Autonomous Vehicle Path Segmentation for Human-Like Driving Smoothness
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Solution Overview
Problem
Autonomous vehicles experience unsmooth acceleration, deceleration, and turning, leading to passenger discomfort due to the lack of efficient ways to replicate human driving behaviors in various scenarios.
Innovation Solution
A driving scene database is created to store and replicate human driving behaviors, allowing autonomous vehicles to match and mimic human driving parameters in predefined scenarios, thereby improving the driving experience by segmenting routes into path segments and using corresponding driving parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous vehicle control systems operate without human driver reference data, then automation extent is improved, but driving smoothness deteriorates
Solution Approach 1:
The system creates a driving scene database that stores and replicates human driver behaviors by recording acceleration, deceleration, and steering parameters across various driving scenarios. The autonomous vehicle then copies these human-driven parameters to match and replicate natural driving patterns, thereby maintaining driving smoothness while operating autonomously
Solution Approach 2:
The system modifies driving parameters by segmenting routes into path segments and selecting appropriate human driver parameters from the database for each segment. This dynamic parameter selection based on driving scenes allows the autonomous vehicle to adapt its acceleration, deceleration, and steering characteristics to match human driving behavior in different contexts
2Ease of operation
If human driver behaviors are recorded for all driving scenarios, then driving smoothness is improved, but device complexity increases
Solution Approach 1:
The system segments the driving database into distinct driving scenes (e.g., acceleration, deceleration, turning scenarios) and further divides routes into path segments. This segmentation allows the system to store human driver behaviors in an organized manner and efficiently retrieve only the relevant parameters needed for current driving conditions, reducing unnecessary data processing complexity
Solution Approach 2:
The system performs preliminary actions by pre-recording and storing human driver behaviors across various driving scenarios in the driving scene database before autonomous operation. This advance preparation allows the autonomous vehicle to quickly reference and apply appropriate human-driven parameters during operation without requiring complex real-time analysis, thereby reducing processing complexity while maintaining smoothness
Data Source
AI summary
In one embodiment, motion planning and control data is received, where the motion planning and control data indicates that an autonomous vehicle is to move from a first point to a second point of a path within a predetermined route. In response to the motion planning and control data, the path from the first point to the second point is segmented into multiple path segments. For each of the path segments, one of predetermined driving scenes is identified that matches motion characteristics of the corresponding path segment. The motion planning and control data associated with the path segments is modified based on predetermined motion settings of the path segments. The autonomous vehicle is driven through the path segments of the path based on the modified motion planning and control data.