Vehicle Control System Destination Type Segmentation
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Solution Overview
Problem
Current vehicle control systems, such as smart cruise control and lane departure warning systems, lack the ability to adapt to different destination types set by drivers, failing to provide optimal convenience and safety when arriving at a destination, particularly in distinguishing between final destinations and landmarks, and do not automatically adjust vehicle speed for timely arrival.
Innovation Solution
A method for controlling a self-driving vehicle based on the destination type selected by the driver, which includes deciding whether the destination is a final destination, controlling the vehicle to stop in the rightmost lane near the final destination, and switching to autonomous parking mode, or warning the driver to take control if it's not a final destination, using sensors and navigation data for accurate lane recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle automatically stops in the rightmost lane at the final destination, then driver convenience and safety are improved, but the control system complexity increases
Solution Approach 1:
The destination is segmented into different types (final destination vs. landmark/passage place), and the control system applies different stopping behaviors for each type. This segmentation allows the system to provide specialized convenience features only when needed, rather than always increasing complexity
Solution Approach 2:
The system automatically determines whether the destination is a final destination or landmark and autonomously decides the appropriate stopping behavior without requiring driver input. The vehicle serves itself by making control decisions based on destination type classification
2Measurement precision
If the vehicle distinguishes between final destination and landmark types, then arrival accuracy is improved, but the information processing requirement increases
Solution Approach 1:
Different quality levels of destination information are used locally - full destination type classification (final destination vs. landmark) is applied only when necessary for accurate stopping, while simpler processing is used for routine navigation. This local quality approach optimizes information processing by applying detailed analysis only where needed
3Productivity
If the vehicle automatically adjusts speed to arrive at destination within defined time, then productivity is improved, but the control complexity increases
Solution Approach 1:
The speed control system dynamically adjusts vehicle speed based on the calculated time required to reach the destination and the desired arrival time window. The control parameters change in real-time to optimize arrival efficiency while maintaining simplicity through adaptive rather than fixed control logic
Data Source
AI summary
A method for controlling a vehicle according to a destination type may promote convenience of a driver by changing a method for controlling a self driving vehicle according to a destination type set by the driver. The method for controlling a vehicle according to a destination type includes: deciding whether or not a destination type selected from a driver is a final destination; and controlling the vehicle to stop in the rightmost lane of a road closest to the final destination after the vehicle arrives at the vicinity of the final destination, when the selected destination type is the final destination.