Preliminary Conference Programme



Day 1: Tuesday 21 May

Room A Keynote Presentations and Conference Opening
09:00 - 12:30

09:00

Verification approaches for autonomous vehicles

Amir Shah
Senior systems engineer
Uber ATG
USA
Defining good safety, functional and performance requirements for completely driverless cars has been an industry struggle since the inception of self-driving vehicles. How do manufacturers set real targets and goals for performance and safety instead of chasing 'better' for eternity? A combination of traditional big systems engineering and new methods of verification for machine learning systems will help pave the way for manufacturers to responsibly demonstrate 'good driving'. We will discuss the methods used at Uber ATG and where we hope to see the industry move in the near future as live deployments become reality.

09:25

Virtual testing for autonomous vehicle validation and certification

Andras Kemeny
Expert leader immersive simulation
Renault
FRANCE
Autonomous vehicle validation for both engineering design and public acceptance will require the development of comprehensive testing and certification methodologies. In view of the large number of driving miles to check for robust and efficient autonomous driving models, the use of driver-in-the-loop and high-performance computing simulation is mandatory. The new validation methodologies to be introduced for virtual testing are under extensive development today by automotive companies and certification bodies. High-performance virtual environments corresponding to the test scenarios are to be built, as well as new validation tools guaranteeing high-fidelity correlation between field and virtual testing.

09:50

Singapore Technical Reference TR 68 : 2019 Autonomous Vehicle Standards

Dr Jayar Shankar
Programme head, Smart Mobility Solution
Singapore Technical Committee for Autonomous Vehicles, Institute for Infocomm Research (A*STAR)
SINGAPORE
This session covers a set of provisional national standards that was launched in Jan 2019 to guide the industry in the development and deployment of fully autonomous vehicles (AVs). Known as TR 68, Technical Reference 68 will promote the safe deployment of fully autonomous vehicles in Singapore. As an industry-led effort, comprising representatives from the AV industry, research institutions, institutes of higher learning and government agencies, the group has developed standards covering four key areas of AV deployment: vehicle behaviour, vehicle functional safety, cybersecurity, and data formats. Set as a provisional standard, TR 68 will continue to undergo refinement as AV technology matures and with future feedback from the industry.

10:15 - 10:45

Break

10:45 - 11:45

Panel Discussion - Accelerated Development to 'Level 4-5' AV's

As dozens of companies from Europe and China to Detroit and Silicon Valley look to build and deploy Level 4+ autonomous vehicles (AV's) in the coming years, many are looking to specialized horizontal software suppliers to accelerate their internal development process and time to market. This panel will feature executives from four such software companies, that are bridging the gap between the tech industry and the auto industry.
Qasar Younis
Co-founder and CEO
Applied Intuition Inc
USA
Mohammad Musa
Founder and CEO
Deepen AI Inc
USA
Ro Gupta
CEO
Carmera
USA
Tobenna Arodiogbu
CEO
Scotty Labs Inc
USA

Room A Vision - LiDAR, Sensors & Mapping Technology
14:00 - 18:15

14:00

Building the vision for autonomous mobility

Dr Jason Eichenholz
Co-founder and CTO
Luminar
USA
Autonomous mobility is the disruptive technology of our era, and at its core are optical sensing challenges. Getting better data required to operate safely is the key to a driverless future, and this all hinges on new kind of lidar built for self-driving scenarios. Join OSA and SPIE fellow and co-founder of Luminar Jason Eichenholz in a talk on the requirements for self-driving vehicles and a vision for a major breakthrough in lidar.

14:25

Invisible integration of solid-state lidar to make beautiful self-driving cars

Filip Geuens
CEO
XenomatiX
BELGIUM
Lidars are still mostly placed on the outside of vehicles. Mass-production adoption will require more aesthetically pleasing integration. Consumers are expecting higher levels of automation without giving up slick car design. As lidars emit and receive specific lightwaves, elements to cover or hide the sensor typically affect their performance. XenomatiX worked together with Tier 1s on integration of its solid-state lidar. A front-view long-range lidar behind the windshield will be presented. The impact of the windshield will be explained, as well as the benefits and challenges of this integration. Example data will be shown taken in real driving circumstances.

14:50

Overcoming the validation challenges for smart video cameras

Davor Kovacec
CEO
Xylon
CROATIA
AI-powered smart automotive video cameras are enabling self-driving vehicles to better perceive their surroundings. Autonomous vehicles will have an estimated 10+ cameras that integrate high-resolution HDR video sensors and vision processors. These systems generate tremendous amounts of heterogeneous data and require innovative new approaches to multi-channel capturing of sensor data for validation. The presentation will give an overview of smart cameras with high-speed serial links, and standard data formats to be used by third-party HIL/SIL platforms. System requirements will vary by OEM, and the design requirements need to support a configurable hardware-based platform for non-invasive capturing of unaltered and accurately time-stamped data.

15:15

Bringing the power of radar to autonomous driving

Kobi Marenko
Co-founder and CEO
Arbe
ISRAEL
While OEMs ramp up Level 3 vehicle production, recent AAA testing shows ADAS systems are not ready to handle real-world driving. To achieve L3 and higher autonomy, there is a need for a highly advanced sensor to view roads with ultra-high resolution and a wide field of view – in the hope of resolving ambiguities, achieving low false alarm rates, and coping with mutual interference.This presentation will explain why imaging radar is the only technology that can overcome industry challenges, and discuss the role radar plays in the future of vehicle autonomy and mobility.

15:40 - 16:10

Break

16:10

OADF – the cross-domain platform driving standardization in HAD

Philip Hubertus
Senior manager, product management
Here Technologies
GERMANY
Automated driving aims to deliver on two key promises to consumers – mobility and comfort – allowing us to make better use of our time when we drive from A to B. Furthermore, increased safety will result in fewer accidents and traffic-related casualties. A network effect that is driven by the exchange of sensor data, traffic/safety information and map data across the automotive industry players is needed. Learn more about the goals and achievements of the OADF with its members Adasis, NDS, Sensoris and TISA – and how you can participate and add to the network effect to fulfill the promise of automated driving.

16:35

Lidar Sensors for Autonomous Vehicles - Testing and Validation Demand

Dr Mircea Gradu
Sr. Vice President Quality and Validation
Velodyne LiDAR
USA
There is significant need for the AV industry to identify lidar requirements and standardize how to address them. The goal is to have lidar products undergo testing and validation based on the standards early in their product lifecycle with the results available to automakers and Tier 1 suppliers. It is necessary to create specialized tests and validation cases that establish standard ways to determine whether lidar sensors can address the industry demand. To be of value to automakers, all lidar sensors need to be assessed by the same gauge.

