Autonomous Vehicle Digital Twin Testing and Homologation Standards

Yoshiaki Shoi (ASAM)

In the testing and homologation of automated vehicles, the adoption of a “digital twin” methodology—integrating real-world driving with simulation—is steadily advancing. This paper presents a comprehensive overview of the ASAM OpenX suite of standards, which is fundamental to implementing this methodology, outlining their objectives, expected impacts, and projected developments. Furthermore, the paper examines the underlying approaches to standardization that were developed in conjunction with these specifications.

Consistency Evaluation System for ADAS ECU and Meter Display

Hiroyuki Takano (Nissan Motor)･ANHTUAN NGO･DUCPHONG NGUYEN (Nissan Automotive Technology Viet Nam)･Tomohiro Kida (Fudo Giken Industry)･Daisuke Maruta (Accenture Japan)･Shigenori Tsunekado (Nissan Motor)

We developed an HIL system that automatically evaluates the consistency between ADAS ECU signals and meter displays. Icon images captured by a camera are recognized through image recognition and compared/judged in synchronization with the ECU signals. By converting the diverse and complex meter displays into signals and synchronizing them with the ECU signals for comparison, the evaluation process was simplified. This system was introduced into the vehicle verification process, where it was evaluated and contributed to reducing test man-hours.

A Comprehensive Pipeline for Scenario Extraction from Open-Road Data for ADS Validation

Marc Perez･Marc Facerias (Applus+ IDIADA)

As automated driving systems (ADS) become increasingly complex, traditional testing methods are no longer sufficient to capture the full variability of real-world traffic. This study presents a comprehensive pipeline for extracting scenarios from open-road data, encompassing data acquisition, perception, scenario identification, and the generation of scenario files compliant with ASAM OpenX standards. The pipeline was evaluated across two data-collection campaigns, allowing to validate the proposed approaches and generate preliminary results. These results serve as an initial contribution toward the development of a harmonized European scenario data space, supporting more robust scenario-based ADS validation.

Physically Replicated Weather Conditions to Evaluate Camera, Radar, and Lidar Object Detection in Automotive Scenarios

Marc Perez (Applus+ IDIADA)

Adverse weather conditions are one of the biggest challenges for large-scale automated driving deployment, due to reduced perception performance. We analyse how rain, fog, and snow affect object detection on cameras, lidars, and radars. We provide experimental results in proving grounds, open road and an enclosed facility with physically replicated controllable rain, fog, and lighting. We report perception and weather metrics, and we discuss some artifacts visible in the point clouds of physically replicated rain, providing actionable insights for the design and operation of future facilities for physically replicating weather conditions.

Integrity of Vehicle Localization for Highly Automated Driving

Robin Smit･Emilia Silvas･Saarang Gaggar (Netherlands Organisation for Applied Scientific Research (TNO))

As automated driving advances from partial automation (SAE Level 2) to high automation (Level 4), the reliability and integrity of vehicle localization systems become increasingly critical. Accurate localization is essential for amongst others safe trajectory planning. Establishing robust upper bounds on localization errors is vital to ensure safety. This involves calculating probabilistic error limits that align with predefined risk thresholds. This presentation reviews the current state of integrity monitoring for vehicle localization in automated driving, highlights ongoing challenges and recent advancements, and outlines future research directions to support the safe deployment of highly automated vehicles.

A Study on Applying ISO 21448 (SOTIF) to a Hypothetical Level 4 Automated Mobility Service

Miharu Oiwa･Yoshihiro Miyazaki･Kazuyoshi Fukuda (JARI)

Currently, there are no publicly available case studies on applying ISO 21448 (SOTIF) to Level 4 automated mobility services, making knowledge sharing difficult. Therefore, this paper presents a case study of applying ISO 21448 (SOTIF) to a hypothetical Level 4 automated mobility service, aiming to provide practical insights to the industry.