Autonomous Vehicle Coasting Control in Multi-Vehicle Traffic
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Solution Overview
Problem
Conventional autonomous vehicle systems struggle to accurately determine when to coast in traffic due to the variability in movements of multiple leading vehicles, often treating them as a single entity or failing to account for their independence, which affects the reliability of navigation and control functions.
Innovation Solution
The system determines the speeds and stations of leading vehicles, calculates a coasting viability factor by comparing target points to a coasting profile, and decides whether the ego vehicle should coast based on a coasting viability threshold, using machine learning models to enhance decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If multiple leading vehicles are treated as a single entity for coasting decisions, then the system complexity is reduced, but the measurement precision of traffic conditions deteriorates
Solution Approach 1:
The patent segments the group of multiple leading vehicles into individual vehicle entities, each with its own speed and station data. The coasting viability factor is calculated by evaluating each leading vehicle separately rather than treating them as a single aggregate entity, thereby improving measurement precision while maintaining manageable system complexity through structured individual assessments.
2Reliability
If individual movements of multiple leading vehicles are accounted for, then the reliability of coasting decisions is improved, but the device complexity increases
Solution Approach 1:
The patent implements a dynamic evaluation system where the coasting viability factor is continuously updated based on real-time speed and station data from multiple leading vehicles. The system adaptively adjusts coasting decisions by comparing predicted coasting speeds against actual traffic conditions, allowing reliability to improve through responsive individual vehicle tracking while managing complexity through algorithmic efficiency.
3Ease of operation
If conventional methods are used to determine coasting timing, then the ease of operation is maintained, but the productivity of navigation functions deteriorates
Solution Approach 1:
The patent implements a self-service navigation system where the autonomous vehicle automatically determines coasting viability by processing its own speed and station data alongside data from leading vehicles. The system autonomously calculates the coasting viability factor and makes coasting decisions without external intervention, thereby improving navigation productivity while maintaining ease of operation through automated decision-making.
Data Source
AI summary
Methods, systems, and non-transitory computer readable media configured to perform operations comprise determining, by a computing system, speeds and stations of a plurality of leading vehicles traveling ahead of an ego vehicle; calculating, by the computing system, a coasting viability factor based on the speeds and stations of the plurality of leading vehicles and a speed and station of the ego vehicle; comparing, by the computing system, the coasting viability factor to a coasting viability threshold; and determining, by the computing system, whether the ego vehicle should coast based on the comparing.