17:00

How FIR technology will bring Level 5 autonomy to mass market

Yakov Shaharabani
CEO
AdaSky
USA
Far infrared (FIR) technology is experiencing a revolution, entering the automotive market to fulfill OEMs' need for a solution capable of detecting and classifying all living and non-living objects in an AV’s surroundings. This presentation will detail the weakness of radar, cameras and lidar, and how these technologies are unable to independently provide AVs with adequate and reliable detection in every environment condition. Moreover, it will assess the technical advantages of FIR and highlight use cases in which FIR and CMOS cameras can be used together to deliver the sensing capabilities needed to deploy full vehicle autonomy to mass market.

17:25

Precise location for AV navigation systems

Anselm Adams
Co-founder and CEO
Albora
UK
Current technologies do not provide fast, high-precision location coordinates in order to be able to navigate a Level 5 AV safely and securely. Although several tech companies are working on the problem, no one has been able to provide a cost-effective solution. Albora is working to provide such solution.

17:50

Developing the ultimate perception system for autonomous vehicles

Juergen Ludwig
Director of business development
Cepton Technologies
USA
The automobile industry is trying to determine the ultimate combination of perception systems for safe navigation in autonomous vehicles. The presentation will discuss why the ideal system will rely on lidar sensors for 3D mapping of surroundings, cameras for vision, and radar to determine speed and distance. We will share the pros and cons of each system and how they balance each other out for safe navigation. The session will also cover the challenges of mass production, and the techniques the industry is using for developing lidar sensors that are high resolution, low power, compact in size and low in cost.

Room B Simulation - Validation in the Virtual Domain
09:00 - 12:50

09:00

Challenges of high-fidelity sensor simulation in SIL and HIL environments

Holger Krumm
Product manager
dSPACE GmbH
GERMANY
Autonomous vehicles are now on the horizon. Functions for autonomous driving have to be test driven over hundreds of millions of kilometers via software-in-the-loop (SIL) simulation to reduce costs and improve test coverage. For development and validation purposes of algorithms based on sensor data, it is necessary to generate synthetic sensor data for the driving simulation. This work presents a powerful integrated and unified toolchain for SIL and HIL testing of autonomous vehicles. It will address challenges for sensor data generation with GPU-based high-performance rendering by state-of-the-art game engines in combination with raytracing. Future developments will also be outlined.

09:25

Leverage hybrid scenario generation for AV certification

Rodolphe Tchalekian
EMEA pre-sales engineer for autonomous driving
ESI Group
GERMANY
Autonomous vehicles should handle complex, unusual and hazardous scenarios without human intervention. Their certification will require a balance between real and virtual testing. To support both, dedicated SW tools should be interoperable, and easy to use and integrate into innovative test and validation processes. ESI is providing a standalone scenario generation solution using a high-level description language based on OpenSCENARIO, together with an environment to simulate the output from multiple physical sensor systems for outdoor scenarios that combine vehicles, obstacles, pedestrians, weather and road conditions. This presentation will highlight results from pilot projects involving hybrid testing and AV certification.

09:50

Application of 'over-the-air' radar stimulation for vehicle-in-the-loop tests

Steffen Metzner
Technology scout ADAS, simulation and control
AVL List GmbH
AUSTRIA
The main test and validation development environment of ADAS and AD functionalities is still the actual vehicle. This time-consuming and expensive method lacks reproducibility and demands a large number of staff depending on the complexity of the scenario. The DrivingCube AVL approach aims to bring a ready-to-drive vehicle into a virtual environment. This enables functional testing independent from weather conditions and daylight, and improves reproducibility. This presentation will show the application of radar stimulation for vehicle tests based on the results of research projects. It will also provide an outlook on radar stimulation for future radar systems.

10:15

Training perception software with simulated test drives

Nicholas Keel
Principal market development manager - autonomous vehicles
National Instruments
USA
There is no question that simulation is the method by which we achieve the billions of miles of driving needed to verify safe operation of autonomous vehicle software. Although we are making great progress in testing path planning and control algorithms, perception testing is still primarily limited to high-bandwidth data recording and playback. This session introduces simulation tools and techniques that augment data playback with simulation that replicates sensors and environments with enough fidelity to test perception algorithms in the lab.

10:40 - 11:10

Break

11:10

Pushing the boundaries – simulation vs. the real world

Dan Atsmon
CEO
Cognata
ISRAEL
The greatest challenge for simulation is finding the matrix that compares it to real life. In this session, Danny will present a mathematical matrix that defines this relationship and will show how a proper simulation can be constructed based on deep learning techniques. He will also supply live examples of the Cognata simulation platform.

11:35

Keeping it real: using simulation for AV certification

Kirsty Lloyd-Jukes
CEO
Latent Logic
UK
The presentation will provide an introduction to the OmniCAV project, a groundbreaking, multi-year R&D initiative supported by the UK Government to develop a holistic simulation system that enables 'AVs for all'. This project is addressing the most interesting challenges in AV testing, including: Can you use a simulation to certify an AV is safe to drive on real roads? What about different road environments, like rural roads vs. crowded cities? How can AV developers protect their IP but still get the regulators on board? Project partners are: Latent Logic (lead), Admiral, Aimsun, Arcadis, Arrival, Oxfordshire Council, Ordnance Survey, RACE, WMG and XPI.

12:00

Driver-in-the-loop applications with sensor fusion to accelerate ADAS/AD development

Roberto De Vecchi
Product development manager
VI-grade
ITALY
Ram Mirwani
Director, global business development, ADAS
Konrad Technologies
GERMANY
As ADAS/AD functionality gains adoption slowly yet surely, the jury is still out on what type of testing is required and, more importantly, how much testing is required. With governmental and focus groups working together on this topic all over the world, OEMS and Tier 1s continue to develop and test ADAS and AD functionality primarily using drive tests and miles on the road as de facto test methods. The paper will discuss how simulators combined with sensor packages for ADAS/AD can be used together in a lab to robustly verify ADAS/AD functionality as a pre-step to ground truthing.

