Emergency Evacuation Parking Using Blind Spot Inference
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Solution Overview
Problem
Existing emergency evacuation devices for vehicles with autonomous driving functions do not adequately address the risk of secondary accidents caused by parking in static or dynamic blind spots, which can lead to collisions with following vehicles or rescuers during emergency stops.
Innovation Solution
An emergency evacuation device that uses a first blind spot inference model to determine a safe parking position by processing road geometry and traveling environment information, preventing the vehicle from entering static or dynamic blind spots by integrating road geometry information and traveling environment information to identify blind spot areas and determine a safe parking position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle evacuates to a parking position determined only by road geometry, then the evacuation process is simple and fast, but the vehicle may park in a static blind spot causing secondary accidents
Solution Approach 1:
The system performs preliminary blind spot detection and evaluation before finalizing the parking position. The processing circuitry predicts potential blind spots based on road geometry and traveling environment information, then adjusts the parking position in advance to avoid these areas, ensuring safety before the vehicle actually parks.
Solution Approach 2:
The blind spot detection is divided into two independent modules: static blind spot detection based on road geometry and dynamic blind spot detection based on traveling environment. This segmentation allows the system to handle different types of blind spots separately while maintaining overall system reliability without excessive complexity.
2Measurement precision
If the vehicle uses a comprehensive blind spot inference model considering both road geometry and traveling environment, then the accuracy of blind spot detection is improved, but the processing time and computational load increase
Solution Approach 1:
The system performs preliminary analysis of road geometry and traveling environment data before the emergency evacuation occurs. By pre-processing and storing this information, the system reduces the computational burden during the actual emergency response, enabling fast and accurate blind spot identification when needed.
Solution Approach 2:
The patent introduces a server device as an intermediary that receives road geometry information and traveling environment information, processes this data to generate blind spot information, and provides it to the emergency evacuation device. This intermediary approach distributes computational load and enables complex analysis without overwhelming the vehicle's onboard processing systems.
3Adaptability or versatility
If the system only detects static blind spots based on road geometry, then the system complexity is low, but dynamic blind spots caused by parked vehicles or other obstacles are not detected
Solution Approach 1:
The blind spot inference model is designed to handle multiple types of blind spots through a unified approach. By accepting both road geometry information (for static blind spots) and traveling environment information (for dynamic blind spots) as inputs, the model provides a universal solution that adapts to different scenarios without requiring separate detection systems.
Solution Approach 2:
The system segments blind spot detection into static components (based on road geometry) and dynamic components (based on traveling environment). This segmentation allows each component to be processed independently with appropriate complexity, then combined to provide comprehensive blind spot coverage.
Data Source
AI summary
A first blind spot information acquisition unit inputs road geometry information and traveling environment information which are acquired by an information acquisition unit to a first blind spot inference model, and thereby acquires, using the first blind spot inference model, first blind spot information indicating a blind spot area of a road along which a vehicle is traveling, the first blind spot inference model being configured to output first blind spot information indicating a blind spot area of a road when receiving road geometry information about geometry of the road and traveling environment information about a traveling environment of the road. A parking position determination unit determines a parking position of the vehicle by using the first blind spot information acquired by the first blind spot information acquisition unit.