News From atlatec, Volvo Trucks, Aurora, Polestar, And Volvo Cars

Hello Dear atlatec subscriber,

As usual at the end of each month, we’ve prepared a brief automotive news overview to help you to keep track of the hottest headlines.

This time, we’re especially happy to include some news of our own! Additionally, we found interesting developments at Volvo Trucks and their partnership with Aurora, the Polestar’s long-term commitment to the first climate-neutral EV, and Nvidia’s DRIVE Orin AI-computing platform, that Volvo Cars has opted to use for their AV.

I hope you enjoy the read and make sure to watch out latest fire-side chat that is already available on YouTube.

ADASテスト:主観的な顧客志向から大規模な客観的検証まで – Via atlatec


While actual autonomous vehicles may still be a few years out, the L1/L2 ADAS domain is already going stronger than ever. That’s why we’re happy to publish some news of our own this week: A detailed look at a solution for ADAS validation that brings capabilities and fidelity previously limited to proving grounds to public road testing.

Take a look at this solution for creating and leveraging reference data at scale as it was piloted by Porsche and built together by atlatec and our partners GeneSys, MdynamiX and the Kempten University of Applied Sciences. We’re quite excited to share this and hope you will take an interest, too: If you have any thoughts, we’d love to hear them!

Volvo partners with Aurora to accelerate autonomous truck applications – Via Autonomous Vehicle International

News From atlatec, Volvo Trucks, Aurora, Polestar, And Volvo Cars

Autonomous trucks are often regarded as perhaps the first instance of actual production AVs we’re likely to encounter on the open road. Reasons include the focus on (relatively non-comlex) highway routes, saving human drivers the grind of long-distance trips as well as the clear business case to be made in the logistics domain.

The latter, of course, relies on actual commercialization – towards which Volvo Trucks may have just taken another step, announcing a partnership with AV stack provider Aurora. The mutual goal: To bring autonomous hub-to-hub truck operations to North America – and thus bringing everyone a step closer to encountering actual AVs on public roads.

Polestar ‘will have to question everything’ in order to build the first climate-neutral EV – Via Tech Crunch

News From atlatec, Volvo Trucks, Aurora, Polestar, And Volvo Cars

Basically every car maker and their suppliers are currently asking themselves, “How can we reduce carbon emissions a bit more – and perhaps offset the rest?” This is, of course, a relevant effort; and it continues to produce reductions for CO2, NOx and other emittents by a few percent every year (or at least every time a new emissions standard is announced).

However, instead of asking about 10% less, Geely-owned Polestar has chosen to question everything about themselves, aiming for 100% elimination of emissions – including not only the operations lifecycle of their new “Polestar 0” model, but also the entire supply chain and production, moving away from toxicity-related materials for chassis and batteries.

That asking bigger questions lead to bigger answers is something tech companies like Google have known for a long time (see “10X thinking”) – it will be exciting to see its effects on automotive and manufacturing, and whether others will follow suit!

Volvo Cars chooses Nvidia DRIVE Orin SoC for Highway Pilot AD system – Via Autonomous Vehicle International

News From atlatec, Volvo Trucks, Aurora, Polestar, And Volvo Cars

More news from Sweden, and thus from Geely, who are also the proud owners of Volvo Cars: As was announced during NVIDIA’s GTC this month, the car maker has chosen their “DRIVE Orin” system to enable its passenger cars to drive themselves.

As Volvo Cars has previously announced, they’re skipping Level 3 entirely, instead aiming for L4 operations on highways as their debut on the autonomous vehicles stage. The first vehicle to come with the new NVIDIA SoC is the next-gen XC90; in which it will work hand in hand with ADAS software developed by Zenseact and LiDAR sensors supplied by Luminar.

Stay tuned for the atlatec industry newsletter coming at the end of May! In the meantime, feel free to reach out to us if you have any questions. 

Get automotive industry news directly to your mailbox – sign up for the atlatec newsletter.



Advanced Driver Assistance Systems (ADAS) have been around since quite a while: Modern-day vehicles inevitably come with assistance features such as Adaptive Cruise Control (ACC), Lane-Keep Assist (LKA), Blind Spot Monitors, Traffic Sign Recognition and other features supposed to make driving safer and more comfortable. In contrast to Autonomous Vehicles, ADAS is a huge and profitable market today, and will likely remain so for the foreseeable future.

