Preliminary Conference Program

Issues, strategies and innovations driving and shaping the development and deployment of ADAS and AV technologies

SUNRISE: the afety assurance framework for connected and automated mobility systems

Stefan de Vries
Project manager connected and automated vehicles
Applus Idiada
Safety assurance of cooperative, connected and automated mobility (CCAM) systems is a crucial factor for their successful adoption and deployment in society. But the wide variety of individual initiatives in this field tends to silo solutions and hamper the large-scale and safe introduction of CCAM systems in our society. It is for these reasons that the SUNRISE project has been initiated. Halfway through this project, a draft version of the safety assurance framework has recently been completed, on which international vehicle safety bodies and individual CCAM experts are now invited to provide their feedback.

Deploying a safe and trustworthy AV in different markets

Vivetha Natterjee
Autonomous vehicle safety specialist
Now that we have removed the human from the vehicle has the AV become safer in traffic? No. We have removed the human and not the human element. But wait, is removing the human the solution? No. In fact the opposite is true, more the merrier. In Vivetha's multi-pillared approach to continuously improve and deploy safe and trustworthy autonomous vehicles, 'inclusion is key'. Data, verification and personas need to be weighed equally. Humans in our different roles (as engineers, as drivers, as traffic inspectors etc.) are to be modelled using AI in order to understand and prove safety of AV.

Are ADAS functions ready for the real world?

Dalia Broggi
Project Manager
European Commission
Ensuring automotive safety requires a shift from standard type-approval tests to comprehensive evaluations. This study compares traditional tests with real-world assessments by the Joint Research Centre (JRC), revealing ADAS/AD function limitations. It promotes defining Operating Design Domains (ODDs) within which the functions and systems are supposed to reach the minimum requirements. The type approval checks should consist of semi-random testing within this ODD. A proposed "robustness index" enhances reliability across diverse conditions. Market surveillance gains importance for independent testing, needing tailored protocols. This integrated approach aligns regulatory compliance with real-world safety, ensuring vehicles meet stringent standards beyond laboratory tests.

Implementing operational design domain for real-world operation

Dr Andreas Richter
Engineering Program Manager - Operational Design Domains
Volkswagen Commercial Vehicles
The concept of operational design domain (ODD) has been discussed in research and industry for a number of years but real-world applications beyond testing are not yet on the road. Regulations will demand a comprehensive ODD description for type approval as well as service area approval. Today’s ODD definitions are very generic and deliver only a few insights about the boundary conditions. This leads to additional efforts for explanation and showing (scenario-based) test results. Additionally, the argumentation of the completeness of the tests gets complicated. Having a technically precise but still human and machine-readable ODD definition could bridge this gap.

Leashing AI: On Challenges and Solutions in Autonomous Vehicle Safety Assurance

Ali Nouri
Senior system safety engineer in autonomous driving
Volvo Cars
Safe behavior of autonomous vehicles needs to be assured before being deployed on public roads and maintained safely during the operation phase. This presentation will delve into the following key aspects: 1. Autonomous Vehicle Safety Assurance and SafetyOps approach 2. Challenges toward Rapid SafetyOps, exemplified by System Theoretic Process Analysis (STPA) 3. Generative AI and Large Language Models as a Potential Solution

The UK's approach to connected and automated mobility (CAM)

Sumit Pandey
Head of Commercialisation
The Centre for Connected and Autonomous Vehicles (CCAV) is a joint unit of the Department for Business and Trade (DBT) and Department for Transport (DfT) unit. This presentation will provide an update on UK government activities on its £100 million, commercialising connected and automated mobility (CAM) programme from 2022-25 and the UK’s future plans for CAM innovation, commercialisation, regulation and legislation. In November 2023, the UK government committed up to £150 million funding between 2025-30 for CAM R&D and early commercialisation of these technologies, whilst also ensuring these are safe and secure for all.

Standards, regulations, homologation and collaboration

Recommendation for a common understanding of ISO 26262 regarding autonomous vehicles

Tobias Traub
Functional safety expert
Jonas Stüble
System architect
Technical regulations and recommendations do not yet fully account for the safety-related availability of power supply systems. Specifically, the application of ISO 26262 on the power supply of autonomous vehicles is troublesome. Concurrently, engineers have gathered to write a recommendation (VDA 450) that facilitates the application of safe electrical power supply to other systems with safety-related availability like autonomous vehicles. This presentation highlights the framework of the VDA 450 recommendation and its principles that comply with ISO 26262 and help to ensure safe power supply for autonomous vehicles.

Automated vehicles Level 1-2-3-4-5: overview of regulation/Euro NCAP status and testing challenges

Alain Piperno
Senior expert - autonomous vehicles testing and homologation
UTAC is a worldwide reference in testing and type approval and an accredited lab for Euro NCAP tests and for type approval tests in France. The presentation will review today's regulation and testing capacities proposals and new challenges including Level 1-2-3-4-5 regulations status for M1 vehicles, shuttles, buses, delivery robots, SW/OTA, cybersecurity, AI and virtual type approval, and today's needs/solutions for testing and validation: physical, new protocols, new targets, rain and fog testing, digital and VIL testing, AI, V2X, cybersecurity, etc.

