bouzouraa mohamed essayed

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An insight into new automated driving experiences

In a recent discussion at Audi, we gained an insight into current progress in the area of automated driving, together with the technical and ethical questions and considerations explored during the development of this technology.

Automated driving is one of the main development fields that we’re pursuing at CARIAD. Among other things, we’re developing assisted and automated driving functions (up to SAE Level 4) for all of the Group’s passenger car brands.

In a recent insightful and inspiring conversation,  Dr. Thomas Dahlem  (Senior Director Development of Autonomous Driving at CARIAD),  Dr. Essayed Bouzouraa  (Head of Feature and Software Development ADAS/Automated Driving at CARIAD) and  Professor Christoph Lütge  from the Technical University of Munich, explored the current developments in the area of automated driving at Audi.

With a handful of specific examples, the three experts offered a glimpse into the future potential of this technology. Not only that, but they also explained the constant  interplay between science and industry , discussed the extent to which traditional automotive engineering can be applied to automated driving technology, and highlighted the importance of going beyond the technical realm and considering  societal and ethical aspects  too.

Technical aspects and progress at Audi

Present-day vehicle development and design is undergoing a fundamental transformation as we look towards offering customers new  software and data-driven experiences  through various vehicle functions and capabilities.

One of the functions that we’re currently developing together with Audi is a highway pilot. This is a system that comes into play at Level 3 automated driving. At this level, drivers can opt to hand over the driving task to the system within defined limits in certain zones. After a given warning period, the driver must take over the steering wheel again. Until that point, the system is responsible.

As Essayed explains, "We design an AI driver by modelling an average driver. We already know that the highway pilot will be a  relatively defensive driver . Ultimately, being driven should also enhance comfort and be enjoyable."

Societal and ethical considerations

But of course, it’s not just the technology itself that’s important. Societal and ethical considerations come into play too. Interdisciplinary networking and a  shared understanding with drivers and passengers  are crucial here.

Even before a function is developed, we need to identify how the vehicle will react to and behave in certain situations. But we also need to understand how the public will react to the vehicle. We need to communicate with drivers and the wider public to help them understand the capabilities and constraints of automated driving technology, and why the AI behaves in the way it does.  Building trust and acceptance in this way are key to securing the success of this technology.

Even Essayed’s point about the highway pilot function and a model driver raises a few areas for consideration. Is there even such a thing as an average driver? Doesn’t this vary around the world, together with different road and infrastructure characteristics? How does an automated driving vehicle map the driving style of a particular geographical region? 

To get a further insight into these questions and considerations in the area of automated driving technology, check out the full interview on the Audi blog:  https://www.progress.audi/progress/en/glimpse-into-the-future-with-the-sphere-concept-vehicles.html

About the author

CARIAD Media Team

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Time for new experiences

Text: Patrick Morda ― Photo: Robert Fischer Reading Time: 9 min

Dr. Bouzouraa, how long will it be before cars are driving themselves?

Dr. Essayed Bouzouraa: There is no short answer to that question. We also need to define the environment in which the technology is to be used – the domains – and its functional scope. Having said that, I am confident that we will see a gradual introduction into structured environments, such as motorways, over the next five years.

Prof. Lütge, you were on the ethics committee that established guidelines for automated driving in Germany in 2017 and continue to research this subject. Are we as a society ready for this technology? Five years is a relatively short period of time.

Prof. Christoph Lütge: As I see it, we are not quite asking enough of people in Germany when it comes to automated mobility. We have been talking about it for a number of years and I think people are now ready to take the next steps. We should talk about the advantages – the real benefits – and not just the challenges and risks.

The technology currently still requires a lot of space in the test vehicles to collect the necessary data. According to the Four Rings’ engineers, it will in future only take up the size of a shoebox.

Dr. Essayed Bouzouraa has been working on highly automated driving since 2012 and, as Head of Development at Audi, he and his team are responsible for developing the “highway pilot” technology.

“The highway pilot will be a defensive driver.”

Dr.-Ing. Essayed Bouzouraa

You talk about automation, but the term “autonomous” is frequently used.