If you’ve driven a car with such features in the last few years, though, you might have realized that the performance of these systems can vary – sometimes by quite a lot: While some LKA systems do a good job of keeping your vehicle on track, others tend to react too late, or overcorrect and send you right across the opposite lane border rather than properly centering the car between them. Similarly, some ACCs make for a smooth ride, while others may apply the brakes when another vehicle cuts you off after overtaking – rather than just letting their higher speed widen the gap between you, as most human drivers would do.

Join live panel discussion “How to scale ADAS testing with objective KPIs“. Register here.

Why ADAS Performance Varies So Much

One of the reasons for the varying performance of ADAS features is that reliable, objective testing procedures for public roads have been rare.

During real-world testing, car makers and their suppliers routinely record all onboard data from sensors, actuators and more – allowing for in-depth analysis of system failures, near-misses and similar incidents after a drive. However: These onboard systems only record their own version of events – figuratively speaking, what the car thinks happened during the drive. If you want to iron out false positives/negatives, you need to compare this questionable version of events to a more trusted data set – reference data, or “ground truth” data.

Using Lane-Keep Assist as an example: If a test vehicle missed a lane border, overcorrected, or failed completely, you need to closely examine the actual environment/lane borders in that exact position – as well as the vehicle’s relative position and pose in that specific moment.

In the past, this has been a huge task and massive undertaking, requiring lots of on-site engineering manpower and high-precision measurements that were only possible in closed-off, controlled environments – in other words, on proving grounds.

And while proving grounds are an amazing asset for automotive testing, the total scope and variability of their test routes are by definition limited – which makes it a challenge to optimize a system for use on hundreds of thousands of kilometers of open road. Similarly, standardized tests as defined by EuroNCAP or ISO don’t come close to capturing the variety of roads and scenarios a vehicle is sure to encounter during its lifecycle.

To use another metaphor: Imagine driver training only taking place on a single safety course, with drivers unable to learn better performance after passing the test and entering public roads.

To better optimize for the real world, more real world testing is required – and it needs to happen without sacrificing the precision and fidelity of known approaches: It is not feasible having to rely on subjective feedback from test drivers that “it felt maybe a little bit strange somewhere back there.”

This leads us to a second reason why ADAS features differ so much from brand to brand: The lack of an objective standard for how they should perform – and what the criteria for optimal driving pleasure might be. The following portion of this article describes a field-tested approach to solving both of these problems.

From Subjective Feelings To Objective KPIs and Measurements

In a collaboration with the performance car maker Porsche, the companies GeneSys, MdynamiX and atlatec as well as research partner Adrive Living Lab of the Kempten University of Applied Sciences have created a solution to bridge this gap. Together, the partners have introduced a testing process that allows for objective ADAS validation at scale and on open roads, as featured in ATZ magazine (Automobiltechnische Zeitschrift).

The approach consists of 4 steps – in the aforementioned project, it was applied to validate LKA performance:

  1. The definition of objective criteria for ADAS performance.
  2. The creation of ground truth environment/HD map data
  3. The accurate recording of vehicle position/pose reference data during test drives 
  4. In-depth analysis of relevant driving situations and their recreation in the virtual space/simulation

Defining Objective Criteria For Driving Pleasure

The first challenge is already one of the hardest: How do you quantify an emotional quality criterion such as driving pleasure, or the feeling of safety? To solve this challenge, the Kempten University of Applied Sciences has developed a model of 3 layers: Subjective customer assessment, subjective expert assessment and finally a layer of objective vehicle signals.

ADAS Testing: From Subjective Customer Preferences To Objective Validation At Scale
Translating driver’s subjective feelings into measurable vehicle signals. © Kempten University of Applied Sciences*

A series of test drives, workshops, benchmarking campaigns and more produce insights into the subjective preference of customers for how a feature (e. g. an LKA) should perform. These insights are then refined into categories and sub-categories by automotive experts. Finally, the results are matched with related vehicle-level signals and the expected intensity to be measured for each of them, on a scale from none (0) to high (9).

Generating Ground Truth Data At Scale

Automotive OEMs and suppliers of ADAS technology already do test drives on a defined set of routes: These routes are chosen for factors like their variety, internationality, likelihood of certain events and more – and can cover hundreds or thousands of kilometers of public roads across multiple continents.

