop feedback mechanism allows the system to automatically adapt to changing conditions without requiring complex manual intervention, improving safety while managing complexity through automated feedback-driven adjustment
Data Source
AI summary
A driving control device has: a deciding section that decides a first weighting coefficient and a second weighting coefficient in an evaluation function including, as variables, a lateral deviation of a vehicle, a speed deviation of the vehicle, an azimuth deviation of the vehicle, an acceleration/deceleration instruction value and a steering angle instruction value; a calculating section that calculates the acceleration/deceleration instruction value and the steering angle instruction value for a time of a next period for minimizing or maximizing an output value of the evaluation function, by periodically inputting the lateral deviation, the speed deviation and the azimuth deviation to the evaluation function; and a travel control section that causes the vehicle to travel on a basis of the acceleration/deceleration instruction value and the steering angle instruction value.