Bouzouraa: In this context, we always talk about automated driving. The “highway pilot” system comes into play at Level 3 (as defined by the Society of Automotive Engineers, SAE; ed. ). At this level, drivers can opt to hand over the driving task to the system within defined limits in certain zones, referred to as domains. After a given warning period, the driver must take over the steering wheel again. Until that point, the system is responsible. At Level 4 (as defined by the SAE; ed. ), the driver is no longer required to take over. Once the driving task is assigned to the vehicle, it needs to be able to handle every conceivable situation.

Lütge: In the ethics committee, we referred to this as “connected” and “automated” driving. However, even though it is somewhat misleading, I have the impression that the term “autonomous driving” has become widely established. I would still rather stick with the terms “automated” and “highly automated” driving.

Dr. Thomas Dahlem: For me, a system is autonomous when it operates entirely independently, without the option of human intervention. But that’s not the vision we are pursuing.

How closely are science and industry working together in this field?

Bouzouraa: We are at a stage where interdisciplinary networking is crucial. It is important for us to have a shared understanding.

Lütge: Up to now, ethics was usually only considered in relation to technology issues after a major problem occurred. Yet we believe that questions above and beyond the technological aspects need to be asked in advance. The sort of questions for which there is still no legal definition and perhaps never will be.

What kind of questions are you thinking of?

Lütge: For instance, there is the question of how an automated car behaves with regard to other road users: does it drive extremely defensively, does it maintain a greater distance than required by law and so on? It is precisely these soft ethical issues that must be taken into account in order to inspire trust in this new technology. Our aim is to provide input right from the development phase.

Bouzouraa: We need dialogue – a permanent feedback loop – both during development and once the technology has gone into series production. Because, essentially, development never ends.

Dr. Thomas Dahlem has spent his entire career to date at the Volkswagen Group, where he is now responsible for the partially and highly automated driving project house.

Audi also relies on lidar sensors, which use a laser to measure distance and speed. Future vehicle architecture will be designed around the necessary sensors and components.

“We develop experiences. That’s never been done before.”

Dr. Thomas Dahlem

To what extent can traditional automotive engineering actually be applied to automated driving?

Bouzouraa: This is a fundamental transformation affecting both our customers – in terms of their future driving experience – and us as the manufacturer with regard to present-day vehicle development and design. It calls for numerous sensors and systems that need to be optimally positioned and networked. Of course, an automated Audi will look good inside and out, but the development requirements and processes are different.

Dahlem: Our aim is to be able to offer customers brand new in-vehicle experiences. Looking ahead, we will develop models around these experiences. That’s never been done before. This will affect virtually all of the components we are familiar with in today’s vehicles, which will need to be looked at with fresh eyes.

Bouzouraa: I’m thinking, for example, of established systems such as windscreen washer reservoirs, which will take on a completely new meaning. In the future, we will have to create conditions to ensure that the sensors on the body can be cleaned and kept clear at all times – even without any passenger’s involvement in the process.

How much progress has Audi made so far?

Bouzouraa: We are constantly on the road with our test vehicles to collect data and learn. The various sensors in and on the car collect vast amounts of information every day. We have had to define new methods, including artificial intelligence (AI), to analyse the huge data volumes. At the same time, we are establishing the requisite processes and paving the way for transitioning the technology to series production.

Dahlem: There is also the challenge of identifying and interpreting all conceivable scenarios – in other words, how the vehicle will behave in certain situations – even before a function is programmed.

How can you anticipate every conceivable scenario? There are infinite possibilities.

Bouzouraa: That’s true. There have been reports, based on the current state-of-the-art technology, that advertising images on buses showing people in motion have been misinterpreted. For instance, the system interpreted this as someone jumping into the street. Sometimes, visual perception using cameras reaches its limits. A while ago, a case involving camera systems interpreting the shining moon as an amber traffic light was doing the rounds online. That’s why we rely on a mixture of visual and actively measuring sensors such as radars and lidars.

The Volkswagen Group bundles its software expertise in the company CARIAD. Today, more than 4,500 developers, engineers and designers at several locations in Germany and around the world are working on a unified software platform that will make the automotive experience safer, more sustainable and more comfortable. Among other things, assisted and automated driving functions (up to SAE Level 4) are being developed for all of the Group’s passenger car brands.