These routes are a great resource for objective ADAS testing on public roads – if you have access to high-accuracy measurements of their features and a way to generate reference data for the trajectories your test vehicles drive over them.

To this effect, the High Definition (HD) mapping capabilities of atlatec are leveraged to create 3-dimensional maps of test routes on – in this case, on public roads around Stuttgart and Kempten in Southern Germany.

ADAS Testing: From Subjective Customer Preferences To Objective Validation At Scale
Mapped lane border types and positions, as seen from a vehicle perspective and above. © atlatec

The produced HD maps contain information on lane borders’ types and their position with inch-perfect accuracy. atlatec’s vision-based approach to mapping allows for consistent high accuracy, even in areas with bad GPS reception.

The finished maps are exported into a multi-layered data format allowing for localization and matching of vehicle poses in real time. For the described collaboration, a variation of OpenDRIVE was used.

Test Drive Recording At High Fidelity

Accurately recording and recreating all trajectories driven during testing is made possible by an Automotive Dynamic Motion Analyzer (ADMA) unit by GeneSys: a high-precision motion sensor which allows for differential GNSS correction and is designed specifically for vehicle dynamics testing.

ADAS Testing: From Subjective Customer Preferences To Objective Validation At Scale
Variations of the ADMA system on equipped vehicles. © GeneSys

Based on this technology new test methods had to be developed for the objective evaluation of driving characteristics in the ADAS/AD context. Therefore, driver input as well as road and traffic input, control intervention and the resulting vehicle reaction/movement should be evaluated in its 6 degrees of freedom. Derived from the automated lateral control, it is necessary to obtain a high level of knowledge of the road excitation (essentially road markings and surface geometry) and the driver input in order to be able to evaluate the resulting vehicle reaction accordingly. In the case of assisted longitudinal guidance, a high-level knowledge of the surrounding traffic is required. 

Like all sensors, environmental sensors such as cameras, radar or lidar are faulty and not available or sufficiently accurate in all situations. This can have a significant impact on driving characteristics: For example, a camera may not be able to reproduce the curvature of a road accurately, which can cause difficulties for the lane-keeping controller. This repeatedly leads to uncertainties if the experienced driving characteristics are a result of the poor performance of sensors, trajectories, controllers, actuators or the poor response of the vehicle influenced by steering, axles, tires and chassis control systems.

In order to investigate this cause and effect chain, a much more accurate reference measurement method should be used as “Ground Truth”.

ADAS Testing: From Subjective Customer Preferences To Objective Validation At Scale
“Ground Truth“ measurement method © MdynamiX**/atlatec

In addition, an optimized measuring steering wheel allows for precise recording of steering speed/angle and torque/gradient. In the collaboration with Porsche, an original steering wheel was used to fully preserve the brand- and model-specific haptics, control functions and other details, ensuring realistic driver/vehicle interaction.

For the test drives, a comprehensive catalog of defined maneuvers and situations is created by MdynamiX and the University of Applied Science Kempten, ensuring that all relevant scenarios are encountered and recorded.

ADAS Testing: From Subjective Customer Preferences To Objective Validation At Scale
Example of a defined driving maneuver for LKA testing. © MdynamiX***

Turning Data Into Insights And Reproducible Scenarios For Simulation

The use of suitable algorithms makes for precise calculations and the automatic generation of KPI values from the recorded data. For example, the yaw rate and lateral acceleration recorded by the reference system – based on the ground truth curvature – can be matched with the measurements from the onboard system, allowing for accurate measurement of the production system’s deviation from the actual/reference values.

Comparing objective criteria and side offsets for straight/curved driving.
Comparing objective criteria (top) and side offsets for straight/curved driving (bottom). © Kempten University of Applied Sciences****

To gain further insights from the data, the digitalized test routes can be imported into automotive simulation tools. This allows for additional MIL/SIL/HIL tests as well as immersive Driver-in-the-Loop simulations.

Additionally, select scenarios encountered and recorded on real-world test drives can be reproduced – allowing for variation of parameters to further narrow down performance limitations.

Supplementing the test setup with atlatec sensor equipment also allows to accurately record real-world traffic and re-create other vehicles’ trajectories in simulations: This is particularly useful when validating ADAS features that are supposed to react to dynamic agents (e. g. Adaptive Cruise Control or Emergency Brake Assist systems). “Scenario fuzzing” again allows for manipulation of the real-world situation and can aid in the hunt for edge/corner cases.