12:25

Real-world 3D road scenario corpus for automated driving simulation

Dr Chang Yuan
CEO
Foresight AI Inc
USA
We present a novel approach for generating realistic and comprehensive road scenarios for driving simulation. The road scenario consists of high-definition road map and 3D trajectories of moving objects (e.g. vehicles, bicycles, pedestrians). Both HD map and motion trajectories are captured by our 3D sensor system from the real world, and processed by computer vision algorithms at high accuracy (5cm level). We are building an extensive scenario corpus of on-road behaviors, including unprotected turns, lane changes, merges/exits and pedestrian traffic. Users can call our web APIs to search and download scenario data in the OpenDrive/OpenScenario format into driving simulation environments.

12:50 - 14:00

Lunch

Room B Test, Verification & Validation Methodologies
14:00 - 18:15

14:00

How to calibrate and test ADAS and AD end-of-line

Thomas Weck
Global segment manager
AVL List GmbH
AUSTRIA
ADAS and AD systems require large-scale testing and validation before vehicles can be released onto the market. While new development processes focus on extensive scenario testing in simulation to cover billions of test miles, vehicle-level testing is important to address integration and confirm the robustness of the sense-plan-act chain. One necessary prerequisite is that all sensors be aligned relative to the vehicle coordinate system. Dürr and AVL have partnered up to consistently transfer testing know-how from development into the end-of-line testbed environment, with the goal of enabling complex sensor calibration and functional testing in manufacturing.

14:25

Increasing reliability and efficiency of ADAS data collection campaigns

Alexander Noack
Head of automotive electronics
b-plus GmbH
GERMANY
Testing autonomous systems requires a tremendous number of test vehicles in order to cover the relevant mileage. How can we manage the complexity of these tests? Sensor makers have to ensure that the test vehicles always operate properly, the test systems are configured correctly and the latest sensor software versions are installed. Test drivers sometimes cannot manage the complex test setup with different loggers, data converters, hundreds of cables, etc. An efficient test drive campaign can save a lot of money if it is easy to manage. A central, intelligent management system for test drive campaigns would be desirable.

14:50

A regulation-compliant safety framework for the approval of automated vehicles

Dr Houssem Abdellatif
Global head autonomous driving and ADAS
TÜV Süd
GERMANY
Currently there are no general regulations or methods for certification or approval of automated vehicles. However, many use cases or initiatives are struggling to operate automated vehicles on public roads. TÜV Süd has developed a universal framework that copes with the heterogeneous local regulations and provides a unified method for the assessment of automated vehicles. This framework considers local roadworthiness regulations, as well as functional safety and cybersecurity, and can therefore be applied in any region in the world. TÜV Süd has enabled ambitious projects to be successful in operating automated vehicles on public roads, without any safety issues.

15:15

Defining and assessing Level 4/5 AV capabilities through physical testing

Niels de Boer
Program director, CETRAN
Nanyang Technological University
SINGAPORE
CETRAN is assessing autonomous vehicles to support the issuance of AV licenses in Singapore. As part of the assessment, not only is safety considered but also the capability to drive in conformance with traffic rules, and with capabilities similar to a human driver and the requirements for the awarding of a driver's license. However, driver's license requirements are written in a way that is hard to interpret using normal engineering standards. The presentation will show how the minimum capabilities required for the assessment are defined, and how tests are defined, executed and assessed to confirm adherence to these requirements.

15:40 - 16:10

Break

16:10

Test cases for safety assessment of autonomous vehicles

Erwin de Gelder
Research scientist
TNO
NETHERLANDS
In view of recent developments in autonomous vehicles (AVs), the need arises for an efficient AV road-approval procedure. To this end, a safety assessment framework is proposed by CETRAN in Singapore that employs virtual and physical tests. For the validity of the assessment, the selection of relevant and realistic test cases is crucial. In this paper, a methodology for deriving test cases is presented. Additionally, many examples are shown because the test cases are currently being used to assess the safety of AVs that are (to be) deployed in Singapore.

16:35

Using portable scenarios and coverage metrics to ensure AV safety

Yoav Hollander
Founder and CTO
Foretellix Ltd
ISRAEL
It is now common practice to use scenarios as one of the main ways to ensure AV safety. The presentation will emphasize the need for scenarios to be portable across the various execution platforms used (test tracks, specific simulators, etc.), the various stakeholders (OEMs, subsystem creators, regulators, etc.), various use modes (fully random and deterministic) and so on. It will also discuss how coverage and grading metrics play a crucial role in defining scenarios, evaluating the results and ensuring safety.

17:00

Safety assessment of automated driver assistance systems using reliability analysis

Maximilian Rasch
PhD and engineer
Daimler AG
GERMANY
Advanced driver assistance systems (ADAS) are being increasingly focused on by researchers and industries as more and more vehicles are equipped with such technology. Testing and validation are essential to reach this goal and release ADAS. Several papers have stated that the mileage required to prove the probability of failure of the system is impossible to reach in field operational tests. Statistical methods such as Monte Carlo simulation combined with software-in-the-loop (SiL) simulation may help to overcome this limitation. The field of reliability analysis provides algorithms and approaches that can be applied to assess ADAS.

17:25

Safe autonomous driving: ASTERO pedestrian target and 6D Target Mover

Dr Igor Doric
Executive director
Messring Active Safety GmbH
GERMANY
This presentation will introduce ASTERO, the latest-generation dynamic pedestrian target. Within the TARGETS research project, which was funded by the Federal Ministry of Economic Affairs and Energy (grant number KF2122308DB3), Messring worked in cooperation with CARISSMA Technische Hochschule Ingolstadt on the development of a novel pedestrian target. Based on previous research results, ASTERO is now focused on realistic human motion while providing the required robustness and usability for AEB tests on proving grounds. The presentation will also include the 6D Target Mover test system, which is currently installed on a proving ground in Germany.

17:50

Application of scenario-based testing to automated driving systems

Tim Edwards
Senior consultant, CAV technologies
Horiba MIRA Ltd
UK
New CAV applications must be robust to withstand increasingly complex driving situations and diverse environments. The development of methods for the identification and structuring of these potential test scenarios remains a very active research topic. This paper draws on two UK-based collaborative projects, SAVVY and Human Drive, which address L2 and L4 applications respectively. Specifically, we reflect on the experiences from applying state-of-the-art methods to these projects, and mapping system requirements to comprehensive sets of test parameters and scenarios. A further UK project, VeriCAV, has started this year to further develop this work, including the automation of these processes.