CAV in-use monitoring metrics development

Ching-Yi Chen
Technical consultant, Smart Mobility Living Lab
The presentation will focus on developing comprehensive safety metrics for real-time monitoring of connected and automated vehicles (CAVs). This monitoring ensures the operational safety of CAV systems and infrastructure in automated driving, remote operation and advanced driver assistance system (ADAS) use cases. These metrics align with international safety assurance frameworks and standards for global relevance. Emphasis will be on detailed assessment methodologies to evaluate vehicle system and infrastructure performance. This critical approach feeds into the validation and verification of CAV safety arguments, facilitating safe and secure deployment.

Germany's autonomous driving law – technical challenges and liability risks

Benjamin von Bodungen
Bird & Bird LLP
Germany has recently adopted one of the most innovative legal frameworks on self-driving vehicles in the world. Yet the new law also requires compliance with extensive requirements regarding vehicle design that manufacturers, suppliers and the engineering community must be aware of. The presentation will place particular emphasis on these technical challenges. For instance, autonomous vehicles must be equipped with systems for mastering dilemma situations that prioritize the interests at stake in the event of an unavoidable accident. Manufacturers also have to ensure safety against cyberattacks throughout the entire vehicle lifecycle. Non-compliance bears significant risks of civil or even criminal liability.

Panel Discussion - Building an integrated toolchain for safe & confident deployment of autonomous vehicle and ADAS technologies

Ali Nouri
Senior system safety engineer in autonomous driving
Volvo Cars
Phil Durston
Technical manager Volkswagen vehicle development: proving grounds AD strategy
Volkswagen AG
Benjamin Engel
Chief Technology Officer (CTO)
Alexander F Walser
Managing Director
Automotive Solution Center for Simulation e.V.
Thomas Tentrup
Director of R&D
KÜS Bundesgeschäftsstelle
Karla Quintero
Research engineer/research and technology coordinator
IRT SystemX

Advances in software, AI, architecture and data management.

Ensuring vehicle software quality in an autonomous and V2X ecosystem

Nishant Khadria
Modern vehicles are no less than 'smartphones on wheels'. The huge growth in in-vehicle functionalities demands increased and continuous connectivity while regulatory requirements mandate extensive testing and cybersecurity. The situation is intensified by ecosystem partners ranging from 'steel to software' and 'simulation to street'. As the cost ratio of software to whole vehicle rises, efficient 'software quality' becomes crucial to manage costs, win market share and achieve early compliance. The presentation proposes a process- and product-based software quality framework in an autonomous and V2X environment through qualitative measurement of customizable KPIs through assessments and tests.

Chasing milliseconds: how we optimized in-vehicle OS boot time

Dustin Black
Senior principal performance engineer
Red Hat
The presentation will take you on a technical journey through some of the challenges of adapting a general-purpose Linux OS to an embedded automotive use case with strict regulatory and safety requirements. Extra seconds of boot time are hardly noticeable or impactful for servers with hundreds of days of uptime, but for a platform rebooted many times in a day and that must provide user interaction in seconds from power on for safety reasons, suddenly every CPU cycle is under the microscope.

Scalable software development addressing different levels of autonomy

Georg Kuschk
Director of perception
The presentation will cover common software architecture for different autonomy levels, how the development and deployment of products at different autonomy levels benefit each other, and examples and lessons learned from Plus’s deployments in Europe, the US and Australia.

Accelerate AV development with data-driven automotive AI

Frank Kraemer
Systems architect
IBM Germany
Developing AVs is a time-intensive and complex process that requires best-in-class data and AI training infrastructure. Companies developing software-defined vehicles need to accelerate time-to-market and minimize costs without sacrificing safety. Combining vehicle sensors, map data, telematics and navigation guidance using machine learning and data fusion techniques, data-driven development is not without its challenges. One of the biggest challenges is data collection and integrity, as data needs to be collected accurately and consistently to drive accurate decisions.

Journey toward software-defined connected and autonomous vehicles (SDCAV)

Plato Pathrose
CTO and technical director ADAS and automated driving
Vinfast Germany
The presentation will discuss the roadmap toward software-defined vehicles. What does a software-defined connected and autonomous vehicle look like and what are the requirements to design and deploy those vehicles? It will also cover the requirements and design considerations that are taken into account for vehicle architecture and various vehicle components. The change in approaches to the development, testing and production of the vehicles will be discussed. The drastic migration toward utilizing new technologies for the service and maintenance phase planned for such vehicles will be discussed.

SDV and vehicle motion management

Dirk Bangel
Chief expert
Robert Bosch
The presentation will show how vehicle motion management, a software system solution from Bosch for the complete vehicle motion domain, helps to drive the transformation toward software-defined mobility through multi-actuator control, a modular and scalable software architecture that simplifies the separation of hardware and software, centralized computing and standardized interfaces.

How generative AI will transform ADAS/AD

Gabriel Sallah
ADAS/AD Lead Architect
United Arab Emirates

How does the law on AI influence autonomous driving?

Jörg Kahler
GSK Stockmann

Panel Discussion - Safe AI for Automated Driving: Reality or Fiction?