How do you build trust among the public when anomalies like this crop up?

Lütge: I believe that people do see the benefits. Today’s assistance systems already hint at some of what could be possible. You can’t convince everyone, but that won’t always be down to a lack of trust.

Bouzouraa: Trust is fundamental. How easy it is for passengers to understand why the AI behaves in the way it does is also important in this respect. For example, test participants have fed back that driving too smoothly causes them to feel uneasy. It makes them wonder whether the system is actually active. So, for instance, we are now discussing in development how much the steering wheel should move during automated driving to provide visual feedback.

Lütge: This also shows that not everything can be explained in rational terms. Emotions also come into play. But I would caution against over-emphasising concerns. Even today, road users trust technology, sometimes drive at very high speeds, and so on.

Transparent behaviour is key: How can automated and non-automated vehicles coexist, especially to begin with?

Bouzouraa: This is something we are obviously giving a lot of thought to. It could be helpful to initially only release the systems for use in the defined domains. At least, that’s the direction we are thinking in. The term “highway pilot” already hints at this. The motorway is a relatively controllable domain, with clear structural and legal frameworks. However, it is naturally important that we take all road users into account in our behavioural assumptions.

Lütge: I don’t think mixed traffic will be that much of a problem. Other carmakers are developing their own systems, which will also lead to a high level of communication and awareness. I think it’s reasonable to learn on the motorway first, but we must not neglect the rest, especially cities.

In 2017, philosopher and economist Prof. Christoph Lütge sat on the German ethics committee that addressed questions about automated driving on behalf of the federal government.

In July 2021, a new law governing among other things the testing and technical requirements for the approval and operation of Level 4 automated vehicles according to the SAE classification was introduced in Germany.

“I would caution against over-emphasising concerns. Even today, people trust technology.”

Prof. Dr. Christoph Lütge

City driving makes the challenge even greater?

Bouzouraa: Fundamentally speaking, we need to take a 360-degree approach, I agree. But the “city” domain, with pedestrians and cyclists, adds a new level of complexity.

Dahlem: Just as motorways merge into urban spaces, we will approach this challenge step by step. But the technology first needs to be able to handle things like complex intersections, roundabouts – potentially with crests that the sensors can’t see over.

Lütge: And it’s important to weigh up the risks in advance. How do we determine what risks would be considered acceptable? That’s what we are looking at now. We need to be clear: we cannot approach the issue with a zero-risk mindset, that is unrealistic.

But how do you evaluate risk?

Dahlem: Human beings are the benchmark. And humans already have an amazing ability to react at the last millisecond. Our demands on the system with its artificial intelligence are correspondingly high.

Lütge: Having said that, being better than a human driver offers significant scope for interpretation. It can be counterproductive if the standard set is too high, too cautious, too sporty, too defensive.

So what do you use for guidance? Bouzouraa: We design an AI driver by modelling an average driver. We already know that the highway pilot will be a relatively defensive driver. Ultimately, being driven should also enhance comfort and be enjoyable. That would be difficult to achieve if the automated vehicle drove too aggressively. It must steer its passengers through traffic unobtrusively and safely. The question we are examining is whether and how the system’s learning curve will be accepted.

Lütge: That’s a good question, and one that we also discussed in the ethics committee. It should not be the individual vehicle that learns, but the entire fleet. At least whenever it comes to issues related to safety. If someone prefers to drive a little slower on the motorway than someone else, that could then be configured variably. The fact that it is fundamentally a learning process, that the experience of being driven will change over time – people can accept that. Our society has long become used to the idea that artificial intelligence gathers experience and adapts.

With regard to the modelled driver: doesn’t each country have its own idiosyncrasies on the road?

Bouzouraa: There is definitely a connection with individual experience and hence culture. How does an automated driving vehicle map the driving style of a particular region? Is there a kind of best-fit line? These are aspects we are currently working on.

Lütge: We have a special situation in Europe where people are constantly travelling across borders into countries where perceptions differ to some extent. Having tried out various test vehicles, I also have the feeling that no standard exists as yet.

