Autonomous Vehicle Safety System with Bladder Impact Mitigation
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Solution Overview
Problem
Autonomous vehicles face challenges in implementing effective active safety systems to prevent collisions with other vehicles and pedestrians, particularly due to unpredictable behaviors of human-driven vehicles and pedestrians, which can lead to potential rear-end collisions.
Innovation Solution
The implementation of a safety system in autonomous vehicles that utilizes sensors to detect potential collisions, classifies objects, predicts their trajectories, and activates safety measures such as altering the vehicle's trajectory, deploying acoustic and visual alerts, and using bladder systems to mitigate impacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle relies solely on standard autonomous navigation systems, then the system complexity is low, but the collision prevention capability is insufficient due to unpredictable human-driven vehicle behaviors
Solution Approach 1:
The safety system is segmented into multiple independent components: sensor suite for detection, object classification module for identification, trajectory prediction module for forecasting, and multiple alert systems (acoustic, visual) for communication. Each component operates semi-independently to provide comprehensive safety functionality without requiring complete system redesign
Solution Approach 2:
The sensor suite serves multiple functions: detecting objects, classifying them, tracking trajectories, and providing data to both navigation and safety systems. The acoustic alert system can communicate with both pedestrians and other drivers, while the bladder system provides both cushioning and structural protection, making the safety system versatile and efficient
2Reliability
If the vehicle activates multiple safety measures (acoustic alerts, visual alerts, trajectory changes), then collision prevention effectiveness increases, but the response time and system reaction complexity increase
Solution Approach 1:
The system performs preliminary classification of detected objects into categories (pedestrians, vehicles, cyclists) with predetermined response protocols. Trajectory predictions are continuously updated in advance, and alert thresholds are pre-established, allowing the system to execute appropriate safety measures immediately when conditions are met, without deliberation delay
Solution Approach 2:
The system dynamically adjusts the combination and intensity of safety measures based on real-time conditions. For example, it may start with acoustic alerts for low-risk situations, escalate to visual alerts or trajectory changes for moderate risks, and combine multiple measures for high-risk scenarios. The bladder system inflates dynamically based on predicted impact severity, optimizing response effectiveness while minimizing unnecessary activation
Data Source
AI summary
Systems and methods implemented in algorithms, software, firmware, logic, or circuitry may be configured to process data and sensory input to determine whether an object external to an autonomous vehicle (e.g., another vehicle, a pedestrian, road debris, a bicyclist, etc.) may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may be configured to implement active safety measures to avoid the potential collision and/or mitigate the impact of an actual collision to passengers in the autonomous vehicle and/or to the autonomous vehicle itself. Interior safety systems, exterior safety systems, a drive system or some combination of those systems may be activated to implement active safety measures in the autonomous vehicle.