The current hype around ChatGPT and Large Language Models (LLMs) has increased the focus on the need for regulating Artificial Intelligence (AI) (UK’s Global AI Safety Summit (Nov 2023) & US Govt’s Executive Order on AI). AI algorithms which are non-deterministic form a fundamental part of any Automated Driving System. Using non-deterministic algorithms in safety critical systems like Automated Driving require new approaches to safety argumentation & their regulation. This panel session will bring diverse AI approaches in AD development & diverse regulatory approaches to identify both the need and feasibility of regulation & developing safe AI.
Dr Siddartha Khastgir
Head of Verification & Validation, Intelligent Vehicles
WMG, University of Warwick
Richard Damm
Dirk Gorissen
Product lead - AI Driver
Georg Stettinger
Senior project manager R&D funding department

Accelerating Software Defined Vehicles through Open Source

Dan Cauchy
Executive Director
Automotive Grade Linux
The concept of a software-defined vehicle (SDV) has become a hot topic across the industry as automakers look for ways to address the dramatically growing complexity of developing and deploying software while simultaneously building the foundation for self-driving vehicles. Automotive Grade Linux (AGL), an open source software platform for connected car technology, has been working on software-defined vehicles for the past eight years. Dan Cauchy, Executive Director of AGL, will discuss the current state of SDVs and the work being done by automakers and Tier 1s as part of the AGL SDV Expert Group. He’ll also provide insight into the driving trends behind SDVs and enabling technologies including virtualization, containers, and the cloud.

What’s ahead for ADAS computing?

Guilherme Marshall
Director, ADAS GTM
Most computational capabilities that will power vehicles starting production in 4-5 years have already been designed in. For a fast-moving software function such as automated driving, this is massive challenge. Thus, in the absence of a crystal ball, Arm builds on close collaborations with leading automotive OEMs and suppliers to define next-generation compute platforms. This presentation will discuss their challenges and how upcoming technologies will help enable more efficient ADAS/AD software innovation.

Relevance of explainable AI and AI compliance for scaling AV fleets

Lucas Bublitz
Principal autonomous vehicle
P3 Automotive GmbH
The commercialization of AVs in San Francisco defined a new phase, as the maturity of technology is now proven at small scale. But scaling AVs requires an overall understanding of the occurrence of errors and their impact on decision making or misbehavior, as faults and failures can lead to a decrease in safety and confidence in AVs. It underlines the relevance of adopting the methods of explainable AI and applying conformity to the upcoming AI regulation. Transparency in self-driving systems ML/DL black boxes is essential for the operation and therefore the scalability of AI-enabled self-driving systems.

Demonstrating safety and validating and homologating automated driving systems for the deployment of level 2+ technologies and beyond


Marc Pajon

The SAM (Safety and Acceptability of Driving and Self-Driving Mobility) research project: results and perspectives

Dr Emmanuel Arnoux
Automated Driving Safety & Validation Working Group co-leader

Regulations and consumer testing requirements in the EU for ADAS and AD and compared to the rest of the world

Andres Aparicio
Head, ADAS and Connected and Automated Vehicles
The deployment of ADAS in the European market is guided by legal and consumer requirements defined by local stakeholders. The General Safety Regulation defines mandatory requirements that urge for standard fitment of multiple ADAS in all new vehicles. And beyond the legal framework, Euro NCAP foresees complex safety and assisted driving systems, with a comprehensive roadmap until 2030. In parallel, other regions including China and US also have implemented specific programs and drafted very ambitious roadmaps. The presentation will review current and future requirements for ADAS applicable to the European and other international markets.

The L2+ safety stakes for engineering

Luc Bourgeois
President AD/ADAS expert community

High Definition sensors redundancy and complementarity for extended autonomous vehicle ODD

Dr Benazouz Bradai
Research & Innovation Director - Master Expert in ADAS/Autonomous Driving

Omniverse and GenAI to accelerate the development and validation of ADAS

Oussama Ben Moussa
Head/CTO autonomous mobility

Mastering the complexity of automated driving in projects beyond L2 with scenario-based testing paving the way to virtual homologation

Dr Heiko Scharke
Global Product Manager
AVL List GmbH
Hannes Schneider
Lead engineer ADAS/AD scenario-based verification
The advancement of automated driving systems (ADS) beyond Level 2 autonomy presents intricate challenges that requires rigorous validation methodologies. Our presentation proposes a scenario-based testing framework that addresses the critical requirements for traceability, interoperability, and credibility in ADS development. It outlines the artefacts of a comprehensive validation toolchain, designed to ensure a robust and systematic approach to safety validation. We will consider methods and tools for identification of realistic scenarios and its statistics as an important part of the framework to ensure SOTIF conform safety and risk validation/mitigation in the given Operational Design Domain (ODD). Furthermore, we will discuss a systematic testing and validation toolchain to manage and deploy validation cases in real and virtual environments during different development and testing stages. A structured approach is crucial to master the complex testing and safety validation requirements and to proof that the residual is acceptable to operate ADS on public roads safely.

From digital vehicle to virtual twin to immersive virtual twin

Didier Wautier
General manager: synthesis and immersive simulation
The digitalization of Renault Group is not new, but it is intensifying as the company transforms itself into a 'tech company'. This is essential to keep pace with the growing technological complexity of vehicles, the ever-increasing number of technical and regulatory requirements and the continuous improvement of existing and future vehicles in a connected world. In recent years, the tools available to design and engineering have become so advanced that virtual reality has overtaken physical reality. The digital twin exists before the vehicle itself, and evolves throughout the design process, including the customer in the design loop. Depending on the stage of the project, the terms used are digital vehicles, digital twin and immersive digital twin. Their fields of application range from design and development to tuning and homologation.

Connected highways: a controlled & realistic testbed environment to validate ADAS/AD and V2X functions

Pierre Delaigue
Director - connected, autonomous, electric mobility projects

Summary and further discussion

Marc Pajon

Learning from real world and proving ground test & deployment, and integrated virtual testing.