Dahlem: Everything needs to be thought through in even greater detail: for example, an automated car purchased in Germany will in future also need to be able to recognise an Italian police officer. In The Netherlands, the colour of motorway signs differs from that in Germany, while in Portugal, different materials are used on the carriageway. This will mean that we won’t be able to make our system readily available everywhere, or only to a limited extent. But as already mentioned, this technology represents a process of perpetual learning and adapting for us.

Bouzouraa: Staying with the highway pilot, we should also remember that we have around 13,200 kilometres of motorway in Germany alone. There is plenty of potential to enjoy the benefits and the experience of automated driving. I am sure of it.

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Path planning for highly automated driving on embedded gpus.

1. Introduction and Related Work

1.1. motivation, 1.2. related work, 2.1. programming an embedded gpu, 2.2. overview.

• Calculate start values in Frenet coordinates for the path planning algorithm in relation to the current vehicle position.
• Plan different paths with different lengthwise and crosswise variations with respect to the reference path.
• Transform from Frenet coordinates to Cartesian coordinates.
• Calculate the costs for each path and select the best path.

2.3. Frenet Coordinates

• s is the tangent unit vector, s = d r → d l ∥ d r → d l ∥
• d is the normal unit vector, d = d s d l ∥ d s d l ∥
• b is the binormal unit vector, b = s × d
• The change of the angle between two polygon courses can only be moderate. Otherwise, there will be jump discontinuity in the polygon course. Since our approach is proposed for highway scenarios, that is not a limitation.
• The polygon course has to be monotonically increasing along the x-axis.
• The path P is an open polygon course and is defined as P = { P 1 → P 2 → , … , → P n } with S 1 = [ P 1 , P 2 ] , S 2 = [ P 2 , P 3 ] , … , S n − 1 = [ P n − 1 , P n ] .

2.4. Path Generation

2.5. rating of paths.

• Distance to the left corridor boundary ( d c l ) and to the right corridor boundary ( d c r ).
• A crosswise deviation related to the reference path in the endpoint of the path ( d R E F ).
• Maximum lateral acceleration ( d a c c l Y ) of the vehicle along the planned path.

3. Experiments

3.1. evaluation environment, 3.2. evaluation of the coordinate transformation from frenet coordinates to cartesian coordinates, 3.3. evaluation of lengthwise and crosswise path planning, 3.4. evaluation of the path rating, 4. conclusion and future work, author contributions, conflicts of interest, abbreviations.

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Share and Cite

Fickenscher, J.; Schmidt, S.; Hannig, F.; Bouzouraa, M.E.; Teich, J. Path Planning for Highly Automated Driving on Embedded GPUs. J. Low Power Electron. Appl. 2018 , 8 , 35. https://doi.org/10.3390/jlpea8040035

Fickenscher J, Schmidt S, Hannig F, Bouzouraa ME, Teich J. Path Planning for Highly Automated Driving on Embedded GPUs. Journal of Low Power Electronics and Applications . 2018; 8(4):35. https://doi.org/10.3390/jlpea8040035

Fickenscher, Jörg, Sandra Schmidt, Frank Hannig, Mohamed Essayed Bouzouraa, and Jürgen Teich. 2018. "Path Planning for Highly Automated Driving on Embedded GPUs" Journal of Low Power Electronics and Applications 8, no. 4: 35. https://doi.org/10.3390/jlpea8040035

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Journal of Low Power Electronics and Applications (Oct 2018)

Path Planning for Highly Automated Driving on Embedded GPUs

• Jörg Fickenscher,
• Sandra Schmidt,
• Frank Hannig,
• Mohamed Essayed Bouzouraa,
• Jürgen Teich

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The sector of autonomous driving gains more and more importance for the car makers. A key enabler of such systems is the planning of the path the vehicle should take, but it can be very computationally burdensome finding a good one. Here, new architectures in Electronic Control Units (ECUs) are required, such as Graphics Processing Units (GPUs), because standard processors struggle to provide enough computing power. In this work, we present a novel parallelization of a path planning algorithm. We show how many paths can be reasonably planned under real-time requirements and how they can be rated. As an evaluation platform, an Nvidia Jetson board equipped with a Tegra K1 System-on-Chip (SoC) was used, whose GPU is also employed in the zFAS ECU of the AUDI AG.

