Layered Cost Map Containers for ITS Collective Perception
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Solution Overview
Problem
Existing Collective Perception Service (CPS) specifications are inefficient in scenarios with a large number of objects, overlapping views, or occlusions, as they require reporting each perceived object individually, leading to high communication overhead and computational challenges.
Innovation Solution
The enhancement of the CPS includes the use of Layered Cost Map (LCM) containers in Collective Perception Messages (CPMs) to share the perceived environment in a more efficient manner, allowing for the reporting of VRUs and VRU clusters as separate cost map layers, and enabling collaboration requests and discrepancy handling among neighboring ITS-Ss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If individual object reporting is used in CPS, then complete perception information is provided, but communication overhead increases and computational efficiency decreases
Solution Approach 1:
The patent merges multiple individual object reports into a single Layered Cost Map (LCM) data structure. Instead of transmitting separate messages for each perceived object, the system consolidates all perception data into a unified cost map representation where spatial locations and object attributes are encoded in a compact grid format, significantly reducing communication overhead while preserving complete perception information.
Solution Approach 2:
The patent segments the perception environment into discrete cost map layers representing different object types (e.g., VRUs, vehicles, obstacles). Each layer contains cost values for grid cells corresponding to specific object categories, allowing selective transmission and processing of relevant perception data while maintaining information completeness.
2Loss of information
If individual object reporting is used in CPS, then complete perception information is provided, but communication overhead increases
Solution Approach 1:
The patent merges multiple individual object reports into a single Layered Cost Map (LCM) data structure. Instead of transmitting separate messages for each perceived object, the system consolidates all perception data into a unified cost map representation where spatial locations and object attributes are encoded in a compact grid format, significantly reducing communication overhead while preserving complete perception information.
Solution Approach 2:
The patent changes the representation parameters from individual object attributes to spatial cost map grids. By encoding perception data as cost values in a regular grid structure rather than as discrete object records, the system achieves more compact data representation that scales efficiently with the number of perceived objects, reducing communication overhead while maintaining information completeness.
3Measurement precision
If detailed individual object data is transmitted, then perception accuracy is improved, but message size increases
Solution Approach 1:
The patent changes the representation parameters from individual object attributes to spatial cost map grids. By encoding perception data as cost values in a regular grid structure rather than as discrete object records, the system achieves more compact data representation that scales efficiently with the number of perceived objects, reducing communication overhead while maintaining information completeness.
Data Source
AI summary
The present disclosure is related to Intelligent Transport Systems (ITS), and in particular, to service dissemination basic services (SDBS) and/or collective perception service (CPS) of an ITS Station (ITS-S). Implementations of how the SDBS and/or CPS is arranged within the facilities layer of an ITS-S, different conditions for service dissemination messages (SDMs) and/or collective perception message (CPM) dissemination, and format and coding rules of the SDM/CPS generation are provided.