Vehicle Travel Assistance Using Predicted Encounter Risk Potentials
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Solution Overview
Problem
Existing vehicle travel assistance systems cannot effectively avoid risks that may arise before detecting surrounding objects, as they rely on actualized risk maps rather than predicted risk potentials.
Innovation Solution
The system calculates a primary estimated risk potential by accumulating risk data at encounter locations and uses a secondary estimated risk potential, derived from predicted travel movements of other vehicles that avoid risks, to autonomously control vehicle travel and anticipate potential hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system uses actualized risk maps based on detected traffic participants, then the travel assistance can be performed for detected objects, but it cannot perform travel assistance to avoid risks that may arise before detection
Solution Approach 1:
The system performs preliminary risk assessment by calculating risk potentials for multiple future encounter locations ahead of the vehicle's current position. This allows the vehicle to identify and avoid potential risks before actually encountering detected objects, enabling proactive rather than reactive travel assistance.
Solution Approach 2:
The system calculates primary and secondary estimated risk potentials to predict and counteract potential risks before they materialize. By anticipating where risks may arise based on object trajectories and vehicle behavior patterns, the system can plan alternative routes or speed adjustments in advance.
2Reliability
If the system calculates risk potential for multiple encounter locations ahead, then proactive risk avoidance is enabled, but the calculation complexity and processing time increase
Solution Approach 1:
The risk calculation process is segmented into distinct stages: first calculating risk potentials for multiple encounter locations, then selectively calculating primary estimated risk potentials only for locations with high risk potential, and finally calculating secondary estimated risk potentials only for remaining high-risk locations. This hierarchical segmentation reduces overall computational complexity.
Solution Approach 2:
The system applies different levels of risk calculation intensity to different spatial locations based on their risk potential. High-risk locations receive more detailed analysis (primary and secondary estimated risk potentials), while low-risk locations receive minimal or no calculation, optimizing resource allocation.
3Measurement precision
If the system performs detailed risk calculations for all encounter locations, then comprehensive risk assessment is achieved, but processing speed and efficiency decrease
Solution Approach 1:
The system performs partial risk calculations by first evaluating all encounter locations with basic risk potential assessment, then performing more detailed primary and secondary estimated risk potential calculations only for a subset of high-risk locations. This selective approach maintains sufficient precision for critical risks while improving overall processing speed.
Data Source
AI summary
A travel assistance method and a travel assistance device for a vehicle is capable of avoiding any risk that may arise. The method includes obtaining a risk potential of an object detected by the vehicle, associating the risk potential of the object with an encounter location at which the object is encountered, accumulating the risk potential at the encounter location, and using the accumulated risk potential to obtain a primary estimated risk potential of the object predicted to be encountered at the encounter location. The primary estimated risk potential is lower than the risk potential obtained when detecting the object. The method further includes obtaining a secondary estimated risk potential using a predicted travel movement of another vehicle that avoids a risk due to the primary estimated risk potential, and when traveling at the encounter location again, autonomously controlling travel of the vehicle using the secondary estimated risk potential.