Day 2: Wednesday 22 May

Room A V2X, 5G & Connectivity
09:00 - 13:40

09:00

Bringing 5G to market requires innovative products and strong partnerships

Mike Peters
Executive vice president and president connected car division
Harman International
GERMANY
In the era of the Internet of Things (IoT), connectivity is a foundational element of next-generation connected and autonomous vehicle technology. It is an enabler for improved vehicle safety and an enhanced user experience. Consumers, regulators and law makers need to trust that these technologies are reliable, secure and safe. To achieve this, the upcoming 5G network infrastructure will provide best-in-class connectivity that will deliver a range of enhancements including higher bandwidth, lower latency and improved coverage. 5G is quickly emerging as the preferred industry solution for the next decade. Bringing 5G to market requires experience, innovative products and strong partnerships.

09:25

Autonomous driving: how to network complex IoT landscapes?

Oliver Bahns
Head of business area connected mobility
T-Systems International GmbH
GERMANY
Millions of connected vehicles and traffic infrastructure elements generate huge amounts of data that must be managed and interpreted as one IoT network. Only by an end-to-end operation of this complex and safety-relevant overall system will autonomous driving be feasible in practice. In many current research and development projects, individual 'solution islands' are being created. To realize practical use cases, these isolated experience domains and working models must be networked to create IoT landscapes with a multi-partner, multi-vendor and multi-technology view. This should include legal, compliance and security aspects in addition to technical categories such as stability, availability and performance.

09:50

Intelligent intersections – solving connected vehicle safety

Dr Ryan Monroe
CTO
Street Simplified
USA
There is a limit to what a vehicle can see. The majority of autonomous vehicle collisions occur at intersections. How can intelligent infrastructure help? The presentation will explore case studies of AV collisions and why they happened, and look at the broader trend of collisions in general and what sets AVs apart. It will examine real videos of near-miss events, and give examples of common accident types, why they happen and how they can be predicted (using computer vision). Attendees will see how to use CV on the infrastructure to map where all road users are, forecast potential safety issues and communicate to enhance safety for all road users.

10:15

Understanding V2X application testing with 3D ray tracing multi-path GNSS simulation

Ali Soliman
Technical product manager, connected autonomous vehicles testing
Spirent Communications
UK
This presentation relates to V2X application performance testing with 3D ray tracing multi-path GNSS simulation. V2X systems use accurate GNSS positioning to provide precise position information for safety. The speaker will discuss how multi-path can create errors in a GNSS receiver within urban environments, and explain how errors can vary due to the geometry of satellites and environmental conditions. The presentation will also explain how testing is crucial for the success of V2X technology, and will include details of a novel system that combines V2X emulation with an advanced GNSS simulator and propagation model, which depends on a 3D reconstruction of real life.

10:40

A test concept for testing V2X vehicles on test fields

Dr Fatih Ozel
Project manager
Oecon Products and Services GmbH
GERMANY
Cooperative intelligent transportation systems using vehicle-to-everything (V2X) communications provide opportunities for achieving sustainable transportation. However, before any V2X hardware and/or software infrastructure is fully developed and deployed, an extensive phase of testing is required. In this presentation, a test concept, which will be implemented in a motorway section of the A39 near Brunswick, is described for testing V2X systems on test fields by emulating cooperative behavior for normal vehicles in real traffic and in the vicinity of a cooperative test vehicle. This is achieved by utilizing systems such as stereo cameras and roadside stations.

11:05 - 11:35

Break

11:35

HiL testing of 802.11p and C-V2X for the connected car

Axel Meinen
Technical sales manager
S.E.A. Datentechnik GmbH
GERMANY
A key issue for highly automated and autonomous driving is the connectivity between the car itself and the surrounding infrastructure via 802.11p and cellular V2X (LTE-V). Due to the safety-relevant functions of most of the components and applications, the mandatory and complex test and validation processes require an open and flexible platform that allows developers to access, analyze and manipulate signals and data in the various implementation phases within the development process. This presentation gives a detailed overview of the various testing approaches and highlights the advantages of an open testing platform.

12:00

Vehicle-to-everything technology (V2X) – the key enabler for autonomous vehicles

Alain Vouffo
Product manager - automotive
Spirent Communications
UK
Vehicle-to-everything technology (V2X) is widely accepted as a key enabler for the autonomous vehicle. Beside the IEEE802.11p (a.k.a DSRC)-based V2X technology, cellular-V2X (C-V2X) has been gaining momentum. C-V2X provides vehicle-to-everything communication over the cellular network, based on 3GPP standards like LTE-V and 5G. Despite similarities with 11p-V2X, C-V2X comes with a range of specific test requirements and challenges that must be addressed early for this technology to deliver the expected benefits. This presentation discusses test requirements and challenges in addressing those. It highlights testing methodologies for C-V2X that ensure that new products and solutions are delivered in time.

12:25

Cooperative driving function development and testing in a virtual environment

Dr Natalya An
Business development manager ADAS and automated driving
IPG Automotive GmbH
GERMANY
Cooperative ADAS and AD functions, also called V2X applications, rely on various sensor data and reliable wireless communication. Virtual environment enables reproducible, efficient, risk-free testing of V2X applications. During early development stages, neither real radios nor virtual vehicle prototypes are necessary. To study the impact of network protocols and wireless channel properties, a network simulator is often used. In later development stages, the use of radios with full V2X software stacks is essential. This paper shows how an open integration and test platform enables model reuse and supports V2X application development and testing during all stages.

12:50

Mechanisms for resilience and robustness in vehicular networks

Muhammad Awais Khan
Researcher
Institute of Telecommunications
PORTUGAL
The UrbanSense cooperative sensing infrastructure offers efficient communications between fixed data-collecting units (DCUs) and vehicles in a smart city. Different system technologies such as wave, wi-fi and cellular can be used to capture information from distant areas. Applications of research work can include monitoring meteorological conditions, noise, air quality and citizen behavior using video cameras. Other applications could be for data dissemination for semi-autonomous driving, adaptive cruise control, touristic information and warning systems such as lane-departure warning system, accident and traffic congestion messages.

13:15

Cooperative ITS pilot deployment in Hungary to support CAD

Adam Nagy
Traffic management engineer
Hungarian Public Road Non-Profit PLC
HUNGARY
Future mobility requires more and more online information even from the road. The Hungarian Public Road company is committed to supporting this development. C-ITS deployment started in 2015 in Hungary to demonstrate the use of C-ITS to exchange data through wireless communication technologies between vehicles and infrastructure (V2I). The first C-ROADS - Harmonized C-ITS Specifications for Europe – Release 1.3 compliant RSU deployment took place in Q4 2018. Urban deployment is planned in the near future to provide testing possibilities in open-road conditions, which can be simulated and analyzed later on, for example within the Zala Automotive Proving Ground.