Scenario Fuzzing
“Scenario Fuzzing” – the creation of variations from real-world traffic situations. © atlatec

Additional Reading/References

If you’d like to explore this topic further and in more scientific detail, we recommend the following resources:

M. Höfer, F. Fuhr, B. Schick und P. E. Pfeffer, „Attribute-based development of driver assistance systems“ in 10th International Munich Chassis Symposium 2019, P. E. Pfeffer, Hg., Wiesbaden: Springer Fachmedien Wiesbaden, 2020, 293 – 306.

J. Nesensohn, S. Levéfre, D. Allgeier, B. Schick, and F. Fuhr. “An Efficient Evaluation Method for Longitudinal Driver Assistance Systems within a Consistent KPI based Development Process”.

S. Keidler, D. Schneider, J. Haselberger, K. Mayannavar und B. Schick, „Entwicklung fahrstreifengenauer Ground Truth Karten für die objektive Eigenschaftsbewertung von automatisierten Fahrfunktionen“ in 17. VDI-Fachtagung, Hannover, 2019.

B. Schick, C. Seidler, S. Aydogdu und Y.-J. Kuo, „Driving experience vs. mental stress with automated lateral guidance from the customer’s point of view“ in Proceedings, 9th International Munich Chassis Symposium 2018, P. Pfeffer, Hg., Wiesbaden: Springer Fachmedien Wiesbaden, 2019, S. 27–44, doi: 10.1007/978-3-658-22050-1_5.

S. Aydodgu, B. Schick und M. Wolf, „Claim and Reality? Lane Keeping Assistant – The Conflict Between Expectation and Customer Experience“ in 27. Aachener Kolloquium, Aachen, 2018.

D. Schneider, B. Schick, B. Huber und H. Lategahn, „Measuring Method for Function and Quality of Automated Lateral Control Based on High-precision Digital “Ground Truth” Maps“ in 34. VDI/VW-Gemeinschaftstagung Fahrerassistenzsysteme und Automatisiertes Fahren 2018: Wolfsburg, 07. und 08. November 2018, 2018.

B. Schick, F. Fuhr, M. Höfer und P. E. Pfeffer, „Eigenschaftsbasierte Entwicklung von Fahrerassistenzsystemen“, ATZ Automobiltech Z, Jg. 121, Nr. 4, S. 70–75, 2019, doi: 10.1007/s35148-019-0006-2.

To learn more from the parties involved, feel free to reach out directly:


Contact: Dr. Henning Lategahn


Contact: Peter Arnold

Kempten University of Applied Sciences

Contact: Prof. Bernhard Schick


Contact: Matthias Niegl

Image source:

Titel image: „Eigenschaftsbasierte Entwicklung von Fahrerassistenzsystemen“, ATZ Automobiltech Z
*„Eigenschaftsbasierte Entwicklung von Fahrerassistenzsystemen“, ATZ Automobiltech Z
**„Eigenschaftsbasierte Entwicklung von Fahrerassistenzsystemen“, ATZ Automobiltech Z
***„Eigenschaftsbasierte Entwicklung von Fahrerassistenzsystemen“, ATZ Automobiltech Z
****„Eigenschaftsbasierte Entwicklung von Fahrerassistenzsystemen“, ATZ Automobiltech Z



Your monthly automotive briefing

As we approach the end of March, let’s look back at the headlines that made noise this month. In this issue: Tesla, Honda, and Volvo. This month we are especially excited about the release of atlatec’s brand-new website. We would like to thank everyone who participated in this challenging project and contributed to the result that we are ready to present. Feel free to check out atlatec.deサイトをご覧ください and let us know what you think. 

Tesla touts self-driving to consumers. To the DMV, it tells a different tale – Via Los Angeles Times

News from Tesla, Volvo, Honda, and atlatec

Tesla is one of those companies that tends to polarize people: You’re either a real fan or a pronounced sceptic, with little middle ground between “Teslaratis” and outspoken critics.

One large reason for that is Tesla’s “Full Self Driving” (FSD) feature – on which, apparently, Tesla is pretty divided itself: While Elon Musk has repeatedly praised the system as an actual self-driving feature on Twitter, his lawyers argue the polar opposite in front of the DMV: A new trove of emails, revealed after after a public records request show that Tesla’s lawyers adamantly claim FSD to be nothing but a L2 driver assist feature – with no perspective or even a plan to turn it into anything resembling autonomous driving, under any conditions.