Deploying autonomous vehicles – Holo's experience

Lars Himmer
Holo is an integrator and operator of autonomous vehicles. It handles applications, training of staff, implementation and supervision of autonomous projects. Holo is currently the driving force behind the leading autonomous project in Europe: the deployment of vehicles using Mobileye’s autonomous software in the Grorud area in Oslo, Norway. The company has deployed more autonomous projects in Scandinavia than any other company. Our experience ensures safe operations that constantly push autonomous technology to its limit and systematically collect data to make improvements in customer experience, stability and autonomous performance.

Agile scenario alteration: a framework to accelerate automated vehicle testing

Nils Katzorke
Project coordinator
Mercedes-Benz AG
With current progress in automated driving, the number of use cases for automated vehicles that can be tested on proving grounds has become substantial. The point where use cases can be tested in an individual, experimental manner has been exceeded. For economic reasons and to increase the reliability, proving ground tests need to be standardized and set up as fast and cost-effective as possible. Hence, test equipment providers and proving ground operators adopted new methods to rapidly alter test scenarios, regarding road markings, traffic infrastructure, vulnerable road users and other traffic participants. The presentations aims at establishing a connection between different methods of agile scenario alteration to showcase how they can be intertwined in a holistic framework. A crucial question in this context is, how physical test drives and digital test drives relate to each other and what potential benefits of cyber-physical test procedures are. Additionally, the presentation will discuss what crucial environmental conditions are currently not available in standardized digital or physical simulation methods. Examples from the research projects for test infrastructure development at the Mercedes-Benz Test and Technology Center in Immendingen will be provided to make the postulated ideas tangible.

Optimizing ISA experience: city data validation strategies to improve the quality of digital maps with speed limits

René Spaan
EU Smart Mobility project leader
City of Helmond (NL)
In its dedication to road safety, the City of Helmond actively participates in international projects concerning intelligent speed adaptation (ISA) to address speeding concerns, both real and perceived. ISA, recognized for preventing 20% of fatal accidents, notifies drivers of speed limits for compliance. René Spaan examines ISA readiness in medium-sized cities, emphasizing data validation for a seamless user experience. During the readiness assessment for ISA-equipped cars, Helmond observed inaccuracies in speed advice due to unvalidated digital maps lacking verified speed limits. As part of the project, a validation and feedback loop was established between the road authority and the Dutch national access point to optimize the national digital maps of speed limits, usable by third parties.

15:15 - 15:45


Evolving PG for the development and validation of AD in different ODDs

Dr Sebastian Siegl
Function verification & validation strategy responsable automated driving functions
Uwe Burckhardt
Head of DEKRA Lausitzring
Autonomous driving poses a new challenge to the design of proving grounds, as autonomous driving functions evaluate with extensive sensor technology not only the road surface and driving dynamics parameters but also the environment to enable operational design domain-specific features. As a consequence, for function testing under public road conditions, the proving ground tracks and environment must reflect the conditions found on public roads in different ODDs. Another important feature is the enablement of various dynamic scenarios on the test track. Dynamic swarm-based scenarios must be executable, reproducible and safe. For this, the connectivity and communication infrastructure of the participants is needed. This presentation gives insight into the track design, infrastructure, communication and equipment requirements and also solutions for a new type of proving ground for the development and validation of autonomous driving.

The AVL prototype 'AutBus': autonomous public transportation in adverse weather

Armin Engstle
Site manager AVL Roding
AVL Software and Functions GmbH
The core of the presentation becomes apparent in the evaluation of lidar perception in adverse weather conditions respectively in different rain intensities and fog visibility ranges. The optimization of AD sensor systems in adverse weather is a prerequisite for the all-day use of autonomous vehicles in public transportation. The analysis demonstrates that the influence of fog on lidar perception is significantly higher than the influence of rain. Additionally, it seems, that small rain rates with finer raindrops might be affecting lidar beams more than higher rain rates with thicker drops.

State of the art scenario based testing and simulation

When ODD meets OpenSCENARIO 2.0 – safety-driven validation

Gil Amid
Chief regulatory affairs officer
The presentation modeling of ODD ( operational design domain) in ASAM OpenSCENARIO® DSL 2.0, and incorporating it into safety-driven validation. The presentation demonstrates the interaction between scenarios and ODD during virtual testing. Special Attention will be given to the challenges of modeling ODDs and validating correct behavior of the ADS within an ODD.

Enabling Virtual Test & Validation – Self-Sovereign Identity via OIDC to enable Decentralized Open Data Markets

Carlo van Driesten
Systems architect for virtual test and validation
BMW Group
The goal of a virtually enhanced homologation process through the usage of driving simulators relies on the quality of the data used as input for the simulation. If HD Maps, driver models, scenarios, or sensor models, the integration of such elements in various systems throughout deep supply chains demand a common understanding brought by standards like e.g., OpenDRIVE from the ASAM e.V. OpenX. BMW explores the possibility to create an open and decentralized data ecosystem (ODDE) to increase the availability of standardized simulation data. The European research family GaiaX with the help of DLT technologies, self-sovereign identities and zero-knowledge proofs for selective privacy and scaling in open networks serve here as the technological baseline. We show the current state of the ODDE realized in the ENVITED (ENvironment for VIrtual TEst Drive) research cluster at the Automotive Solution Center for Simulation e.V.