13:40 - 15:00

Lunch

Room A Data Management, Storage and Cloud Technology
15:00 - 18:00

15:00

Modern hybrid storage solution for sensor data and HIL/SIL simulation

Dr Stefan Radtke
Technical director, EMEA
Qumulo
GERMANY
Data rates of modern sensors are constantly growing due to higher resolutions, multiple sensor types and an increasing number of sensors per car. A typical test car today produces 20-30TB per day. Considering a fleet of 10 cars and 200 recording days, the enormous amount of 60PB must be stored, processed and archived. Other requirements are global ingest and global access for annotation, processing and other process steps. In this session we’ll discuss a modern hybrid scale-out solution that uses cloud as well as data-center implementations to address these challenges.

15:25

Need speed? Automotive datalogging at 10GBs and more

Bernhard Kockoth
Advanced development lead
ViGEM GmbH
GERMANY
The main driver for high data rates in automated vehicles is growing sensor resolution for better environment understanding. Current setups require a number of high-resolution cameras and radar systems. Compression of data is traded for safety to achieve lowest latency from sensor to drive computers – the car can drive faster! OEMs and Tier 1s require all raw sensor data to train ML on the very same data the central drive computer 'saw' when the vehicle was on the road. We faced the challenges of 10 Gigabits and more and present a handy solution for data recording and transfer.

15:50

ADAS data gathering 2.0

Richard Levy
Director
EU Platform UG
GERMANY
In the development of ADAS, data is generally collected in-vehicle and transferred to a low-cost site for labeling. The collection and transfer process wastes resources and time and creates risk. Data loses value quickly as sensors change. Sharing for fusion projects adds difficulty. Our test platform allows real-time annotation of raw data within the vehicle, and manual correction. We retain the ability to simulate multiple vehicle platforms with the same collected data. The cybersecurity implementation allows work with multiple partners on one vehicle, for example in fusion projects where camera, lidar and fusion components come from competitor companies.

16:15 - 16:45

Break

16:45

Integrated data management for efficient validation of autonomous vehicles

Franz Gaber
Program Manager Data Management & Processing Platform
CMORE Automotive GmbH
GERMANY
Integrating various stakeholders, disciplines and locations into a data management system is one of the key challenges within the development and validation of autonomous vehicles. An intelligent workflow engine is required as well as integration of, and compatibility with, big data technologies. In addition, collaboration between huge teams, e.g. for data annotation and test, and management, must be supported. The presentation will show how CMORE Automotive's modular and highly flexible data management platform addresses these needs.

17:10

High-bandwidth datalogging solution for autonomous driving

Andreas Ehrle
R&D
X2E GmbH
GERMANY
With the new bandwidth demands arising from assistance systems and autonomous driving, a new architecture for datalogging devices is needed. The solution is a distributed datalogging system with a central datalogger and additional tap devices that can be located everywhere in the car. They send the data via an Ethernet link to the datalogger. For a high-speed infrastructure, 10GBit links between the datalogger and tap devices are needed. A distributed system like this has many advantages. Tap devices for different bus systems can be chosen and installed as needed for a specific car infrastructure.

17:35

Creating an optimized storage environment for autonomous vehicles

Jason Coari
Director, high-performance solutions
Quantum Storage
UK
As organizations focus heavily on autonomous vehicle development, they are quickly learning that there is a massive volume of data rapidly growing in parallel to this activity – data that is extremely valuable and requires access in a time-sensitive manner. Within this context, it is imperative that the industry be better informed of data management solutions for this valuable data. This presentation will focus on how these organizations can create balanced storage architectures that can accelerate the ingest phase of this data from car to data center, and more cost-effectively preserve it over its lifecycle.

Room B Using Simulation for Test Scenario Validation
09:00 - 12:50

09:00

Testing and validating autonomous vehicles using traffic simulation

Dr Jochen Lohmiller
Manager microscopic simulation
PTV Group
GERMANY
Before testing connected and autonomous vehicles (CAVs) in real traffic on public test areas such as in Karlsruhe, Germany, virtual testing of those test areas using traffic simulation accelerates the development. Advanced traffic simulation models simulate all modes, such as individual human drivers, cyclists, pedestrians and different CAV behavior, which allows testing under different vehicle/driver populations. We present in a case study of how virtual tests can be applied using co-simulations between ego-vehicle simulation and a traffic simulation in the example of signal communication (V2X).

09:25

Massive simulation: recent achievements and perspectives

Thomas Nguyen That
Head of automotive domain
AV Simulation
FRANCE
Simulation has a key role to play in demonstrating the safety of autonomous vehicles, enabling billions of miles of virtual driving. This requires dedicated tools and methodologies, scenarios and models for the environment, sensors, and vehicles that are highly representative of the real world. AV Simulation is developing SCANeR studio, a versatile engine for automotive systems simulation. In this presentation we will present our latest experiences with massive simulation and explain how we addressed the challenges of model representativity, scenario generation, massive parallel execution and metrics computation.

09:50

Integration of simulation tools in validation processes

Ahmed Yousif
Software design engineer
Valeo Schalter und Sensoren GmbH
GERMANY
The presentation talks about the use of simulation tools to aid the validation of autonomous systems and algorithms. These systems can include lidars, cameras, ultrasonics and radar sensors. The use of simulation tools will help to reach the mileage required to validate the driving assistance systems in Level 4 and 5. In addition, the use of these simulation tools is needed where the artificial intelligence algorithms are exposed. The presentation will include some demos for lidars and ultrasonics-based algorithms such as full automatic parking.

10:15

The driver-in-the-loop simulator in the ADAS development and validation toolchain

Jelle van Doornik
Product manager ADAS
Cruden
NETHERLANDS
All car manufacturers are investing heavily in ADAS and AD development; billions of test kilometers are driven in simulation, and proving grounds are built specifically for the development and validation of (semi-)autonomous systems. A driver-in-the-loop simulator is effective to save time and cost, and speed up driver or passenger acceptance. Corner cases with different scenarios and conditions can be evaluated quickly. The challenge is to create an open architecture for engineers to work with in the development, and have standardized interfaces and content available to perform quick validation. This presentation explains how the driver-in-the-loop simulator fits in the total toolchain.