• autonomous driving
• path planning
• embedded GPUs
• parallelization

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Mohamed Essayed Bouzouraa has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

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Designing for Prediction-Level Collaboration Between a Human Driver and an Automated Driving System

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Bibliometrics & citations.

• Peintner J Escher B Detjen H Manger C Riener A (2024) How to Design Human-Vehicle Cooperation for Automated Driving: A Review of Use Cases, Concepts, and Interfaces Multimodal Technologies and Interaction 10.3390/mti8030016 8 :3 (16) Online publication date: 26-Feb-2024 https://doi.org/10.3390/mti8030016
• You F Yan X Zhang J Cui W (2022) Design Factors of Shared Situation Awareness Interface in Human–Machine Co-Driving Information 10.3390/info13090437 13 :9 (437) Online publication date: 16-Sep-2022 https://doi.org/10.3390/info13090437
• Zhang J (2022) Researches advanced in human-computer collaboration and human-machine cooperation: from variances to common prospect 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022) 10.1117/12.2641865 (142) Online publication date: 10-Nov-2022 https://doi.org/10.1117/12.2641865

Human-centered computing

Human computer interaction (HCI)

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Association for Computing Machinery

New York, NY, United States

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• Cooperative driving
• automated driving
• gaze interaction
• human-machine interaction
• Demonstration
• Refereed limited

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• 2 Total Citations View Citations
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Time for new experiences

Audi has given us a glimpse into the future of automated mobility with its Sphere concept vehicles. How far has the technology come, what possibilities does it offer and – technical aspects aside – what else needs to be considered? A conversation about current developments.

Copy:  Patrick Morda  ― Photo:  Robert Fischer Reading time: 9 min

Prof. Christoph Lütge (left) researches business and corporate ethics at the Technical University of Munich, Germany. Dr. Thomas Dahlem and Dr. Essayed Bouzouraa (right) are shaping the future of automated driving at CARIAD. They are driving forward the technology’s development in Gaimersheim near Ingolstadt, Germany.

Dr. Bouzouraa, how long will it be before cars are driving themselves? Dr. Essayed Bouzouraa: There is no short answer to that question. We also need to define the environment in which the technology is to be used – the domains – and its functional scope. Having said that, I am confident that we will see a gradual introduction into structured environments, such as motorways, over the next five years.

Prof. Lütge, you were on the ethics committee that established guidelines for automated driving in Germany in 2017 and continue to research this subject. Are we as a society ready for this technology? Five years is a relatively short period of time. Prof. Christoph Lütge: As I see it, we are not quite asking enough of people in Germany when it comes to automated mobility. We have been talking about it for a number of years and I think people are now ready to take the next steps. We should talk about the advantages – the real benefits – and not just the challenges and risks.

The technology currently still requires a lot of space in the test vehicles to collect the necessary data. According to the Four Rings’ engineers, it will in future only take up the size of a shoebox.

Dr. Essayed Bouzouraa has been working on highly automated driving since 2012 and, as Head of Development at Audi, he and his team are responsible for developing the “highway pilot” technology.

“ The highway pilot will be a defensive driver. ”

Dr.-Ing. Essayed Bouzouraa

You talk about automation, but the term “autonomous” is frequently used. Bouzouraa: In this context, we always talk about automated driving. The “highway pilot” system comes into play at Level 3 (as defined by the Society of Automotive Engineers, SAE; ed.). At this level, drivers can opt to hand over the driving task to the system within defined limits in certain zones, referred to as domains. After a given warning period, the driver must take over the steering wheel again. Until that point, the system is responsible. At Level 4 (as defined by the SAE; ed.), the driver is no longer required to take over. Once the driving task is assigned to the vehicle, it needs to be able to handle every conceivable situation. Lütge: In the ethics committee, we referred to this as “connected” and “automated” driving. However, even though it is somewhat misleading, I have the impression that the term “autonomous driving” has become widely established. I would still rather stick with the terms “automated” and “highly automated” driving. Dr. Thomas Dahlem: For me, a system is autonomous when it operates entirely independently, without the option of human intervention. But that’s not the vision we are pursuing.

