Critical Location Mapping for Targeted ADS Shadow Testing

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Solution Overview

Problem

Existing shadow mode testing for autonomous driving systems in production vehicles is inefficient and resource-intensive, particularly when evaluating multiple candidate software simultaneously, as it often fails to expose the software to crucial and challenging driving situations, and route planning based on historical data may not adequately identify critical locations for testing.

Innovation Solution

A locations mapping system that identifies and maps critical and challenging locations by analyzing past vehicle situations, extracting geo-tagged data from accidentology and vehicle performance databases, and matching these locations with similar road segments in digital maps, enabling a scaled-up mapping for targeted shadow mode testing and real-time vehicle rerouting.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If shadow mode testing is run continuously in production vehicles, then software performance can be evaluated, but computational power and resources are wasted on normal operating conditions that do not expose challenging situations

Engineering Contradiction:
Improvesoftware development efficiencyVSAvoidcomputational resource waste
Core Design Contradiction:
ProductivityVSLoss of energy

Solution Approach 1:

The system pre-identifies and stores challenging locations in advance using historical data and accidentology databases. These locations are prepared beforehand and made available for targeted testing, eliminating the need for continuous random shadow mode testing and reducing computational waste during normal operations

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system changes the operational parameter from continuous shadow mode testing to event-triggered testing based on location identification. By monitoring whether the vehicle is approaching a pre-identified challenging location, the system activates testing only when necessary, optimizing resource utilization

Inventive Principle:
Principle #35Parameter changes

2Reliability

If multiple candidate software are evaluated simultaneously, then comprehensive testing coverage is achieved, but onboard computational power requirements increase significantly

Engineering Contradiction:
Improvetesting coverageVSAvoidcomputational power requirements
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The system extracts and separates the location identification function from the software evaluation process. By pre-identifying challenging locations independently of the candidate software being tested, the system reduces the computational burden during simultaneous multi-software evaluation while maintaining comprehensive testing coverage

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The testing process is segmented into two independent parts: location identification (done once using historical data) and software evaluation (done continuously on identified locations). This segmentation allows multiple candidate software to be evaluated simultaneously without compounding computational requirements

Inventive Principle:
Principle #1Segmentation

3Productivity

If route planning is based on historical crucial locations, then testing focuses on relevant scenarios, but the system cannot identify new or emerging challenging situations

Engineering Contradiction:
Improvetesting effectivenessVSAvoidability to detect new challenging situations
Core Design Contradiction:
ProductivityVSAdaptability or versatility

Solution Approach 1:

The system incorporates feedback loops where shadow mode testing results and new challenging situations are fed back into the location database. This continuous feedback mechanism allows the system to update and expand its knowledge of challenging locations, enabling it to adapt to new scenarios while maintaining focus on proven critical areas

Inventive Principle:
Principle #23Feedback

Data Source

PatentEP4303537B1Identifying locations crucial to an autonomous vehicle
Publication Date: 2025.11.19 ZENSEACT AB
  • EP4303537B1 patent drawingFigure 1
  • EP4303537B1 patent drawingFigure 2
  • EP4303537B1 patent drawingFigure 3

AI summary

The present disclosure relates to a method performed by a locations mapping system (1) for supporting identifying locations crucial to a vehicle (2) equipped with an Automated Driving System, ADS (21). The locations mapping system obtains (1001) data of crucial locations (3) of past vehicle situations identified as critical and/or challenging; extracts (1002) from the crucial locations data, for at least a first past vehicle situation, static road features and operating conditions pertaining to the at least first past vehicle situation; identifies (1004) road segments (4) , e.g. of an ADS-compliant digital map, exhibiting road features to a predeterminable extent matching the static road features pertaining to the at least first past vehicle situation; and generates (1005) a mapping (40) associating the identified road segments with said operating conditions. The disclosure also relates to a locations mapping system in accordance with the foregoing, an arrangement - for instance an offboard system (112) and/or a vehicle comprising such a locations mapping system, and a respective corresponding computer program product and non-volatile computer readable storage medium.