Roadside Equipment Selection for Active Safety
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Solution Overview
Problem
Current systems for automated vehicles lack efficient methods to select the most relevant road-side equipment (RSE) for communication, leading to potential data saturation and reduced safety in congested traffic areas, where vehicles may receive data from multiple RSEs with varying levels of relevance and security validation.
Innovation Solution
The system employs methods to select the RSE of interest based on relative geometric data, vehicle dynamics, and security validation, including filtering, duplicate detection, and ordering RSEs based on relevance, using techniques such as range and cross-range calculations, and security certificate validation to ensure efficient and secure communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles receive data from multiple RSEs in congested traffic areas, then data coverage is improved, but data processing burden and system complexity increase
Solution Approach 1:
The patent segments the RSE data selection process into multiple filtering stages: initial reception of data from multiple RSEs, followed by sequential filtering based on geometric relevance, security validation, and duplicate detection. This segmentation allows the system to manage multiple data sources without overwhelming processing complexity at any single stage.
Solution Approach 2:
The system performs preliminary filtering and validation of RSE data before full processing. By pre-screening RSEs based on geometric criteria and security certificates before integrating their data, the system reduces the processing burden while maintaining comprehensive data coverage from multiple sources.
2Measurement precision
If RSEs are selected based on geometric relevance, then data accuracy is improved, but calculation complexity increases
Solution Approach 1:
The patent applies local quality by calculating geometric relevance specifically for RSEs in the vicinity of the host vehicle. Instead of uniform complex calculations for all RSEs, the system focuses detailed geometric analysis only on locally relevant RSEs, thereby improving data accuracy for critical areas while reducing overall calculation complexity.
Solution Approach 2:
The system changes parameters dynamically by adjusting the geometric calculation precision based on distance and relevance. For distant or less relevant RSEs, simplified geometric criteria are used, while for nearby critical RSEs, more precise calculations are applied, optimizing the balance between accuracy and computational load.
3Reliability
If security validation is performed on all RSE data, then system security is improved, but processing time increases
Solution Approach 1:
Security validation is performed as a preliminary filtering step before full data integration. By validating security certificates early in the RSE selection process, the system ensures security for all incorporated data while minimizing the time impact by not performing full validation on every single RSE data packet, but rather on the RSEs themselves.
Solution Approach 2:
RSEs provide self-validation through embedded security certificates that allow the host vehicle to quickly verify authenticity without requiring extensive external validation processes. This self-service approach to security validation reduces processing time while maintaining system security.
Data Source
AI summary
In one example, we describe a method and infrastructure for DSRC V2X (vehicle to infrastructure plus vehicle) system. In one example, some of connected vehicle applications require data from infrastructure road side equipment (RSE). Examples of such applications are road intersection safety application which mostly requires map and traffic signal phase data to perform the appropriate threat assessment. The examples given cover different dimensions of the above issue: (1) It provides methods of RSE of interest selection based solely on the derived relative geometric data between the host vehicle and the RSE's, in addition to some of the host vehicle data, such as heading. (2) It provides methods of RSE of interest selection when detailed map data is communicated or when some generic map data is available. (3) It provides methods of RSE of interest selection when other vehicles data is available. Other variations and cases are also given.