Autonomous Vehicle Path Prediction for Emergency Vehicle Evasion
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Solution Overview
Problem
Current autonomous vehicle systems face challenges in accurately predicting and responding to emergency vehicles on the road, as they need to rapidly change driving paths and modes to comply with traffic regulations, which is complex and requires advanced sensing and decision-making capabilities.
Innovation Solution
An autonomous vehicle path prediction system equipped with sensors and a processor that includes a determining module, path prediction module, emergency decision module, and control module, which senses multiple vehicles, determines the presence of emergency vehicles, performs emergency path predictions, and generates autonomous driving decisions to adjust the vehicle's path and mode accordingly, using V2X communication to comply with traffic regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle system performs emergency path prediction and adjusts driving paths when detecting emergency vehicles, then road safety and compliance with traffic laws are improved, but the system complexity and computational requirements increase
Solution Approach 1:
The autonomous vehicle system divides the path prediction task into separate modules: a first path prediction module for predicting paths of surrounding vehicles under normal conditions, and a second path prediction module for predicting paths when emergency vehicles are present. This segmentation allows each module to specialize in specific scenarios, improving reliability while managing system complexity through modular design.
Solution Approach 2:
The system performs preliminary detection of emergency vehicles using sensors before executing path adjustment maneuvers. The emergency determination module proactively identifies emergency vehicles and triggers the appropriate path prediction module in advance, allowing the system to prepare for emergency situations before they require immediate response, thereby improving safety without proportionally increasing complexity.
2Adaptability or versatility
If the autonomous vehicle rapidly changes driving paths and modes to give way to emergency vehicles, then compliance with traffic regulations is improved, but the response time and decision-making accuracy may be compromised
Solution Approach 1:
The system performs preliminary detection and classification of emergency vehicles using sensor data and communication modules before the actual path change is required. By identifying emergency vehicles in advance and pre-calculating potential path adjustments, the system reduces the critical response time when actual evasion maneuvers are needed, allowing compliance with traffic regulations without sacrificing response speed.
Solution Approach 2:
The system continuously monitors the environment using sensors and receives information from communication modules about emergency vehicles. This feedback loop allows the system to detect emergency situations, adjust paths, and verify the effectiveness of adjustments in real-time, ensuring rapid compliance while maintaining decision accuracy through continuous environmental awareness and adaptive response.
3Measurement precision
If the autonomous vehicle uses multiple sensors and V2X communication to detect emergency vehicles, then detection accuracy is improved, but the energy consumption and processing load increase
Solution Approach 1:
The system segments the detection process into multiple layers: basic sensor detection for all vehicles, enhanced detection modes for suspected emergency vehicles, and verification through V2X communication. This segmented approach allows the system to use high-precision detection methods selectively rather than continuously, improving detection accuracy for emergency vehicles while reducing overall energy consumption by activating intensive detection only when needed.
Solution Approach 2:
The system applies full detection resources (multiple sensors and V2X communication) partially - only when emergency vehicles are suspected or confirmed - rather than maintaining maximum detection intensity continuously. This partial application of excessive detection capability ensures high measurement precision for emergency situations while avoiding the prohibitive energy cost of continuous maximum-intensity sensing and communication.
Data Source
Figure 1
Figure 2A~2B
Figure 3A~3B
AI summary
An autonomous vehicle path prediction method (4) includes sensing vehicles driving on a road (2,3) and generating sensing signals corresponding to the vehicles; surrounding vehicles (22,32) and a current state of the emergency vehicle (23,33) and performing an emergency path prediction (22b,32b) corresponding to the emergency vehicle (23,33) when the vehicles further include the emergency vehicle (23,33); generating an emergency autonomous driving decision according to the emergency path prediction (22b,32b) and providing an autonomous vehicle path planning (21b,31b) corresponding to the emergency autonomous driving decision; and controlling the autonomous vehicle (21,31) to change the driving path and the driving mode on the road (2,3) according to the autonomous vehicle path planning (21b,31b).