10:40 - 11:10

Break

11:10

Machine learning and a systems approach to creating autonomous vehicle test cases

Siddartha Khastgir
Principal engineer
WMG, University of Warwick
UK
To prove automated driving systems are safer than human drivers, it is suggested that they will need to be driven for over 11 billion miles. However, rather than the number of miles it is the quality of those miles that is important. To find the 'interesting test cases', a novel machine learning and systems-engineering-based approach has been developed to identify system failures, applied to low-speed automated driving systems (Pods). The approach also helps identify test cases from simulation environments that need to be carried over to real-world testing.

11:35

Real, robust and comprehensive – smart simulation for AV validation

Laksh Parthasarathy
Business head - automotive (autonomous validation)
Tata Consultancy Services
USA
To ensure the safety of AVs, it is said that a vehicle needs to be validated by driving over 11 billion miles. However, beyond the number of miles that need to be racked up, it’s the miles where the vehicle encounters incidents that matter. Physical testing is not economically viable – we have to consider simulations. Some challenges with simulation includes identifying 'as many' edge cases as possible – where the software is likely to fail – along with an accurate representation of the world. In this paper, we explore unique techniques that could be leveraged to make simulations real, robust and comprehensive.

12:00

Physics-based simulation for ADAS and autonomous testing

Chris Hoyle
Technical director
rFpro
UK
Physics-based simulation allows us to model and simulate the real world and the sensors that feed perception systems. Taking a physics-based approach to simulation ensures that the results are not just convincing for humans, but also for machine vision systems, which require far greater levels of fidelity to deliver behavior that correlates with real-world testing. rFpro will demonstrate the techniques being adopted on UK Government- and EU-funded projects in which it is collaborating, aimed at delivering a roadmap to regulatory approval for Level 4 and Level 5 autonomous vehicles.

12:25

Vehicle-in-the-loop: validation of automated driving functions with virtual elements

Paul Prescher
Team manager
IAV
GERMANY
Future automated driving functions are supporting ever greater parts of driving scenarios in increasingly complex situations. This calls for new approaches to safe and resource-conserving testing and validation. To extend the test process to cover complex and safety-critical systems, such as automated driving functions, IAV has developed an approach that combines a real-world test vehicle with virtual elements for reproducible, safe and resource-saving tests. This opens up possibilities for validating automated driving functions both in the early as well as in the late phases of the development process.

12:50 - 14:00

Lunch

Workshop - dSPACE

Further information to follow shortly. Check back soon for details.

Room B Using Simulation for Test Scenario Validation Cont...
16:00 - 18:10

16:00 - 16:30

Break

16:30

Certification of autonomous vehicles in synthetic environments: initial findings

Timothy Coley
Product specialist
XPI Simulation
UK
XPI Simulation, Warwick University and Thales are undertaking a feasibility study to examine the certification of autonomous vehicles in synthetic environments. The research aims of this study include: identifying resolution, rate and type of data required to represent the virtual world with a view to informing standardization activities; understanding the security vulnerability of a synthetic system being used in this manner; developing a certification approach that would achieve the expected repeatability and robustness within the synthetic environment to test autonomous vehicles. This presentation will cover initial findings from the research activity.

16:55

Development of model predictive motion planning and control for AD

Vishwas Sharma
Project Engineer, CAE
Applus IDIADA
SPAIN
The presentation will discuss generation of optimal trajectory for autonomous vehicles, advanced control guidance for autonomous vehicles, and real-time validation in virtual environments. The aim of the paper is to present a system that can generate a real-time online optimal feasible trajectory to maximize comfort, stability and travel efficiency of autonomous vehicles while overcoming their physical constraints. In order to validate and tune the algorithms, several dynamics maneuvers and realistic urban driving scenarios are simulated. In the second half of 2019 it is planned to test the algorithms on a driving simulator.

17:20

Iterative real drive simulation in HILS

Sreeraj Arole
HiLS technical lead
Tata Elxsi
UK
Vehicle simulation in a lab environment has played a key role in development and testing in the automotive industry. However, even when actual vehicle parameters and closest real-world scenarios are incorporated in the lab environment, there are several situations where a real vehicle is needed for testing/calibrating/recalibrating vehicle functionalities. This paper presents an effective way of using the network log from a vehicle combined with external sensor simulation and plant model running on a high-precision real-time simulator and control software to achieve a repeatable robust simulation environment. This enables a drive cycle with multiple variations to be undertaken to assess the performance and for calibration.

17:45

Open simulation interface as an enabler for virtual sensor models

Kmeid Saad
Scientific researcher
Hochschule Kempten
GERMANY
In the process of developing advanced driver assistance systems (ADAS), relying on virtual environments for the development process provides the advantage of entirely reproducible and controlled environment conditions. However, the existence of various function developers and simulation environments imposes the need for a generic and standardized interface. To tackle this issue, the open simulation interface (OSI) is created. OSI is a generic interface for the environment perception of automated driving functions in virtual scenarios. This paper demonstrates, with the help of OSI, the virtual implementation/simulation of a 'semi-physical camera model' and a 'behavioral multi-sensor model' in various simulation environments.

Day 3: Thursday 23 May

Room A Open Road & Real World Testing
09:00 - 12:50

09:00

Integration of the StreetWise scenario database in AVL virtual testing tools

Sytze Kalisvaart
Project manager StreetWise
TNO
NETHERLANDS
Recently, the StreetWise scenario database has become available within the AVL toolchain. This data-driven cloud-based scenario database provides insight in real-world scenario classes, their exposure and variation. Seamless integration with the AVL test planning tool allows test engineers to select scenario classes and parameter ranges and define their test plans with real-world percentiles of observed scenarios. Test cases are expressed in OpenDRIVE and OpenSCENARIO and can be run through Model.CONNECT and Vires VTD. Through StreetWise real-world statistics and AVL test management tooling, the question of "have we tested enough?" can be addressed for validation of automated driving.

09:25

Catalonia Living Lab – CAV testing on public roads

Stefan de Vries
Project manager
Applus IDIADA
SPAIN
Since its launch, Catalonia Living Lab has steadily expanded its abilities related to development and testing of connected and automated vehicles (CAV). In order to understand clients’ needs related to CAV testing on public roads, several pre-studies, market research and interviews with 30 potential clients were conducted, resulting in the definition of 12 universally applicable objectives. These objectives guide the current deployment of CAV testing services on Catalan public roads, as well as similar initiatives undertaken by international partners. If you are interested in CAV testing on public roads or development of CAV testbeds, this is your topic.