How to maneuver in the stakeholder landscape when verifying and validating highly automated driving systems

Dr Majid K Vakilzadeh
AD V&V system architect
One of the greatest challenges on the road to full deployment is proving that Autonomous Driving technology positively impacts traffic safety. To support such a claim with statistical evidence, an enormous number of kilometers of driving is required, widely accepted to be unfeasible. Zenseact’s approach to safety evaluation is developed around three pillars. First, adopting a truly redundant design strategy in different parts of our AD solution. Second, to scale up the quantity of data from in field operations through dynamically probing data from a large customer fleet. Third, using state of the art simulation environment to stress test traffic scenarios required to excel in from a societal perspective. Zenseact aims to accelerate the transition toward zero collisions through faster development, verification and validation and deployment of safety-critical features. By collecting road data and analyzing safety related information, we direct the development efforts to maximize safety and comfort.

Method development of test track testing of a head on scenario

Carina Björnsson
Technical expert, driver assistance and active safety test methods
Volvo Car Corporation
Head on collisions are high speed collisions and these mostly cause severe injuries of the persons in the vehicle. The speed at the impact is inevitably the sum of the two oncoming vehicle speeds. Volvo Cars decided to investigate how to address these types of accidents with our active safety function collision mitigation by braking. The aim is to primarily mitigate the injuries by reducing the speed at the impact, and not to have full avoidance in all cases. As the function is developed, the question on how to test it was raised. This presentation describes the development of the test methods for testing of such a function. A function that focus on high speeds and interact at a timing of very low time to collision.

Power to the people: democratizing safety for automated driving

Dr Siddartha Khastgir
Head of Verification & Validation, Intelligent Vehicles
WMG, University of Warwick
Hamid Serry
Autonomous vehicle engineer
WMG, University of Warwick

Simulation-based critical scenario identification and analysis for automated driving

Adam Molin
Technical manager
Denso Automotive Deutschland GmbH
Verification and validation processes play a vital role in ensuring the safety and reliability of autonomous vehicles. Scenario-based testing has emerged as an effective approach for identifying critical scenarios that challenge the capabilities of automated driving systems. This presentation aims to explore the usage of scenario-based testing to automatically identify critical factors by data analysis within a simulation. Built on experience from various R&D projects, the presentation will share best practices and insights for critical scenario identification to maximize efficiency and coverage.

Real-world accident scenario simulation

Thomas Unger
Head of data analysis and simulation
Verkehrsunfallforschung an der TU Dresden GmbH
The GIDAS (German In-Depth Accident Study) database contains detailed information about accidents and the GIDAS Pre-Crash Matrix (GIDAS-PCM) offers the possibility to observe the pre-crash phase. The GIDAS-PCM contains all relevant data to simulate the pre-crash phase. This includes the characteristics of the participants, the dynamic behavior of the participants as a time-dependent course as well as the geometry of the traffic infrastructure. The paper shows the conversion progress of GIDAS data in OpenDrive and OpenScenario. A detailed investigation of active safety systems in real accident situations has been made feasible and the importance of simulating real-world accidents is shown.

Measuring the quality of a scenario database

Sytze Kalisvaart
Senior project manager
Many companies have created scenario databases. One question remains open: what is a good scenario database? Based on work with Torc Robotics, Project SunRISE and Hi-Drive, TNO will present approaches and metrics including metrics for identifying missing scenario categories, assessing scenario coverage related to specific environments or operational design domains (ODDs), determining the most common sequences or combinations of scenario categories and comparing data sets across years. Examples will illustrate enriching the database with accidentology and edge cases. These metrics are essential for providing enough confidence in utilizing scenario databases to specify an ODD or test automated driving.

Rapid SW and HW prototyping for automated driving: sensor and function benchmarking with JUPITER platform

Dr Clara Marina Martinez
Engineer - ADAS virtual development
Porsche Engineering Services
The race to release next-generation ADAS is slow and expensive. Complex ADAS functions are developed using theoretical sensor specifications and can only be tested in late project stages. In Porsche Engineering we have accelerated the time to vehicle testing of our ADAS algorithms by means of our JUPITER vehicles. JUPITER is a fully scalable rapid prototyping platform for ADAS that allows for early close-to-series testing. It integrates state-of-the-art ADAS algorithms, is equipped with high-performance ASIL-D Middleware and scalable data exchange, and is interoperable and real-time capable. We will present the sensor benchmark use case as a teaser of the plethora of possibilities that JUPITER offers.

From Road to Simulation in a Nutshell

Thomas Mauthner
Program manager
Hong-Seok Lee
Senior Researcher
Korea Testing Laboratory (KTL)
Christian Gutenkunst
Solution Manager
AVL Deutschland GmbH
Overwhelmed with the coverage of your Operational Design Domain? How can you guarantee the completeness and reliability of your ODD parameterization? AVLs approach from Road-to-Simulation allows getting a better understanding of your underlying data. Our solution supports you from real-world data collection to data processing until evaluation and analysis. Such concrete scenarios are mapped to logical scenarios and parameterized by captured real-world data. These resulting scenarios are used to execute simulation test plans. Based on these results, the following next steps can be taken: identify gaps in the current implementation, gaps in the current ODD definition, and missing real-world data. Our customer Korea Testing Laboratory operates the complete toolchain mentioned above and will give insights for data collection, analytics, scenario extraction, digitalization, and scenario re-simulation.

