Guided Soft Target for Crash Avoidance Testing
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Solution Overview
Problem
Current crash avoidance technology testing methods face challenges in replicating realistic crash scenarios while minimizing hazards and equipment damage, and in providing a consistent radar and sensor signature for various collision types, especially at high speeds.
Innovation Solution
A Guided Soft Target system comprising a soft target vehicle or pedestrian form attached to a programmable, autonomously guided Dynamic Motion Element, which can replicate pre-crash motions and follow predetermined trajectories, ensuring realistic and safe collision scenarios with consistent sensor signatures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a rigid target vehicle is used to simulate real vehicles, then the sensor signature consistency is improved, but the physical risk to test personnel and damage to equipment increases
Solution Approach 1:
The patent applies a soft, flexible outer shell or skin covering the target vehicle structure. This flexible covering maintains the external geometry and radar cross-section similar to a real vehicle, ensuring consistent sensor signatures, while being compliant enough to reduce impact forces and physical risk during collisions.
Solution Approach 2:
The target vehicle employs composite construction combining rigid internal framework with soft external materials. This composite structure preserves the geometric shape and sensor signature characteristics of real vehicles while using energy-absorbing materials to minimize physical risk and damage during impact.
2Object-affected harmful factors
If a soft target is used to minimize physical risk, then the safety is improved, but the sensor signature consistency deteriorates
Solution Approach 1:
The patent uses a carefully engineered flexible outer shell that maintains the target vehicle's external geometry and radar cross-section. This shell is designed to be compliant for safety while preserving the geometric fidelity needed for consistent sensor signatures across different collision scenarios.
Solution Approach 2:
The patent adjusts physical parameters of the soft target materials, such as density, elasticity, and surface texture, to optimize the balance between safety and sensor signature consistency. By controlling these parameters, the target maintains realistic radar and sensor characteristics while minimizing physical risk.
3Weight of moving object
If a heavy target vehicle is used to simulate real-world mass, then the collision realism is improved, but the ease of repositioning and reusability deteriorates
Solution Approach 1:
The target vehicle is divided into modular segments or components that can be easily disconnected and repositioned. This segmentation allows the target to be quickly moved between test locations and reused for multiple collision scenarios without requiring heavy equipment for repositioning.
Solution Approach 2:
The patent employs dynamic positioning systems such as electric motors, hydraulic actuators, or electric scooters to automatically reposition the target vehicle between tests. This dynamic repositioning capability allows the target to be moved easily despite its mass, improving reusability and operational efficiency.
4Adaptability or versatility
If a complex guided motion system is added to replicate pre-crash motions, then the test scenario realism is improved, but the device complexity increases
Solution Approach 1:
The guided motion system is designed with multi-functionality to perform multiple operations: positioning the target vehicle, replicating pre-crash motions, and coordinating with subject vehicles. By consolidating these functions into a single integrated system, the patent reduces overall complexity while maintaining comprehensive test scenario replication capability.
Solution Approach 2:
The patent introduces a centralized control system or coordinator that acts as an intermediary between the guided motion system and subject vehicles. This mediator manages the complex coordination required for realistic crash scenarios, simplifying the control architecture by centralizing the decision-making and communication functions.
Data Source
AI summary
A Guided Soft Target (GST) system and method provides a versatile test system and methodology for the evaluation of various crash avoidance technologies. This system and method can be used to replicate the pre-crash motions of the CP in a wide variety of crash scenarios while minimizing physical risk, all while consistently providing radar and other sensor signatures substantially identical to that of the item being simulated. The GST system in various example embodiments may comprise a soft target vehicle or pedestrian form removably attached to a programmable, autonomously guided, self-propelled Dynamic Motion Element (DME), which may be operated in connection with a wireless computer network operating on a plurality of complimentary communication networks. Specific DME geometries are provided to minimize ride disturbance and observability by radar and other sensors. Computer controlled DME braking systems are disclosed as well as break-away and retractable antenna systems.