09:50

Successful methods for open-road autonomous vehicle validation

Dr Wolfgang Nickel
Senior manager
DTC GmbH Navigation & Security Solutions
GERMANY
Autonomous vehicle engineers need robust and repeatable methods to validate vehicle performance on the open road in real time. This presentation will share how ground truth data from an inertial navigation system provides a reference for vehicle position, orientation and dynamics that is needed in difficult urban test areas. We will share a number of current examples where this technology is being used effectively by automotive manufacturers and sensor suppliers.

10:15

Open-site trialling of automated vehicles at the Swiss Transit Lab

Dominique Müller
Managing director
AMoTech GmbH
SWITZERLAND
Conveniently located near Zurich Airport, the Swiss Transit Lab incorporates automated vehicles into the local public transport system. For the population, this means involvement in the development and trialling of various first/last-mile services. For vehicle manufacturers and component suppliers, this means early field validation of new technology. Fast project execution thanks to short paths in one of the smallest Swiss cantons, and excellent cooperation with the relevant authorities at all levels, are the trademark of the Swiss Transit Lab, which is run jointly by Public Transport of Schaffhausen and AMoTech.

10:40 - 11:10

Break

11:10

EasyMile's way to safe autonomous driving

Dr Olivier Lefebvre
Product manager
EasyMile
FRANCE
EasyMile is developing an autonomous driving solution that is currently running on more than 70 operational shuttles worldwide and is being integrated on other types of vehicles for people or goods transportation. In this talk we will present the key points of EasyMile’s navigation solution, and also provide insights into the company's approach to the development of a product that constantly remains operational and safe and that is also continuously evolving to solve new transportation use cases.

11:35

MUEAVI: the future autonomous vehicle validation infrastructure for smart city

Dr Yun Wu
Research fellow
Cranfield University
UK
Validation of driving model, human factor model and traffic model is key for the future of the autonomous vehicle industry. Most previous infrastructures have mainly focused on validating those models separately either in a physical or virtualized infrastructure. However, the physical infrastructure cannot cover all the possible scenarios, nor can the virtualized infrastructure easily accommodate a realistic driving model. To achieve comprehensive validation in smart city, the Multi-User Environment for Autonomous Vehicle Innovation (MUEAVI) has been built. With reference to multiple research projects, the latest research solutions for autonomous vehicle validation are presented.

Room A Test and Validation of LiDAR, Sensors & Mapping Technology
12:00 - 17:50

12:00

Sensor simulation plug-in for radar, lidar, ultrasound and camera

Dr Dennis Stapp
Program manager
ITK Engineering GmbH (Bosch)
GERMANY
About 40 unique sensors are required for environment and situation recognition in highly automated driving. This enables high-level simulations for virtual sensor systems, automated selection and optimization of relevant scenarios. ITK Engineering has developed the raytracing framework to enhance complex environment and vehicle simulations. This co-simulation uses custom rendering engines from the visual effects industry and provides whitebox interfaces for sensor models and raw data generation – independent from manufacturer. Parallelization and GPU computing optimize cycle times for real-time, closed-loop simulation including multi-sensor systems. This enables consistency of tests and scenarios across development phases, and harmonizes models across toolchain boundaries.

12:25

Frequency domain automotive radar verification: enabler of autonomous driving deployment

Dr Kasra Haghighi
CEO
UniqueSec
SWEDEN
Radar sensors play a safety-critical role in autonomous driving (AD) and advanced driver assistance systems (ADAS). Thus their reliable functioning needs to be verified by smarter, less risky and more efficient methods than millions of kilometers of test driving. Radar target simulator (RTS) enables evaluation of radar sensors, ADAS and AD for their performance, availability and reliability on a stationary car. RTS sits in front of the vehicle or car radar inside the lab and creates the illusion of any test scenario, even dangerous and improbable scenarios, for the radar by emulating electromagnetic emissions analogous to real radar reflections.

12:50 - 13:50

Lunch

13:50

Millimeter-wave distributed radar modules for autonomous driving

Mitsuru Kirita
Munifacture
Mitsubishi Electric Corporation
JAPAN
Various sensors for automobiles are studied and developed actively to realize autonomous driving. For autonomous driving, the sensors must reliably detect road structures, vehicles and pedestrians. The front sensor must be able to separate multiple targets at long distances with high resolution in azimuth and elevation. We have been developing TRX modules for millimeter-wave radar for autonomous driving, and propose a technique to realize high-resolution angle measurement performance with the virtual antenna aperture by distributing multiple TRX modules. In this presentation we will show this new technology and the field test results.

14:15

Physics-based lidar simulation

Jordan Gorrochotegui
Senior technical product manager
Siemens
NETHERLANDS
Reaching level SAE autonomy is a big challenge that the automotive industry as a whole is trying to address. To be successful, simulation will need to play a key role as part of a robust and agile V-cycle. In this presentation we focus on lidar systems, and the importance of having physics-based lidar simulation to help develop robust and safe ADAS systems and autonomous driving capabilities. Simulation can help sensor manufacturers develop the next generation of sensors for AV vehicles, and it can also help OEMs make sure that their AV systems are robust, safe and reliable.

14:40

Autonomous vehicle navigation using single map in non-snow and snowstorm conditions

Dr Umar Zakir Abdul Hamid
Senior autonomous vehicle engineer
Sensible 4
FINLAND
Sensible 4's autonomous driving technology provides a solution to extreme weather conditions. In this work, the algorithm was tested in the Arctic Circle in a prototype vehicle, Juto, where it navigated autonomously in non-snow and snowstorm conditions using the same map. In both scenarios, our system provides desirable autonomous navigation, thus rendering a solution to the extreme weather issue. The system can also be utilized for use in other bad weather conditions, where robust algorithms are required to aid the autonomous vehicle perception and mapping modules. Thus, it promises an all-weather AD experience.

15:05

End-to-end sensor modeling for lidar point cloud

Mohamed ElSobky
Software validation expert
Valeo
EGYPT
The major problems with relying on machine learning to learn a self-driving car's control software rules from data are that the amount of training data required to generalize a machine learning model is big, lidar data annotation is very costly, and virtual testing and development environments are still immature in terms of physical properties representation. We propose a deep learning-based lidar sensor model, a method that models the sensor echos, and a deep neural network to model echo pulse widths learned from real data. We benchmark our model performance against comprehensive real sensor data and very promising results are achieved.

