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2017 Conference Program

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Day 1

Tuesday 20 June

09:30 - 12:30 - Keynote Presentations – Software Development & AI For Autonomous & Self-Driving Vehicles

Selenium and Caesium – software elements of driverless cars
Paul Newman, founder, Oxbotica, UK
Selenium and Caesium are Oxbotica’s solution to this remarkable set of challenges. Selenium is our platform-agnostic autonomy operating system, which provides autonomy and deep scene understanding with any combination of laser or vision sensors, with or without prebuilt maps. Caesium is our fleet coordination system, which handles fleet configuration, data and learning sharing and meta information. This presentation will explain how these 'elements of autonomy' have been architected, built and deployed in fleets of vehicles and OEM vehicles.

The open road to autonomous driving
Dan Cauchy, general manager automotive, The Linux Foundation, USA
The autonomous driving market continues to heat up as auto makers race to acquire tech companies or forge partnerships with suppliers who can accelerate and expand their development efforts. This flurry of M&A activity over the past year is being driven by the realisation that the software and hardware required for autonomous driving is too complex for any company to develop alone. Although this is a step in the right direction, an open-source platform for auto makers to share information such as map data, miles driven and scenarios tested could speed up production cycles and decrease time to market. This presentation will discuss the impact that open source could have on autonomous driving, and how collaboration could benefit auto makers without hindering competition.

An open-source software platform for autonomous driving systems: its success and its difficulties
Lukas Bulwahn, software engineer - software infrastructure group, BMW Car IT, GERMANY
Since 2013, Tilmann Ochs, Daniel Wagner and Lukas Bulwahn have been working on research activities to define, motivate and implement a software platform for autonomous driving systems using custom-off-the-shelf open-source software. In 2014 they presented their understanding of future automotive software and their plans to use pre-existing open-source software for implementation of a collaborative automotive base platform at various automotive software engineering conferences. Now, three years later, it is time to re-evaluate this effort and critically review its progress, its successes and its failures. In this talk, the engineers present their main assumptions in 2013, and give some insights into ongoing software development activities supporting their ideas. Then, they evaluate to what extent they were successful in implementing these ideas, to what extent they could improve their understanding, and how this has refined their plans. On the technical side, they discuss the factors that influence the selection of the communication middleware and the underlying operating system of an automotive platform for autonomous driving systems. On the business side, they discuss the economics of automotive software development and the implications for the use and development of open-source software in the automotive domain.

AI - The Answer to Autonomous Driving and Transportation
Serkan Arslan, Director of Automotive, Nvidia, GERMANY
Artificial Intelligence: What seemed like science fiction just a decade ago is now just science. In the next few years, AI will transform every major industry pertaining to the advancement of humankind. Soon, autonomous cars will reduce congestion and improve road safety. And the tools to embrace these improvements will be new infrastructures and vehicle computing platforms leveraging sensors such as cameras, radars, and lidars. Most importantly, this suite of sensors and tools includes AI for various levels of autonomous driving and transportation both inside and outside of cities. Discussed will be how AI algorithms leveraging structure from motion, sensor fusion and deep learning will help perceive the environment, create HD maps, and not only predict traffic behavior but what to do to control it.

14:00 - 17:30 - Solving Complex Software Challenges for Autonomous Transportation

Compete and succeed with IIoT architectures in autonomous cars
Bob Leigh, director of market development, Real-Time Innovations, USA
Dr Alexander Leonhardi, senior manager, ETAS, GERMANY
Autonomous vehicles are quickly becoming reality. Unfortunately, the existing industry standards can’t keep pace. New players and standards are driving OEMs, Tier 1s and electric car makers to adopt unfamiliar technologies and approaches. In particular, the DDS (Data Distribution Service) standard specifically addresses autonomy in other industries. It now presents an alternative architecture and communication framework for complex, safety-critical automotive designs. This session will review how DDS can solve the most challenging use cases in new car architectures. It will also outline how this IIoT standard will complement or impact AUTOSAR standards.

End--to-End Software Solutions for Automated Driving
Dr Haotian Wu, Software Technical Lead, Intel, USA
Automated driving will enable better, safer and more efficient mobility. However, the automated driving technology heavily relies on reliable, functional, safe, intelligent and comprehensive software that requires cross-platform software development. Cross-platforms include computation, connectivity and the cloud. Facing such complexity, an end-to-end software solution can ensure seamless inter-operation across platforms and functional teams. The end-to-end software solution will facilitate data scientists, system designers and software developers to deliver autonomous driving software stack and algorithms. The end-to-end software solution bundles computer vision, deep learning and sensor data labeling, optimization libraries and compilers in a functional and safety-compliant way.

