Zone Identification for Collision Avoidance
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Solution Overview
Problem
Current collision monitoring systems in environments with multiple vehicles and objects are ineffective due to reliance on operator vigilance, inaccurate magnetic field techniques, and high latency in software geofence systems, leading to potential collisions and lack of zone-based action responses.
Innovation Solution
A system using object and vehicle sensors to determine the distance and zone of an object relative to a vehicle, providing alerts or automatic actions based on configured zones to prevent collisions, with configurable zone settings and communication range adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If operator vigilance is used for collision monitoring, then the system is simple to implement, but the reliability of collision detection is insufficient
Solution Approach 1:
The patent replaces the mechanical human operator vigilance system with an automated sensor-based detection system. Vehicle sensors and object sensors electronically detect distances and calculate zones, substituting human visual monitoring and manual response with automated electronic sensing and algorithmic processing, thereby improving reliability while maintaining reasonable system complexity
Solution Approach 2:
The patent introduces intermediate computational elements (distance calculation algorithms, zone identification logic) that mediate between raw sensor data and collision detection decisions. These intermediaries process sensor signals to determine whether objects are in danger zones, providing a reliable automated decision-making layer between sensing and action
2Difficulty of detecting and measuring
If magnetic field techniques are used for collision monitoring, then the system can detect objects, but the measurement precision is inaccurate
Solution Approach 1:
The patent changes the physical parameter used for detection from magnetic field strength to electromagnetic signal time-of-flight or phase shift. By measuring the time for an electromagnetic signal to travel between vehicle and object sensors, or by analyzing phase differences in continuous waves, the system achieves precise distance measurements that are not attainable with magnetic field techniques
Solution Approach 2:
The patent substitutes magnetic field-based detection with electromagnetic wave-based detection. Instead of measuring disturbances in magnetic fields, the system uses electromagnetic signals (radio waves, microwaves) to precisely measure distances through time-of-flight or phase comparison, achieving superior measurement precision
3Adaptability or versatility
If software geofence systems are used for collision monitoring, then the system can define monitoring areas, but the response latency is high
Solution Approach 1:
The patent pre-calculates and pre-defines danger zones based on vehicle characteristics and operational parameters before collision risks arise. Zone boundaries and response thresholds are established in advance through algorithmic computation, allowing the system to immediately determine collision risk status without performing complex calculations during critical response moments, thereby reducing latency while maintaining adaptability
Solution Approach 2:
The patent implements dynamic zone adjustment where danger zone parameters are continuously updated based on real-time vehicle speed, load, and environmental conditions. The system transitions from static pre-programmed geofences to dynamically adapted zones that automatically adjust their boundaries and response criteria, providing both flexibility and rapid response through continuous real-time computation
4Reliability
If zone-based automatic actions are implemented, then the collision prevention effectiveness is improved, but the device complexity increases
Solution Approach 1:
The patent segments the operational space into distinct zones (safe zone, danger zone, critical zone) with progressively stricter response requirements. Each zone has predefined detection thresholds and associated automatic actions, breaking down the complex collision prevention task into manageable segmented regions with simple binary decision logic, thereby improving effectiveness without excessive complexity
Solution Approach 2:
The patent applies different detection sensitivities and response strategies to different spatial zones. Rather than using a uniform high-complexity system throughout all space, the system employs localized quality adjustments where only regions requiring intervention have active automatic responses, reducing overall system complexity while maintaining high collision prevention effectiveness in critical areas
Data Source
AI summary
One embodiment provides a method, including: receiving data indicating an object sensor associated with an object is within communication range of a vehicle sensor associated with a vehicle; determining, using a distance calculation algorithm, a distance between the object sensor and the vehicle sensor; identifying a zone, from a plurality of zones that are based upon distances from the vehicle sensor, associated with the determined distance between the object sensor and the vehicle sensor; and providing, based upon the identified zone, an output comprising an indication of the identified zone corresponding to a location of the object sensor. Other aspects are described and claimed.