Vehicle Surroundings Monitoring for Collision Probability Guidance
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Solution Overview
Problem
Existing vehicle monitoring systems, particularly for agricultural machines with trailers, struggle to effectively assess collision risks in areas with poor visibility or complex traffic situations, failing to provide adequate assistance to drivers.
Innovation Solution
A system and method utilizing sensors and displays to determine collision probabilities by evaluating vehicle and object parameters, providing visual and acoustic warnings based on collision risk levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If purely imaging methods are used for monitoring, then the system complexity is low, but the measurement precision and reliability of collision risk assessment deteriorates in areas with poor visibility
Solution Approach 1:
The patent combines multiple sensor types (imaging sensors, radar, ultrasonic sensors, LIDAR) into a hybrid monitoring system. This merging of different sensing technologies allows the system to overcome the limitations of purely imaging methods in poor visibility conditions while maintaining manageable system complexity through integrated processing.
Solution Approach 2:
The monitoring system is designed to perform multiple functions: detecting objects, assessing collision risk, and providing warnings. By making the system multi-functional and capable of operating across different environmental conditions, it achieves high measurement precision without requiring separate specialized systems for each condition.
2Measurement precision
If multiple sensor devices are integrated to improve detection accuracy, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent segments the monitoring system into distinct functional modules: imaging sensors for visual detection, radar for distance and velocity measurement, ultrasonic sensors for close-range detection, and LIDAR for precise positioning. Each sensor type handles specific detection tasks, and the evaluation device integrates their data. This segmentation allows high measurement precision while managing device complexity through modular architecture.
3Reliability
If comprehensive vehicle and object parameters are evaluated to determine collision probability, then the reliability of collision risk assessment improves, but the computational requirements and device complexity increase
Solution Approach 1:
The evaluation device continuously monitors vehicle movement parameters, object parameters, and environmental conditions, then dynamically updates the collision probability assessment. This feedback mechanism uses real-time data from multiple sensors to reliably determine collision risk while managing computational complexity through iterative processing rather than exhaustive calculation.
Solution Approach 2:
The system evaluates multiple parameters including vehicle speed, acceleration, object position, object speed, and environmental conditions. By systematically changing and evaluating these parameters, the system achieves high reliability in collision risk assessment. The evaluation device processes these parameter changes efficiently by focusing on the most critical factors for collision probability.
Data Source
AI summary
The present invention provides a method for monitoring the surroundings of a vehicle (F) comprising sensing (S1) an object (O) in the surroundings of the vehicle (F) by means of at least one sensor device (S); determining (S2) a probability of a collision of the vehicle (F) with the object (O) by means of an evaluation device on the basis of sensor data of the sensor device (S), wherein at least one movement parameter (BP-F) of the vehicle (F), at least one vehicle parameter (FP) and at least one movement parameter (BP-O) of the object (O) are taken into account; and displaying (S3) a recommendation for the vehicle (F) to drive on or to stop in accordance with the determined probability of a collision on a display device (D).