15:30

SceneScan: real-time stereo vision for fast 3D sensing

Dr Konstantin Schauwecker
CEO
Nerian Vision GmbH
GERMANY
Autonomous vehicles must be able to sense their 3D environment. Today, lidars are widely used for this task. However, the low vertical resolution, low frame rate and high costs have motivated the development of alternative sensors. Stereo vision is a promising technology that can provide dense outdoor measurements. The image processing is, however, very computationally demanding. This is why Nerian developed an FPGA-based stereo image processor: SceneScan. With SceneScan it is possible to sense depth data at 100 fps, or 30 million 3D points per second. At the same time, the system is small and low power, making it ideal for vehicle integration.

15:55

A new ultrasonic sensor for pedestrian detection

Dr Peter Nauth
Professor
Frankfurt University of Applied Sciences
GERMANY
The presentation discusses a new approach for pedestrian detection by means of a sophisticated analysis of ultrasonic signals. The main objective is to enable driver assistance systems in vehicles to recognize whether an obstacle in front is a pedestrian or a car. The sensor evaluates ultrasonic signals backscattered from the obstacle and extracts task-specific features that are used to differentiate between pedestrians and cars.

Room B Robust Test, Verification and Validation Methodology
09:00 - 14:00

09:00

Connected datalogging and analytics

Dr Marina Kreutz
Data scientist
FEV Europe GmbH
GERMANY
Markus Kremer
Data scientist
FEV Europe GmbH
GERMANY
The huge amount of data collected by loggers is a special challenge in the field of data analytics for autonomous driving scenarios. On one hand, the measured basic data is transmitted via network dataloggers. On the other hand, the amount of video data is too big to be transmitted via mobile connections. Since the vehicle data is generated in a proprietary unstructured raw format, an appropriate data and storage structure must be defined first. Particular attention lies on interfaces between the loggers and the back end, which are realized by available streaming services. Another challenge is the processing of an enormous quantity of data to adequately prepare the raw data for further analysis.

09:25

Data acquisition and analysis for efficient testing and validation of ADAS/AD systems

Michael Luxen
Technical specialist
FEV Europe GmbH
GERMANY
Highly and fully automated driver assistance systems place new demands on test and validation solutions. High-precision dataloggers are required to support these increasingly complex systems in the ADAS/AD area. The validation and optimization of automated driving functions requires time-synchronous and highly precise log data from vehicle sensors such as ultrasound, radar, lidar and video, and vehicle bus communication like CAN(-FD), FlexRay or Ethernet in real driving situations. This data can be used for playback, analysis, testing, simulation and validation. The big data process used (acquisition, preprocessing, handling and use cases) was developed and applied within the European-funded L3Pilot project. An outlook shows the further challenges for datalogger solutions.

09:50

Autonomous vehicle teleoperation through the lens of systems engineering

Amit Rosenzweig
CEO
Ottopia
ISRAEL
In the absence of fully autonomous vehicles, which are many years away, safe deployment should require maintaining a human in the loop. This human in the loop can be remote, as long as the method for her to intervene is sufficiently safe. Using systems engineering and automotive safety standards as an approach, we present different characteristics that a remote intervention system should have, along several dimensions: robustness to poor connectivity and network latency, added layers of redundancy when a remote human is in control, 'built-in' cybersecurity.

10:15

Parking cars autonomously

Dr Brian Holt
Head of autonomous driving and parking
Parkopedia Limited
UK
Autonomous Valet Parking (avp-project.uk) is a two-and-a-half-year InnovateUK-funded project to develop maps suitable to support navigation and localization within GNSS-denied environments. A specific goal is to demonstrate and test these maps on an autonomous vehicle for which we are using Autoware on a StreetDroneONE. This presentation will discuss the software architecture, simulation and practical details of controlling the vehicle safely.

10:40 - 11:10

Break

11:10

Reliable lane-keeping and platooning for automated road transport

Surya Satyavolu
Founder and CTO
Sirab Technologies Inc
USA
Lane-keeping and platooning are fundamental functionalities necessary to achieve safe, scalable and high-capacity automated road transport. Although there is rudimentary lane-keeping demonstrated using currently available painted lane guides, reliability at a functional level as well as dependability and safety assurance are impossible with that kind of an approach. Similarly, although platooning has been researched, reliability is a key performance metric necessary for safety assurance as well as system-level objectives like operational efficiency and scalable capacity. We present our unique architecture for reliable platooning and lane-keeping based on radar, IMU and wireless communications meeting system-level objectives.

11:35

A safety testing protocol for automated and connected vehicle technologies

Dr Jonathan Riehl
Transportation systems engineer
University of Wisconsin-Madison
USA
The Wisconsin Automated Vehicle Proving Grounds team has developed a set of scenarios to test automated and connected vehicles on a closed course to simulate real-world conditions that AVs must meet in order to be viable. These edge cases being tested are the precursor to a validation program for vehicles to be certified to drive on public roads. Information in the presentation will be drawn from the current AV Shuttle pilot program where an automated shuttle is operating on public roads in Madison, WI and communicating with traffic signals. Scenario testing development at our MGA closed-course testing facility will also be discussed.

12:00

Automated long-term validating of cloud-based driver assistance functions

Uwe Gropengiesser
Team manager active safety
IAV GmbH
GERMANY
Modern cloud-based driver assistance functions are used to increase safety on the streets and will be a necessary part of future developments in autonomous driving. Developing these kinds of functions requires testing and validating the function at any development state and beyond. To provide long-lasting reliability even between different vehicle types and software statuses, a long-term approach for testing cloud-based driver assistance functions is needed. As a possible solution, virtual instances of hardware modules simulate vehicle behavior and can be automatically tested over a long time. This ensures durable functional reliability even for hybrid software states.

12:25

Functional testing of autonomous vehicle decision module

Adel Djoudi
Research engineer
IRT SystemX
FRANCE
Motion planning is a major component of any autonomous driving system. The safety assessment of such components requires a formal characterization of the perception and decision mechanisms. In this context, we consider a decision module as a black box and try to determine the 'right decision', if it exists. An optimization-based oracle is created for each control function. The oracle allows each scene in the environment to be linked to the desired decision regardless of the black box. The black box and the oracle are run on several critical functional scenarios. In output, a report on decision making is provided.

12:50 - 14:00

Lunch

Please Note: This conference programme may be subject to change

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