The ecosystem of self-driving by AImotive
Árpád Takács, outreach scientist, AImotive, HUNGARY
AImotive has developed a full-stack software suite for fully autonomous self-driving cars, providing a hardware-agnostic, scalable solution. Based on the idea that self-driving cars should mimic human behaviour, the algorithms rely on cameras as primary sensors for accomplishing the tasks of object recognition and classification, localisation, decision making, trajectory planning and vehicle control. The software engine components are aided by an extensive toolkit to accelerate the training and verification, including calibration, data collection and augmented data generation, semi-supervised annotation, and a real-time, photorealistic simulation environment. The presentation will provide an insight into the ecosystem of these software components.

The open standards enabling vision processing in ADAS
Illya Rudkin, principal software engineer, Codeplay Ltd, UK
For cars to control or drive themselves, they must 'see' their surroundings in a fast, safe and secure way. Recent advances in computing hardware make vision algorithms and machine learning practical for automotive systems. Open software standards allow competition and innovation in a supply chain, providing substantial advantages to all involved. Open standards enable innovators to develop software for vision or deep learning with flexibility of different hardware. Codeplay will present the virtues of open software standards OpenC and its growing use in automotive, plus how its implementation stack includes open standard SYCL and Google Tensaflow to enable machine learning solutions.

The pedestrian challenge
Michael Hartmann, researcher, Virtual Vehicle Research Center, AUSTRIA
When looking at 'how to make future automated vehicles save', the topic of trajectory planning plays a key role. How can safe trajectories be found for autonomous vehicles? Motion planning for automated vehicles moving in traffic situations in general requires decision making based on incomplete and uncertain knowledge of the situation. The importance of trajectory planning is most evident for situations with vulnerable road users. What happens if some assumptions for planning are uncertain? It is proposed to use methods for uncertainty quantification in motion planning considering the fact that the environment can't be modelled.

Addressing software complexity in ADAS and autonomous driving
Christopher Wild, technical director - CoherenSE, Altran, FRANCE
The future of automotive is increasingly defined by intelligent software. Such software will support increasingly sophisticated algorithms and services for ADAS, with the goal of widespread adoption of autonomous driving. Creating the required software, integrating and testing it, and managing it in-field present a challenge of complexity. Addressing this complexity requires a change in culture and architecture in the automotive world. In this presentation, we introduce CoherenSE and VueForge for ADAS verification, which provide an approach to software architecture targeting the management of complexity in development, integration and test of ADAS.


Day 2

Wednesday 21 June

09:00 - 12:30 - Solving Complex Software Challenges for Autonomous Transportation - Continued

Making future autonomous transportation a reality – safe and secure
John Round, ADAS software manager, NXP Semiconductors, GERMANY
As the world’s largest supplier of automotive semiconductor solutions, NXP is driving innovation for safe and secure vehicle autonomy. In this presentation NXP will discuss the prevailing software and systems architectures that are evolving to address the challenges of fully autonomous design. In addition, NXP will review emerging software technologies in areas such as tooling, AI, middleware and testing, and their potential contribution to mass-market deployment of safe autonomous vehicles. NXP will also share its unique perspective on the challenges and opportunities that exist to truly deliver our collective safe, secure and autonomous transportation future.

Robot to road – future software architecture for autonomous vehicles
Dr Raul Rojas, director, Dahlem Center for Intelligent Systems, Freie Universität Berlin, GERMANY
The session will review possible software architectures for autonomous vehicles, based on experience with other kinds of mobile robots. One important aspect is the interplay and fusion of different kinds of sensors, and also the coordination between 'cognitive' and reactive actoric modules.

Revision conformity, corporate governance and compliance in software calibration processes
Thomas Wambera, affiliate business manager, AVL Deutschland GmbH, GERMANY
The complete documentation of software application responsibilities, calibration processes and related data, as well as the possibility to evaluate these according to different aspects in terms of the right-to-the-right, is crucial when developing ADAS systems. By combining established and controlled workflows and measures for IT security, revision certainty and conformity with ISO 27001, European law (eIDAS regulation) and usability for the implementation of ISO 26262 can be achieved. The speech gives an introduction to legal and technical requirements for the documentation, and is intended to provide an awareness of the complexity and dependencies in the software application process.