How closely are science and industry working together in this field? Bouzouraa: We are at a stage where interdisciplinary networking is crucial. It is important for us to have a shared understanding. Lütge: Up to now, ethics was usually only considered in relation to technology issues after a major problem occurred. Yet we believe that questions above and beyond the technological aspects need to be asked in advance. The sort of questions for which there is still no legal definition and perhaps never will be.

What kind of questions are you thinking of? Lütge: For instance, there is the question of how an automated car behaves with regard to other road users: does it drive extremely defensively, does it maintain a greater distance than required by law and so on? It is precisely these soft ethical issues that must be taken into account in order to inspire trust in this new technology. Our aim is to provide input right from the development phase. Bouzouraa: We need dialogue – a permanent feedback loop – both during development and once the technology has gone into series production. Because, essentially, development never ends.

Dr. Thomas Dahlem has spent his entire career to date at the Volkswagen Group, where he is now responsible for the partially and highly automated driving project house.

Audi also relies on lidar sensors, which use a laser to measure distance and speed. Future vehicle architecture will be designed around the necessary sensors and components.

“ We develop experiences. That’s never been done before. ”

Dr. Thomas Dahlem

To what extent can traditional automotive engineering actually be applied to automated driving? Bouzouraa: This is a fundamental transformation affecting both our customers – in terms of their future driving experience – and us as the manufacturer with regard to present-day vehicle development and design. It calls for numerous sensors and systems that need to be optimally positioned and networked. Of course, an automated Audi will look good inside and out, but the development requirements and processes are different. Dahlem: Our aim is to be able to offer customers brand new in-vehicle experiences. Looking ahead, we will develop models around these experiences. That’s never been done before. This will affect virtually all of the components we are familiar with in today’s vehicles, which will need to be looked at with fresh eyes.

Such as? Bouzouraa: I’m thinking, for example, of established systems such as windscreen washer reservoirs, which will take on a completely new meaning. In the future, we will have to create conditions to ensure that the sensors on the body can be cleaned and kept clear at all times – even without any passenger’s involvement in the process.

How much progress has Audi made so far? Bouzouraa: We are constantly on the road with our test vehicles to collect data and learn. The various sensors in and on the car collect vast amounts of information every day. We have had to define new methods, including artificial intelligence (AI), to analyse the huge data volumes. At the same time, we are establishing the requisite processes and paving the way for transitioning the technology to series production. Dahlem: There is also the challenge of identifying and interpreting all conceivable scenarios – in other words, how the vehicle will behave in certain situations – even before a function is programmed.

How can you anticipate every conceivable scenario? There are infinite possibilities. Bouzouraa: That’s true. There have been reports, based on the current state-of-the-art technology, that advertising images on buses showing people in motion have been misinterpreted. For instance, the system interpreted this as someone jumping into the street. Sometimes, visual perception using cameras reaches its limits. A while ago, a case involving camera systems interpreting the shining moon as an amber traffic light was doing the rounds online. That’s why we rely on a mixture of visual and actively measuring sensors such as radars and lidars.

Different sensors record what is happening in front of an automated vehicle. How much or little distance the system maintains independently is one of the key questions addressed by Thomas Dahlem and Christoph Lütge.

How do you build trust among the public when anomalies like this crop up? Lütge: I believe that people do see the benefits. Today’s assistance systems already hint at some of what could be possible. You can’t convince everyone, but that won’t always be down to a lack of trust. Bouzouraa: Trust is fundamental. How easy it is for passengers to understand why the AI behaves in the way it does is also important in this respect. For example, test participants have fed back that driving too smoothly causes them to feel uneasy. It makes them wonder whether the system is actually active. So, for instance, we are now discussing in development how much the steering wheel should move during automated driving to provide visual feedback. Lütge: This also shows that not everything can be explained in rational terms. Emotions also come into play. But I would caution against over-emphasising concerns. Even today, road users trust technology, sometimes drive at very high speeds, and so on.