Navigate toward the next generation of automated driving and software-defined vehicles

Olivier Sappin
Dassault Systèmes
In the constantly evolving industry ecosystem toward the software-defined vehicle, the development of advanced driver assistance systems (ADAS) and automated driving (AD) are at the forefront, promising enhanced safety and a better driving experience. However, the sheer complexity of these technologies requires a paradigm shift in the development strategy to ensure success. This presentation will explore innovative methods based on model-based systems engineering, massive simulation and digital certification scenarios correlated with real on-track results for the delivery of safe and efficient highly automated technology. Key industrial projects with automotive car makers will illustrate the usage of these methods and software solutions.

Panel discussion - Using scenarios and ODDs together to best achieve state of the art safety.

Vincent Abadie
Senior Fellow ADAS and Autonomous Driving
Dr Andreas Richter
Engineering Program Manager - Operational Design Domains
Volkswagen Commercial Vehicles
Carlo van Driesten
Systems architect for virtual test and validation
BMW Group
Hakim Mohellebi
Expert, engineering simulation functional architecture
Marc Pajon, Consultant, TAKTECH SAS

Developments in connectivity, mapping and positioning

The emerging importance of connected mobility for safety on roads

Thomas Jäger
Senior vice president
The presentation will cover the latest updates on road safety issues (DEKRA yearly road safety reports, global issues, vehicle type impacts); the latest V2x connectivity technology developments, deployments and related safety improvements; the latest regulatory and certification situation (EU, US and others); the latest updates on testing requirements for connected and automated driving; the most recent developments in regional and global interest groups; and the challenges and outlook.

5G automotive connectivity: what to expect and when

Dr Maxime Flament
5GAA brings together global automotive, technology and telecommunications companies to develop end-to-end connected vehicle solutions for smarter, safer and more sustainable traffic. The presentation will give an overview of the 5GAA roadmap ramping up toward increasingly advanced use cases in the 2030 timeframe. The full integration of V2X technology into ADAS and automated driving systems (ADS) is one of the most prominent targets with many challenges at technological, standards, policy and business levels, but even more around the required mutual trust in such distributed systems. The presentation will expand on these industry challenges and the possible solutions before there can be any true introduction of these advanced use cases on the market at a global level.

ESA's LEO-PNT mission: revolutionizing GNSS

Florin Grec
LEO-PNT mission and experimentation engineer
European Space Agency
In this presentation, we explore the European Space Agency's innovative Low-Earth Orbit PNT initiative, a project poised to significantly enhance GNSS systems. Particularly relevant to the automotive community, this development promises improved accuracy and reliability over traditional GNSS. By harnessing the closer proximity of low Earth orbit (LEO), the ESA's program aims to offer rapid, precise PNT data, crucial for the future of autonomous and connected vehicles. This presentation delves into the technical advancements, potential applications and the transformative impact of LEO-PNT on automotive navigation technologies.

10:15 - 10:45


Opportunities and challenges of integrating V2X in ADAS

Jens Buttgereit
Product owner
Vector Informatik GmbH
The integration of V2X communication into modern ADAS offers significant advantages and eliminates the limitations of traditional sensors. This enables improved perception of the environment and significantly increases safety. However, the challenges in integrating V2X communication into modern ADAS are manifold: the interoperability requires industry-wide accepted standards, sensor fusion algorithms additionally need to integrate and interpret another sensor, and an effective test and validation system is crucial to ensure the reliability and performance of these systems at all stages of development. This presentation provides an overview of the opportunities and challenges of V2X integration in ADAS.

The pathway to fully connected services

Suku Phull
Technical specialist
The Department for Transport
Intelligent transport systems (ITS) have evolved over the last 20 years from simple traffic signals, traffic detectors and signs operated by human operators into interconnected systems connecting and interfacing more directly to individual users with increasing levels of automated control through the emergence of connected and automated vehicle technologies. These more recent developments are intended to enable data sharing between systems to deliver a wide range of transportation-related socioeconomic benefits; within Europe these are generally termed ‘cooperative ITS’ (C-ITS) services and embrace infrastructure-to-vehicle (I2V), vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication. This paper will provide an overview of global activities.

Advancing autonomous driving through ADAS and V2X communication

Khaled Alomari
Manager for connected vehicles
MHP, a Porsche company
This presentation explores the intersection of advanced driver assistance systems (ADAS) and vehicle-to-everything (V2X) communication, illuminating the transformative impact of connectivity in autonomous driving. The benefits of this symbiotic relationship are explored, emphasizing improved safety, enhanced traffic efficiency and rapid response to dynamic road conditions. Key ADAS functions are scrutinized in the context of real-time data exchange, situational awareness and predictive analytics enabled by V2X connectivity. Real-world case studies underscore successful applications of V2X in ADAS, showcasing tangible positive impacts on safety and operational efficiency. The presentation concludes with a forward-looking perspective, envisioning the future potential of ADAS with V2X.

12:00 - 13:20



Advanced simulation and HIL testing

Reduction of the residual risk in a SOTIF-compliant validation process

Thorsten Püschl
Product manager
dSpace GmbH
A major challenge for bringing autonomous vehicles to public service is homologation. It requires a SOTIF-compliant verification and validation process of the AV stack. Validation is a particular challenge as a reliable argumentation is required proving that the residual unknown risk is sufficiently low when the vehicle operates within its operation design domain. dSpace presents a new approach combining the analysis of real test drives with SIL simulation. Unknown risks in driving scenarios are found, evaluated and reduced. Abstract scenarios are used to categorize relevant scenarios experienced in test drives for an approximation of plausible test coverage evidence.