Mastering time coherency and execution performance in your AD software
Nicolas Du Lac, CEO, Intempora SA, FRANCE
As embedded software in intelligent vehicles becomes more and more complex, because the number of ECUs and parallel software tasks has increased tremendously, it becomes critical to set up mechanisms that can handle time coherency among these software tasks and data streams. In this presentation we will address some of the software design concepts in the RTMaps framework that allow time coherency to be mastered in multi-thread and distributed architectures while achieving unprecedented execution performance in applications for autonomous driving, from the early stages of applications prototyping down to the execution on the most recent ECU architectures.

The nervous system of an automated driving vehicle
Peter Brink, principal engineer, PolySync Technologies Inc, USA
There are many discussions about the 'brain' of an automated driving vehicle (ADV), looking at the technology required to perform decision making in real time. Little has been said about the nervous system of the ADV – the mechanisms by which the environmental data around the vehicle is transmitted to and from the brain. This presentation covers the requirements for a vehicle hardware abstraction layer for the software defined vehicle. The system requirements end up making the environmental data one of the most safety-critical pieces. How that data is shared is a key factor in making this abstraction layer a requirement.

Towards autonomous driving – developing reliable automated driving features
Thorsten Gerke, automotive industry manager EMEA, MathWorks, GERMANY
Building autonomous cars requires overcoming several technological challenges. It mainly contains three elements: perception, planning and control. This paper will demonstrate how to use a model-based engineering workflow solution based on MATLAB and Simulink to develop and efficiently test automated driving features including different sensor technology such as camera, radar and lidar.

Highly automated driving on highways – reference architecture for coping with complexity
Sebastian Klaas, senior project manager, Elektrobit, GERMANY
The complexity of automated driving systems (e.g. adaptive cruise control, lane keeping assist, emergency braking, etc.) and related components has been rapidly increasing during recent years. Targeting Level 3 and above functions, like a Highway Pilot, adds another level of complexity due to the necessity for cooperation between formerly independent functionalities and additional safety needs. This talk discusses how to cope with complexity, based on a reference architecture and implementation for a Highway Pilot system.

14:00 - 17:30 - Building Resilient Software-Based Security Systems for Autonomous Vehicles

Protecting automotive sensors in connected cars: emerging trends with security vulnerabilities and software solutions
Ben Gardiner, principal security engineer, Irdeto, CANADA
The increased connectivity and complexity in modern vehicles is resulting in new risks and threats. Hackers continuously evolve attack strategies to exploit vulnerabilities and access vehicles. To address these challenges, the industry must make cybersecurity a priority by focusing on key vulnerabilities that hackers exploit. Automotive sensors' designs – the embedded computers of which they are increasingly comprised – will be part of this software solution in concert with other systems to protect connected vehicles. This session will provide an overview of current threats, hackers' motivations for attacking automotive sensors, and software security strategies to protect automotive sensors.

Lessons from the spaceship for the sedan
Frédéric Bourcier, delivery director, autonomous driving solutions, Wind River, FRANCE
As autonomous driving prototypes are being rolled out globally, the industry is developing in earnest. Safety is central. The auto industry can learn from other industries, such as aerospace and defence, with similarly tight restrictions. The industry is experiencing a wave of new innovation, and software is at the heart of this transformation. However, the development of these new autonomous systems requires a combination of mature and sound approaches as well as new ones, in order to ensure safe solutions. This presentation will cover: parallels between automotive and other mission-critical industries as they pertain to safety and security; the changing software landscape, especially with the growing trend of IoT, and how it is adding complexity to automotive systems; how autonomous vehicles can/will need to securely 'talk' with their surroundings in the smart cities of the future.

How to safeguard software in vehicles
Hans van Oosten, software management consultant, Software Improvement Group, NETHERLANDS
Software in vehicles must be secure, reliable and private. Normally this is tested from the outside and quality is ensured through processes only. We offer software quality code measurements by looking at software from the inside out, by analysing the source code. The presentation will offer examples from state-of-the-art practices.

Sealing connected and autonomous cars’ ECUs according to factory settings, by integrating with its software build environment
David Barzilai, executive chairman and co-founder, Karamba Security Ltd, ISRAEL
The presentation will discuss how to automatically lock down the ECU according to its factory settings, by identification and mapping of all legitimate binaries and valid function calls. It will also cover checking all operations in runtime, blocking droppers and in-memory attacks as they don't comply with the factory settings, plus preventing cyber-attacks with zero false positives and negligible performance impact.

*This Program may be subject to change.

