Collision Avoidance via Superimposed Movement Profiles
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Solution Overview
Problem
Current methods for avoiding collisions in traffic scenarios, such as those using LIDAR and RADAR, struggle with predicting quickly changing behaviors due to lack of communication and exchange of information among participants, leading to unreliable and latency-prone solutions, and require each participant to carry systems like TCAS for safety assessment.
Innovation Solution
A method that assigns movement profiles to traffic participants, determines collision probabilities by superimposing their profiles, and uses edge computing for decentralized, real-time data processing to provide warnings, leveraging mobile devices and communication networks to enhance prediction and reaction time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LIDAR and RADAR are used for distance and speed measurements, then measurement precision is improved, but reliability deteriorates due to interference from aerosols and water content in air
Solution Approach 1:
The patent introduces communication networks as an intermediary to enable traffic participants to exchange information about their movement profiles and environmental conditions. This allows participants to share data that compensates for LIDAR/RADAR limitations, improving overall system reliability by combining multiple information sources rather than relying solely on direct sensing that is vulnerable to atmospheric interference
Solution Approach 2:
The system combines multiple functions into a unified approach: LIDAR/RADAR for direct measurement, communication networks for information exchange, and centralized servers for data integration. This multi-functional system addresses both the precision requirement (through LIDAR/RADAR) and reliability requirement (through redundant communication-based verification) simultaneously
2Adaptability or versatility
If decentralized long-range mobile radio solutions are used for networking traffic participants, then adaptability is improved, but loss of time increases due to data transmission to distant servers
Solution Approach 1:
The patent segments the data processing function by introducing edge computing nodes that are geographically distributed closer to traffic participants. This segmentation allows data to be processed at multiple levels: local devices handle immediate data collection, edge servers handle regional data integration and collision risk calculation, and centralized servers handle overall system coordination. This hierarchical segmentation reduces transmission distances and latencies while maintaining system adaptability
Solution Approach 2:
The patent adds a spatial dimension to the data processing architecture by deploying edge computing servers at multiple geographic locations rather than relying on a single centralized cloud server. This dimensional change from one-dimensional centralized processing to multi-dimensional distributed processing enables faster local response times while maintaining the adaptability benefits of decentralized communication
3Reliability
If each traffic participant carries TCAS and transponders for safety assessment, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent merges the collision avoidance functionality into existing mobile devices that traffic participants already carry, combining communication capabilities, positioning systems, and processing power into a single integrated platform. This eliminates the need for separate TCAS units and transponders, reducing device complexity while maintaining reliability through the enhanced networked information exchange capability
Solution Approach 2:
The system uses universal mobile devices with multiple functions (communication, positioning, processing) to perform collision avoidance tasks, rather than requiring specialized single-function TCAS equipment. This universal approach reduces overall system complexity by leveraging existing multi-functional hardware while achieving the same safety objectives through networked collaboration
Data Source
AI summary
A method for avoiding a collision between at least one first traffic participant and at least one second traffic participant. A first movement profile is assigned to the first traffic participant, a second movement profile is assigned to the second traffic participant, a first probability profile is generated from the first movement profile and a second probability profile is generated from the second movement profile, and the probability profile comprises information relating to the probability of the location of the respective traffic participant at a time in the future. A collision probability is determined in a mobile device by superimposing the first probability profile and the second probability profile. The probability profile is transmitted to at least one computing unit which superimposes at least the first probability profile of the first traffic participant with the second probability profile of the second traffic participant in order to determine the collision probability.