Autonomous Vehicle Threat Detection and Relocation
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Solution Overview
Problem
Existing methods for autonomous vehicles fail to effectively and autonomously handle threatening situations, such as persistent threats near parked vehicles, leading to potential safety risks and inefficiencies in threat recognition and response.
Innovation Solution
A method and device that utilize onboard sensors and cameras to detect the presence of threats, determine vehicle parking states, and autonomously drive the vehicle to a safe location, such as a well-lit area, while using AI-powered image recognition to differentiate between threats and authorized individuals, and alert authorities through audible and silent alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous threat handling is implemented, then vehicle safety is improved, but system complexity increases
Solution Approach 1:
The autonomous threat handling system is divided into distinct functional modules: sensor module for detecting motion and capturing images, processing module for analyzing images and determining threats, and response module for executing autonomous responses. This segmentation manages system complexity by organizing functions into separate, manageable components while maintaining overall safety effectiveness.
2Measurement precision
If AI-powered image recognition is used to differentiate threats, then measurement precision is improved, but computing requirements and energy consumption increase
Solution Approach 1:
The system applies AI-powered image recognition selectively rather than continuously - images are captured and analyzed only when motion is detected in the surrounding space. This partial action approach maintains high threat recognition accuracy when needed while significantly reducing computing energy consumption during normal parking periods without threats.
Solution Approach 2:
The system performs preliminary motion detection using sensors before triggering the more computationally intensive AI image recognition. This preliminary action filters out unnecessary processing by only activating the energy-consuming AI recognition when motion is detected, thereby reducing overall energy consumption while maintaining precision when threats are present.
3Reliability
If continuous monitoring is performed to detect persisting threats, then reliability is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic monitoring by capturing images during specific time periods when motion is detected, rather than continuous monitoring. The system monitors for motion continuously but only activates image capture and analysis during detected motion events, creating a periodic action pattern that maintains threat detection reliability while significantly reducing energy consumption compared to continuous operation.
Data Source
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AI summary
A device and a method of operating a vehicle comprising detecting (101) a presence or an absence of an occupant inside the vehicle, determining (102) a vehicle parking state, detecting (103), a motion in a space surrounding the vehicle within a predetermined distance of the vehicle, capturing (104) at least one image of at least a part of the space surrounding the vehicle, detecting (105) from the at least one image a presence of a thread to the vehicle, determining (106) a reaction of the vehicle depending on the detected thread, starting (107) the determined response autonomously in case of absence of any occupant inside the vehicle and when the vehicle is in a vehicle parking state.