Day 1

Tuesday 20 June

09:30 - 12:30 - Keynote Presentations – Software Development & AI For Autonomous & Self-Driving Vehicles

Selenium and Caesium – software elements of driverless cars
Paul Newman, founder, Oxbotica, UK
Selenium and Caesium are Oxbotica’s solution to this remarkable set of challenges. Selenium is our platform-agnostic autonomy operating system, which provides autonomy and deep scene understanding with any combination of laser or vision sensors, with or without prebuilt maps. Caesium is our fleet coordination system, which handles fleet configuration, data and learning sharing and meta information. This presentation will explain how these 'elements of autonomy' have been architected, built and deployed in fleets of vehicles and OEM vehicles.

The open road to autonomous driving
Dan Cauchy, general manager automotive, The Linux Foundation, USA
The autonomous driving market continues to heat up as auto makers race to acquire tech companies or forge partnerships with suppliers who can accelerate and expand their development efforts. This flurry of M&A activity over the past year is being driven by the realisation that the software and hardware required for autonomous driving is too complex for any company to develop alone. Although this is a step in the right direction, an open-source platform for auto makers to share information such as map data, miles driven and scenarios tested could speed up production cycles and decrease time to market. This presentation will discuss the impact that open source could have on autonomous driving, and how collaboration could benefit auto makers without hindering competition.

An open-source software platform for autonomous driving systems: its success and its difficulties
Lukas Bulwahn, software engineer - software infrastructure group, BMW Car IT, GERMANY
Since 2013, Tilmann Ochs, Daniel Wagner and Lukas Bulwahn have been working on research activities to define, motivate and implement a software platform for autonomous driving systems using custom-off-the-shelf open-source software. In 2014 they presented their understanding of future automotive software and their plans to use pre-existing open-source software for implementation of a collaborative automotive base platform at various automotive software engineering conferences. Now, three years later, it is time to re-evaluate this effort and critically review its progress, its successes and its failures. In this talk, the engineers present their main assumptions in 2013, and give some insights into ongoing software development activities supporting their ideas. Then, they evaluate to what extent they were successful in implementing these ideas, to what extent they could improve their understanding, and how this has refined their plans. On the technical side, they discuss the factors that influence the selection of the communication middleware and the underlying operating system of an automotive platform for autonomous driving systems. On the business side, they discuss the economics of automotive software development and the implications for the use and development of open-source software in the automotive domain.

AI - The Answer to Autonomous Driving and Transportation
Serkan Arslan, Director of Automotive, Nvidia, GERMANY
Artificial Intelligence: What seemed like science fiction just a decade ago is now just science. In the next few years, AI will transform every major industry pertaining to the advancement of humankind. Soon, autonomous cars will reduce congestion and improve road safety. And the tools to embrace these improvements will be new infrastructures and vehicle computing platforms leveraging sensors such as cameras, radars, and lidars. Most importantly, this suite of sensors and tools includes AI for various levels of autonomous driving and transportation both inside and outside of cities. Discussed will be how AI algorithms leveraging structure from motion, sensor fusion and deep learning will help perceive the environment, create HD maps, and not only predict traffic behavior but what to do to control it.

14:00 - 17:30 - Solving Complex Software Challenges for Autonomous Transportation

Compete and succeed with IIoT architectures in autonomous cars
Bob Leigh, director of market development, Real-Time Innovations, USA
Dr Alexander Leonhardi, senior manager, ETAS, GERMANY
Autonomous vehicles are quickly becoming reality. Unfortunately, the existing industry standards can’t keep pace. New players and standards are driving OEMs, Tier 1s and electric car makers to adopt unfamiliar technologies and approaches. In particular, the DDS (Data Distribution Service) standard specifically addresses autonomy in other industries. It now presents an alternative architecture and communication framework for complex, safety-critical automotive designs. This session will review how DDS can solve the most challenging use cases in new car architectures. It will also outline how this IIoT standard will complement or impact AUTOSAR standards.

End--to-End Software Solutions for Automated Driving
Dr Haotian Wu, Software Technical Lead, Intel, USA
Automated driving will enable better, safer and more efficient mobility. However, the automated driving technology heavily relies on reliable, functional, safe, intelligent and comprehensive software that requires cross-platform software development. Cross-platforms include computation, connectivity and the cloud. Facing such complexity, an end-to-end software solution can ensure seamless inter-operation across platforms and functional teams. The end-to-end software solution will facilitate data scientists, system designers and software developers to deliver autonomous driving software stack and algorithms. The end-to-end software solution bundles computer vision, deep learning and sensor data labeling, optimization libraries and compilers in a functional and safety-compliant way.