Unlocking the future: harnessing the power of digital twins

Ahmed Yousif
System simulation expert/simulation and HIL team leader
Valeo Detection Systems
In this presentation, we delve into the transformative potential of digital twins driven by advanced simulation technologies. Digital twins – virtual replicas of physical objects or systems – have become game-changers in various industries. We explore how simulation allows us to create highly accurate and dynamic digital twins, offering real-time insights into product performance, predictive maintenance and design optimization. By bridging the gap between the physical and digital worlds, digital twins enable informed decision making, reduced costs and enhanced efficiency.

Real-time testing of automated driving functions using parallelization

Martin Herrmann
Application expert ADAS & AV
IPG Automotive GmbH
Autonomous driving functions can no longer be validated solely in the real world, as critical edge cases are rare and dangerous. HIL simulation technologies bridge the gap between simulation and in-vehicle testing. However, the complexity of autonomous vehicles, number of sensors and ever-increasing data rates pose new challenges for HIL simulation. A possible approach is prototypically demonstrated with the implementation of two parallelization concepts based on specific use cases: CPU-based calculations on multiple real-time systems and parallelized sensor simulation on multiple GPUs, allowing arbitrary scalability of the number of sensors as well as the integration of additional models and systems.

Enhancing autonomous vehicle development through simulation with aiSim

Dániel Tósoki
Product director, aiSim,
Explore the critical role of perception simulation in developing safe and reliable autonomous vehicles. This keynote offers an in-depth look at aiMotive's aiSim and its capabilities in simulating real-world sensor data to train and validate perception systems. Learn how aiSim empowers engineers to create highly realistic and challenging scenarios for perception algorithms, ensuring they are prepared for complex road environments. Discover the impact of perception simulation on accelerating the development of AI-driven perception in self-driving technology.

Best practices for the development, acceleration and safe deployment of ADAS & AV technologies

Navigating challenges in autonomous driving data acquisition

Adrian Bertl
Strategic product manager
b-plus technologies GmbH
This presentation delves into pivotal challenges faced by sensor and vehicle manufacturers in autonomous driving data acquisition. Focusing on data protection and confidentiality, it spans issues related to navigating sensitive data and enabling collaboration with external entities right from the beginning. Addressing data quality concerns, essential inputs for AI model training including tool requirements for compression, sensor synchronization and quality control of annotated data are covered. Emphasizing the importance of a diverse set of scenarios, tool requirements for selective data recording are outlined. Lastly, the presentation delves into the process aspects, covering the infrastructure for managing large scale data acquisition.

The significance of iterative understanding of ML data sets

Tommy Johansson
Perception expert
Machine learning (ML) models are only as good as the data sets they are trained on. The quality of the data set plays a pivotal role in determining the performance and reliability of the resulting models. However, achieving high-quality data sets is not a one-time task; it requires an iterative process of understanding, assessing and refining data to enhance model performance continually. This presentation delves into the critical role of iteratively assessing data set quality concerning model performance in the realm of machine learning, focusing on ADAS/AD use cases.

Accelerating the safe deployment of autonomous trucks

Dr Maximilian Köper
Senior engineering manager
Torc Robotics
Dr Holger Banzhaf
Managing Director
DeepScenario GmbH
Deploying safe autonomous trucks requires a deep understanding of real-world driving. A key part of this process is the collection and analysis of traffic data to derive requirements, test cases and statistical distributions for safety validation. In this joint presentation, we give insights into DeepScenario’s collaboration with Torc Robotics to accelerate the safe deployment of autonomous trucks. At the core of the solution are stationary cameras combined with DeepScenario’s AI software, providing Torc with unparalleled data collection capabilities at critical locations. This allows Torc to significantly increase the efficiency of scenario mining and advance the safety of its autonomous trucks.

10:15 - 10:45


Validation of interior cameras in synthetic environments

Wolfgang Stolzmann
Advanced driver distraction warning (ADDW) is mandatory from 2024. Besides this and other safety functions, interior cameras can be used for extended user experience and improved passive safety and well-being. For occupant monitoring systems (OMS), this means that a vast range of new features will be introduced in the upcoming years. Therefore, Luxoft has further developed its OMS virtual validation toolchain. This presentation will cover corner cases for OMS validation as well as typical test scenarios for KPI analysis. It will present a database of virtual videos together with perfect ground truth (GT) data and apply it to a prototype device under test.

Moving from ADAS to HDAS – humanized driver assistance systems

Raunaq Bose
Humanising Autonomy
ADAS and AV technologies have so far had limited success in areas with high numbers of vulnerable road users (VRUs) such as pedestrians and cyclists. The current approach is much too focused on the 'physics' of the situation (relative distances, velocities and accelerations of VRUs), which does not reflect the reality of interactions and negotiations between vehicles and VRUs. Developing ADAS and AV technologies focused on the behavior of VRUs, on top of their physics, is key for the widespread adoption of ADAS. This presentation will outline the performance and user benefits of a humanized driver assistance system (HDAS).