Transparent behaviour is key: How can automated and non-automated vehicles coexist, especially to begin with? Bouzouraa: This is something we are obviously giving a lot of thought to. It could be helpful to initially only release the systems for use in the defined domains. At least, that’s the direction we are thinking in. The term “highway pilot” already hints at this. The motorway is a relatively controllable domain, with clear structural and legal frameworks. However, it is naturally important that we take all road users into account in our behavioural assumptions. Lütge: I don’t think mixed traffic will be that much of a problem. Other carmakers are developing their own systems, which will also lead to a high level of communication and awareness. I think it’s reasonable to learn on the motorway first, but we must not neglect the rest, especially cities.

In 2017, philosopher and economist Prof. Christoph Lütge sat on the German ethics committee that addressed questions about automated driving on behalf of the federal government.

In July 2021, a new law governing among other things the testing and technical requirements for the approval and operation of Level 4 automated vehicles according to the SAE classification was introduced in Germany.

“ I would caution against over-emphasising concerns. Even today, people trust technology. ”

Prof. Dr. Christoph Lütge

City driving makes the challenge even greater? Bouzouraa: Fundamentally speaking, we need to take a 360-degree approach, I agree. But the “city” domain, with pedestrians and cyclists, adds a new level of complexity. Dahlem: Just as motorways merge into urban spaces, we will approach this challenge step by step. But the technology first needs to be able to handle things like complex intersections, roundabouts – potentially with crests that the sensors can’t see over. Lütge: And it’s important to weigh up the risks in advance. How do we determine what risks would be considered acceptable? That’s what we are looking at now. We need to be clear: we cannot approach the issue with a zero-risk mindset, that is unrealistic.

But how do you evaluate risk? Dahlem: Human beings are the benchmark. And humans already have an amazing ability to react at the last millisecond. Our demands on the system with its artificial intelligence are correspondingly high. Lütge: Having said that, being better than a human driver offers significant scope for interpretation. It can be counterproductive if the standard set is too high, too cautious, too sporty, too defensive.

So what do you use for guidance? Bouzouraa: We design an AI driver by modelling an average driver. We already know that the highway pilot will be a relatively defensive driver. Ultimately, being driven should also enhance comfort and be enjoyable. That would be difficult to achieve if the automated vehicle drove too aggressively. It must steer its passengers through traffic unobtrusively and safely. The question we are examining is whether and how the system’s learning curve will be accepted. Lütge: That’s a good question, and one that we also discussed in the ethics committee. It should not be the individual vehicle that learns, but the entire fleet. At least whenever it comes to issues related to safety. If someone prefers to drive a little slower on the motorway than someone else, that could then be configured variably. The fact that it is fundamentally a learning process, that the experience of being driven will change over time – people can accept that. Our society has long become used to the idea that artificial intelligence gathers experience and adapts.

Interdisciplinary exchanges on the challenges and opportunities of automated driving, even at an early stage of development, is crucial for ethicist Christoph Lütge (right) as well as for Thomas Dahlem (centre) and Essayed Bouzouraa.

With regard to the modelled driver: doesn’t each country have its own idiosyncrasies on the road? Bouzouraa: There is definitely a connection with individual experience and hence culture. How does an automated driving vehicle map the driving style of a particular region? Is there a kind of best-fit line? These are aspects we are currently working on. Lütge: We have a special situation in Europe where people are constantly travelling across borders into countries where perceptions differ to some extent. Having tried out various test vehicles, I also have the feeling that no standard exists as yet. Dahlem: Everything needs to be thought through in even greater detail: for example, an automated car purchased in Germany will in future also need to be able to recognise an Italian police officer. In The Netherlands, the colour of motorway signs differs from that in Germany, while in Portugal, different materials are used on the carriageway. This will mean that we won’t be able to make our system readily available everywhere, or only to a limited extent. But as already mentioned, this technology represents a process of perpetual learning and adapting for us. Bouzouraa: Staying with the highway pilot, we should also remember that we have around 13,200 kilometres of motorway in Germany alone. There is plenty of potential to enjoy the benefits and the experience of automated driving. I am sure of it.

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