The ecosystem of self-driving by AImotive
Árpád Takács, outreach scientist, AImotive, HUNGARY
AImotive has developed a full-stack software suite for fully autonomous self-driving cars, providing a hardware-agnostic, scalable solution. Based on the idea that self-driving cars should mimic human behaviour, the algorithms rely on cameras as primary sensors for accomplishing the tasks of object recognition and classification, localisation, decision making, trajectory planning and vehicle control. The software engine components are aided by an extensive toolkit to accelerate the training and verification, including calibration, data collection and augmented data generation, semi-supervised annotation, and a real-time, photorealistic simulation environment. The presentation will provide an insight into the ecosystem of these software components.

The open standards enabling vision processing in ADAS
Illya Rudkin, principal software engineer, Codeplay Ltd, UK
For cars to control or drive themselves, they must 'see' their surroundings in a fast, safe and secure way. Recent advances in computing hardware make vision algorithms and machine learning practical for automotive systems. Open software standards allow competition and innovation in a supply chain, providing substantial advantages to all involved. Open standards enable innovators to develop software for vision or deep learning with flexibility of different hardware. Codeplay will present the virtues of open software standards OpenC and its growing use in automotive, plus how its implementation stack includes open standard SYCL and Google Tensaflow to enable machine learning solutions.

The pedestrian challenge
Michael Hartmann, researcher, Virtual Vehicle Research Center, AUSTRIA
When looking at 'how to make future automated vehicles save', the topic of trajectory planning plays a key role. How can safe trajectories be found for autonomous vehicles? Motion planning for automated vehicles moving in traffic situations in general requires decision making based on incomplete and uncertain knowledge of the situation. The importance of trajectory planning is most evident for situations with vulnerable road users. What happens if some assumptions for planning are uncertain? It is proposed to use methods for uncertainty quantification in motion planning considering the fact that the environment can't be modelled.

Addressing software complexity in ADAS and autonomous driving
Christopher Wild, technical director - CoherenSE, Altran, FRANCE
The future of automotive is increasingly defined by intelligent software. Such software will support increasingly sophisticated algorithms and services for ADAS, with the goal of widespread adoption of autonomous driving. Creating the required software, integrating and testing it, and managing it in-field present a challenge of complexity. Addressing this complexity requires a change in culture and architecture in the automotive world. In this presentation, we introduce CoherenSE and VueForge for ADAS verification, which provide an approach to software architecture targeting the management of complexity in development, integration and test of ADAS.

*This Program may be subject to change.

Day 2

Wednesday 21 June

09:00 - 12:30 - Solving Complex Software Challenges for Autonomous Transportation - Continued

Making future autonomous transportation a reality – safe and secure
John Round, ADAS software manager, NXP Semiconductors, GERMANY
As the world’s largest supplier of automotive semiconductor solutions, NXP is driving innovation for safe and secure vehicle autonomy. In this presentation NXP will discuss the prevailing software and systems architectures that are evolving to address the challenges of fully autonomous design. In addition, NXP will review emerging software technologies in areas such as tooling, AI, middleware and testing, and their potential contribution to mass-market deployment of safe autonomous vehicles. NXP will also share its unique perspective on the challenges and opportunities that exist to truly deliver our collective safe, secure and autonomous transportation future.

Robot to road – future software architecture for autonomous vehicles
Dr Raul Rojas, director, Dahlem Center for Intelligent Systems, Freie Universität Berlin, GERMANY
The session will review possible software architectures for autonomous vehicles, based on experience with other kinds of mobile robots. One important aspect is the interplay and fusion of different kinds of sensors, and also the coordination between 'cognitive' and reactive actoric modules.

Revision conformity, corporate governance and compliance in software calibration processes
Thomas Wambera, affiliate business manager, AVL Deutschland GmbH, GERMANY
The complete documentation of software application responsibilities, calibration processes and related data, as well as the possibility to evaluate these according to different aspects in terms of the right-to-the-right, is crucial when developing ADAS systems. By combining established and controlled workflows and measures for IT security, revision certainty and conformity with ISO 27001, European law (eIDAS regulation) and usability for the implementation of ISO 26262 can be achieved. The speech gives an introduction to legal and technical requirements for the documentation, and is intended to provide an awareness of the complexity and dependencies in the software application process.