Bridging Scale and Differentiation in Autonomous Driving

Nimrod Brickman
VP business development
The aspirations of automakers to create hands-off systems tailored to their brand identity face challenges from the practical business imperatives of timely market entry and cost-effectiveness. Striking a delicate balance between achieving scale and delivering customization requires a nuanced interplay involving perception, driving policy, and control, alongside a dynamic collaboration between supplier and carmaker. This presentation by Mobileye VP of Business Development Nimrod Brickman will discuss the complexities of designing for differentiation in hands-off driving and remaining challenges on the path from development to commercialization. Nimrod will discuss the paradigm shift that Mobileye DXP is fueling by enabling automakers to retain control of the driver experience through a new programming language that strategically splits the stack into universal and unique components.

Optimizing safe stop trajectories: synthesizing algorithms for autonomous vehicles

Kai Wah Chan
Software developer
TOPAS Industriemathematik Innovation gGmbH
In the realm of autonomous driving, ensuring a secure and seamless halt is imperative across diverse scenarios, ranging from routine stops at traffic lights to critical situations involving navigation failures or communication errors. This presentation unveils a novel methodology for swiftly calculating safe stop trajectories. The approach harmonizes machine learning tools with classical algorithms rooted in optimization and optimal control theory. Notably, it harnesses the underutilized feasibility correction method, leveraging parametric sensitivity analysis to significantly expedite computation. This research contributes a nuanced perspective to the pursuit of enhancing safety and efficiency in autonomous vehicle systems.

12:25 - 13:55



Development, test, deployment and evaluation of sensors.

Transforming vehicle manufacturing: redefining sensor selection processes through cloud technology

Danny Atsmon
CEO & founder
The Automated Driving Perception Hub (ADPH) is a joint venture between Cognata, Microsoft and AMD, providing an end-to-end solution for selecting sensor packages with confidence and efficiency. It combines Cognata’s ADAS simulation software, Microsoft’s Azure cloud, AMD GPUs and sensor models supported by suppliers. The presentation will address the complexities of selecting a sensor suite for ADAS and autonomous vehicles, offering a solution to help impede innovation and reduce costs. The platform enables engineers to run virtual tests and analyze sensor package alternatives, producing a cost/performance analysis in a matter of days instead of weeks.

Quantifying AV sensor performance during adverse weather conditions

Andre Burgess
Assured Autonomy Progamme lead
National Physical Laboratory
NPL and the Met Office have been undertaking a project funded by the UK Department for Transport to develop the methodological framework required to reliably evaluate how well automotive sensors used within self-driving vehicles perform in different weather-related conditions. When developed, this framework will be used to allow for the testing of AV sensors as part of the assurance process as well as aiding in the safety assurance process to determine the limits in which these vehicles may operate (operational design domains). This presentation considers what is required to demonstrate the performance of CAV sensors to support system developers, regulatory approval and authorization processes.

Advanced in-cabin safety and comfort with new hybrid image sensors

Lutz Hoestermann
Technical marketing manager automotive imaging
While driver monitoring systems promise greater road safety by assessing driver alertness and ability to drive, the next step on the way to autonomous cars is sensors that monitor the full vehicle interior, covering both the driver and all passengers. At the same time, new applications will be enabled, like safety belt checks, vital sign monitoring, child detection and high-quality video/picture recording. The presentation will show how this innovative sensor can enable a 'one camera' system which integrates both infrared and HDR color images and solves development pain points, thus generating a cost-efficient solution and at the same time bringing added value to customers.

15:15 - 15:45


Flexible HIL helps technology providers accelerate CI/CD capabilities

Gordan Galic
Technical marketing director
Nowadays automated vehicles have 10+ cameras, multiple radar, lidar and other sensors. A diverse approach to simulation is a strategic need for ADAS platform providers. Technology providers adopting HIL-based resimulation together with cloud-native SW capabilities have a more complete approach. HIL platforms must leverage big data and enable fast feedback to developers. The presentation will explain how to stay ahead of new HW requirements with the futureproof HIL platform that grows with users’ needs. Typical HIL validation challenges and their solutions will be presented based on Qualcomm’s use of Xylon’s HIL system in the development and validation of Snapdragon Ride Vision.

Lab-based homologation of SAE Level 3 vehicles using multisensor simulation

Gregor Sievers
Product manager
dSpace GmbH
Efficient homologation of SAE Level 3 vehicles requires testing and validation of software and hardware systems in the lab. This results in new challenges and requirements compared to traditional testing such as the simulation of validated sensor raw data with the highest timing accuracy. This presentation offers a comprehensive end-to-end test architecture for the verification of Level 3 functions in a controlled lab environment. This includes the simulation of dozens of sensors simultaneously in real time and highly synchronized. The presentation covers sensor simulation for camera, radar, lidar and ultrasonic sensors, as well as all automotive bus interfaces and V2X and GNSS/GPS.

New tendencies in lidar technology for autonomous vehicles

Valeriy Savelyev
Chief science officer
Integrated Quantum Photonics
The current state of development of autonomous vehicle technology requires a critical analysis of the requirements and key elements of autonomous driving systems, in particular, visualization systems. The report focuses on emerging trends in lidar technology to improve performance in autonomous vehicles. The new trends are flash principles of lidar with fast response; optical systems for laser beam distribution, in particular diffraction optics; a new method of obtaining information in the format of a visual camera with distance information (possibly in color), which makes it possible to analyze information based on AI without the stage of spatial reconstruction; and others. This also provides advanced engineering solutions, such as the absence of mechanical parts, miniaturization, power consumption and others.