Map Information Generation for Emergency Areas
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Solution Overview
Problem
Current digital road maps lack the accuracy and timeliness to depict safe locations such as emergency bays and areas outside the road, which are crucial for highly automated or autonomous driving, especially in construction sites and temporary setups, and existing sensor systems cannot capture these locations with sufficient precision in real time for driving maneuvers.
Innovation Solution
A system that generates map information by processing data sets from multiple vehicles, including images from cameras, radar, and lidar, to categorize and identify suitable areas outside the immediate road space for minimal risk maneuvers, using a computer program that evaluates and updates this information in real-time for digital road maps and eHorizon systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current digital road maps are used, then basic road information is available, but safe locations such as emergency bays and areas outside the road cannot be depicted with sufficient accuracy and timeliness
Solution Approach 1:
The system performs preliminary detection and categorization of emergency areas using sensor data from multiple vehicles before they are needed for minimal risk maneuvers. This advance preparation ensures that when an emergency situation arises, the information is already available and categorized for immediate use, resolving the contradiction between accuracy and timeliness.
Solution Approach 2:
The system enables vehicles to contribute their own sensor data to the collective knowledge base of emergency areas. Each vehicle's sensors detect and report emergency areas, which are then processed and made available to all vehicles in the network, eliminating the need for dedicated mapping infrastructure while improving both accuracy and timeliness.
2Measurement precision
If existing sensor systems are used, then real-time data can be captured, but sufficient precision for capturing safe locations cannot be achieved
Solution Approach 1:
The system merges data from multiple sensor systems (cameras, radar, lidar) and multiple vehicle sources to achieve the precision required for safe location capture. By combining redundant measurements from different sensors and vehicles, the system achieves high precision while maintaining real-time capture capability through parallel data collection.
Solution Approach 2:
The system creates multiple copies of the same physical reality through redundant sensor measurements from different vehicles and sensor types. This copying approach allows for cross-validation and precision improvement without sacrificing real-time capture, as multiple copies are generated simultaneously through the distributed sensor network.
3Reliability
If data from multiple vehicles is processed, then comprehensive and up-to-date map information is generated, but processing complexity increases
Solution Approach 1:
The system segments the data processing task by assigning different functions to different components: individual vehicles perform initial data collection and filtering, edge servers perform local aggregation and preprocessing, and central servers perform final integration and map updating. This segmentation reduces the processing burden on any single component while maintaining comprehensive information quality.
Solution Approach 2:
The system introduces intermediary processing layers (edge servers and communication protocols) between the vehicles and the central map database. These intermediaries filter, aggregate, and pre-process data from multiple vehicles before transmission to the central system, reducing communication overhead and processing complexity while maintaining data comprehensiveness and reliability.
Data Source
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AI summary
The invention relates to a system for generating map information for one or more roadway sections of a digital roadway map, comprising an interface (208) for receiving (102) data sets for the one or more roadway sections. The data sets describe properties of surfaces (402; 602) outside of the immediate roadway area (404; 604; 704). The system further comprises a first module for evaluating (104) the received data sets in order to identify surfaces outside of the immediate roadway area which are traversable by a vehicle after leaving the roadway and on which the vehicle can be brought to a stop after leaving the roadway, a second module for generating (108) a description of the first surfaces in a format which is suitable for digital roadway maps, and a third module for providing (110) the description of the first surfaces in one or more formats which are suitable for digital roadway maps in a retrievable manner.