The article contains a link to the emails if you want to dive in yourself. An additional takeaway that was very interesting to us: Tesla lawyer Eric Williams references the Model 3 handbook, clarifying that FSD will indeed have trouble in areas for which proper map data is not available and may very well be unable to recognize stop signs and traffic lights due to inaccurate maps. Once again, quite the contrast to the messages of Musk himself, who has called reliance on (HD) maps “a really bad idea” before. 

Honda launches world’s first level 3 self-driving car – Via Asia Nikkei

News from Tesla, Volvo, Honda, and atlatec

So there it is, the first Level 3 system on the market, that will actually allow you to take your hands off the wheel, while the car takes over responsibility for driving.

Honda debuted its first L3 feature this month, the “Traffic Jam Pilot” which can drive autonomously in bumper-to-bumper highway traffic, while the “driver” is free to enjoy the infotainment system or otherwise occupy themself – provided they remain able to take back operations if the system notifies this to be required.

Honda reports they’ve driven 1.3 million kilometers for testing, and have simulated around 10 million scenarios in preparation. Still, the company wants to make sure they’re not moving too fast: The feature will only be available to 100 leasing customers to start with and they’re limiting it to speeds up to 50 km/h rather than the 60 mph regulation allows for.

Volvo says it will be ‘fully electric’ by 2030 and move car sales online – Via CNBC

News from Tesla, Volvo, Honda, and atlatec

Volvo Cars is one company that has been behind some massive innovations in automotive over the decades: The 3-prong safety belt, SIPS/side airbags and limiting all new vehicles to 180 km/h top speed, to name a few. The first and the latter were pretty controversial at their time (the latter as recently as 2020) but Volvo did what they thought was right anyway.

The next chapter in that legacy may be ahead: Volvo Cars has announced they see “no long-term future for cars with an internal combustion engine” and will sell nothing but electric vehicles by 2030. By 2025, half of the fleet shall be fully electric already, with hybrids making up the other 50%.

In addition to this massive overhaul, they also want to modernize the customer experience in order to make car sales more digital and mainly online-driven, only offering in-person assistance where customers really want it (e. g. around test drives and delivery). relaunched with all-new website concept and design – Via atlatec

News from Tesla, Volvo, Honda, and atlatec

This month, we have some news of our own, and we’re pretty excited about it: After loads of discussions, drafting, designing and reworking, we are happy to announce the launch of our all-new website.

So, why the do-over? First of all, we wanted to reflect the degree of maturity that we’ve achieved over time: Working for international automotive OEMs and Tier1 suppliers as well as other leading companies in the mobility sector, we thought it was high time to get rid of what our CEO lovingly called “Mickey Mouse animations” and replace similar young-blood gimmicks with actual footage of our work.

Secondly, we wanted to present said work in a more customer-oriented manner: Rather than focusing on what we find interesting ourselves, the new website breaks down our solutions by customer use cases, such as HD maps/scenarios for simulation or maps for AV/ADAS production systems. For those and more, now offers dedicated pages focusing on specific, related parts of our portfolio: All the relevant info is curated in one place, the rest left to explore elsewhere, for those who want to do so.

If you decide to take a look at the new website, we’d love to hear your thoughts on it: Let us know by simply replying to this email or shoot us a message on LinkedIn!

I hope this overview helps you to stay on top of the industry news. Make sure to watch the latest fireside chat with the atlatec team on YouTube.

Stay tuned for the atlatec industry newsletter coming end of April!


自動車ニュース 2021年2月

News from TuSimple, Motional, New Flyer, AIMotive, and MathWorks

As usual, at the end of the month the atlatec team prepares for you a short overview of the automotive news that we found the most interesting. Enjoy the summary and make sure to watch our latest Zoom talk – it is already available on YouTube

5,000 autonomous trucks [by TuSimple] will hit the roads in China in 2021” – via Jair Ribeiro/Medium


There has been a lot of news from China about robotaxi rollouts in the last few months; now comes a huge leap for autonomous trucks: TuSimple, a 4 year old startup has received approval for operating a fleet of 5000 fully self-driving trucks, without safety drivers on board.

This is also interesting news for investors in the space: TuSimple expects to turn a net profit of $300 million thanks to this move – while eyeing an IPO in 2021 that might lead to a $7 billion valuation.