Mastering time coherency and execution performance in your AD software
Nicolas Du Lac, CEO, Intempora SA, FRANCE
As embedded software in intelligent vehicles becomes more and more complex, because the number of ECUs and parallel software tasks has increased tremendously, it becomes critical to set up mechanisms that can handle time coherency among these software tasks and data streams. In this presentation we will address some of the software design concepts in the RTMaps framework that allow time coherency to be mastered in multi-thread and distributed architectures while achieving unprecedented execution performance in applications for autonomous driving, from the early stages of applications prototyping down to the execution on the most recent ECU architectures.

The nervous system of an automated driving vehicle
Peter Brink, principal engineer, PolySync Technologies Inc, USA
There are many discussions about the 'brain' of an automated driving vehicle (ADV), looking at the technology required to perform decision making in real time. Little has been said about the nervous system of the ADV – the mechanisms by which the environmental data around the vehicle is transmitted to and from the brain. This presentation covers the requirements for a vehicle hardware abstraction layer for the software defined vehicle. The system requirements end up making the environmental data one of the most safety-critical pieces. How that data is shared is a key factor in making this abstraction layer a requirement.

Towards autonomous driving – developing reliable automated driving features
Thorsten Gerke, automotive industry manager EMEA, MathWorks, GERMANY
Building autonomous cars requires overcoming several technological challenges. It mainly contains three elements: perception, planning and control. This paper will demonstrate how to use a model-based engineering workflow solution based on MATLAB and Simulink to develop and efficiently test automated driving features including different sensor technology such as camera, radar and lidar.

Highly automated driving on highways – reference architecture for coping with complexity
Sebastian Klaas, senior project manager, Elektrobit, GERMANY
The complexity of automated driving systems (e.g. adaptive cruise control, lane keeping assist, emergency braking, etc.) and related components has been rapidly increasing during recent years. Targeting Level 3 and above functions, like a Highway Pilot, adds another level of complexity due to the necessity for cooperation between formerly independent functionalities and additional safety needs. This talk discusses how to cope with complexity, based on a reference architecture and implementation for a Highway Pilot system.

14:00 - 17:30 - Building Resilient Software-Based Security Systems for Autonomous Vehicles

Protecting automotive sensors in connected cars: emerging trends with security vulnerabilities and software solutions
Ben Gardiner, principal security engineer, Irdeto, CANADA
The increased connectivity and complexity in modern vehicles is resulting in new risks and threats. Hackers continuously evolve attack strategies to exploit vulnerabilities and access vehicles. To address these challenges, the industry must make cybersecurity a priority by focusing on key vulnerabilities that hackers exploit. Automotive sensors' designs – the embedded computers of which they are increasingly comprised – will be part of this software solution in concert with other systems to protect connected vehicles. This session will provide an overview of current threats, hackers' motivations for attacking automotive sensors, and software security strategies to protect automotive sensors.

Lessons from the spaceship for the sedan
Frédéric Bourcier, delivery director, autonomous driving solutions, Wind River, FRANCE
As autonomous driving prototypes are being rolled out globally, the industry is developing in earnest. Safety is central. The auto industry can learn from other industries, such as aerospace and defence, with similarly tight restrictions. The industry is experiencing a wave of new innovation, and software is at the heart of this transformation. However, the development of these new autonomous systems requires a combination of mature and sound approaches as well as new ones, in order to ensure safe solutions. This presentation will cover: parallels between automotive and other mission-critical industries as they pertain to safety and security; the changing software landscape, especially with the growing trend of IoT, and how it is adding complexity to automotive systems; how autonomous vehicles can/will need to securely 'talk' with their surroundings in the smart cities of the future.

How to safeguard software in vehicles
Hans van Oosten, software management consultant, Software Improvement Group, NETHERLANDS
Software in vehicles must be secure, reliable and private. Normally this is tested from the outside and quality is ensured through processes only. We offer software quality code measurements by looking at software from the inside out, by analysing the source code. The presentation will offer examples from state-of-the-art practices.

Sealing connected and autonomous cars’ ECUs according to factory settings, by integrating with its software build environment
David Barzilai, executive chairman and co-founder, Karamba Security Ltd, ISRAEL
The presentation will discuss how to automatically lock down the ECU according to its factory settings, by identification and mapping of all legitimate binaries and valid function calls. It will also cover checking all operations in runtime, blocking droppers and in-memory attacks as they don't comply with the factory settings, plus preventing cyber-attacks with zero false positives and negligible performance impact.

*This Program may be subject to change.

 
 

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