Drive Assist Apparatus Risk Map Expansion for Environmental Deviations
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Solution Overview
Problem
Existing drive assist apparatuses do not adequately consider deviations in a vehicle's drive track due to external environmental factors like road surface conditions and winds, leading to potential collisions with risk objects.
Innovation Solution
A drive assist apparatus that generates a risk map by assigning a risk potential to risk objects and expands the setting range of this potential based on external environmental factors such as road surface friction states and wind directions, thereby adjusting the vehicle's drive conditions to minimize collision risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the drive assist apparatus sets drive conditions based on apparent risks only, then the system complexity is low, but the reliability of collision avoidance deteriorates due to unaccounted track deviations
Solution Approach 1:
The system performs preliminary action by predicting the expected drive track deviation caused by external environmental factors before the vehicle actually deviates. The risk map generator pre-calculates the expanded risk areas by anticipating where the vehicle might drift, allowing the drive condition setter to proactively adjust the drive track to avoid these predicted risk zones, thereby improving collision avoidance reliability without requiring complex real-time intervention systems
Solution Approach 2:
The system transitions from a two-dimensional risk map (distance and direction from vehicle) to a three-dimensional risk assessment by incorporating the expected drive track deviation as an additional spatial dimension. This allows the risk map generator to create a more comprehensive risk model that accounts for lateral displacement, enabling more reliable collision avoidance while maintaining manageable system complexity through algorithmic expansion rather than additional hardware
2Reliability
If the risk potential setting range is expanded to account for external factors, then the safety improves, but the computational load and processing time increase
Solution Approach 1:
The system calculates the expected drive track deviation in advance based on pre-stored environmental factor data (road surface friction coefficients, wind characteristics) before generating the risk map. This preliminary calculation allows the risk map generator to efficiently expand the risk potential setting range without adding significant processing time during critical drive condition adjustments
Solution Approach 2:
The system optimizes computational efficiency by dynamically adjusting the expansion distance parameter based on the magnitude of external environmental factors. When road surface friction is low or wind speed is high, the expansion distance increases proportionally, but the system uses efficient algorithms to calculate this expansion, balancing enhanced safety with acceptable processing time for real-time drive condition adjustments
3Measurement precision
If the system considers more external environmental factors, then the drive condition accuracy improves, but the information processing complexity increases
Solution Approach 1:
The system applies local quality by selectively processing external environmental factor information based on its relevance to the current drive situation. The risk map generator focuses on calculating deviations caused by significant factors (such as low friction road surfaces or strong winds) while simplifying or ignoring minor factors, thereby improving drive condition accuracy for critical scenarios without overwhelming the information processing system with unnecessary complexity
Data Source
AI summary
A drive assist apparatus configured to set a drive condition of a vehicle based on a risk map generated by giving a risk potential to a risk object that is present around the vehicle, includes one or more processors and one or more memories connected to the one or more processors to be able to communicate with the one or more processors. The one or more processors is configured to execute a process including: obtaining information on a surrounding environment of the vehicle; obtaining information on an external environmental factor that may cause deviation of a drive track of the vehicle; and expanding a setting range of the risk potential of the risk object which is positioned in a direction of the expected deviation based on the information on the external environmental factor.