“Motional Initiates Testing Of Driverless Vehicles In Las Vegas” – via Forbes


Motional, the joint venture by Hyundai and Aptiv, will begin to offer driverless rides in Las Vegas, joining companies such as Waymo and Cruise. A “safety steward” (with somewhat unspecified responsibilities) will apparently be on board, but the permit issued by the state of Nevada allows for an empty driver’s seat.

An interesting detail is that operations are reportedly focused on “suburban residential areas”, which arguably make for a good use of AVs: Offering a bridge across the “last mile” gap between public transit stations and people’s homes might make more sense that deploying an ever-rising number of vehicles in city centers, where public transportation is usually at its best and most dense.

“Self-Driving Tech Heads To Transit With New Flyer’s Autonomous Electric Bus” – via Forbes

New Flyer Bus

Speaking of public transportation: Why are we reading so much about autonomous trucks and robotaxis, but rarely hear of autonomous buses? Reasons behind that might be the challenge of navigating massive vehicles in dense, busy urban environments – but apparently New Flyer, North America’s biggest producer of buses feels up to that: Their first autonomous model, an electric Xcelsior, will begin testing in 2022.

There’s also advantages over other AV use cases according to New Flyer president Chris Stoddart: “One of the nice things is the ability to pre-map the routes, when you can run your vehicle around that route and pre-map it so that you have some redundancy and don’t have to rely completely on your various visual systems all the time […] When your average bus speed is only 12.5 mph that certainly helps.”

“AImotive, MathWorks team to improve autonomous vehicle simulation” – via Futurride


There’s lots of providers of tools for AV/ADAS simulation, and it mostly seems they’re sticking to their own devices, attempting to build the best solution they can independently of other players in the space. It’s a refreshing change to see some collaboration here, with AImotive and MathWorks integrating their “aiSim” and “RoadRunner” offerings:

This will apparently allow for an easy import of road models created in RoadRunner (formerly by VectorZero) into aiSim, an ISO 26262/ASIL-D-certified simulation platform. Since RoadRunner in turn provides the ability to import real-world OpenDRIVE HD maps (e. g. by atlatec), this might indeed make for a compelling toolchain, coupling access to realistic environment models with sophisticated virtual sensor simulation. If you happen to be using/trialing this solution, we’d love to hear some impressions!

We hope you enjoyed this issue. Stay tuned for the upcoming automotive news overview at the end of March. Get the overview directly to your mailbox – sign up for the atlatec newsletter.


atlatec、ボルボトラック、オーロラ、ポールスター、ボルボカーズからのニュース こんにちはatlatecニュースレター定期読者の皆様、いつものようにそれぞれの終わりに

Your monthly automotive briefing

November has been quite an eventful month not only for automotive industry, but also for atlatec. We are happy to announce that our HD maps are compatible with one more simulation tool: Cognata

Also, our team is ready to present the result of the collaboration with TrianGraphics – the sample data is already available for download on our website.

Enjoy your monthly overview of automotive industry news!

Daimler Trucks partners with Waymo to build self-driving semi trucks – Via TechCrunch

When I initially saw the headlines about this, I was intrigued by words like “partnership” and “collaboration” between Waymo and Daimler Trucks North America. Upon closer reading of the press pieces, it turns out this partnership amounts to: Daimler selling trucks to a customer (who happens to be Waymo). Apparently, the Freightliner team at Daimler will not be involved in the “Waymofication” of the vehicles and have no insight whatsoever.

Seems like a lot of buzz for “OEM sells vehicles”, but serves to highlight the conflict of legacy OEMs and Silicon Valley software companies: Will the Daimlers of the world become the new Tier1s in the world of autonomous driving? Let’s wait and see – after all, Daimler Trucks still has its own AV project going on with Torc Robotics …

Volvo Trucks to electrify entire lineup by 2021 – Via electrive

There’s been a lot of news items this year about OEMs electrifying their model range; most recent examples including GM and Volkswagen, whose chairman called EVs “the only reasonable option” for the future.

One piece that was not quite as popular was this one from Volvo Trucks – which piqued my interest because electrification in commercial vehicles (save for buses) hasn’t been that much of a hot topic in my opinion. That might change quite soon, with Volvo promising EV options for their entire range, starting next year in Europe.

シミュレーション用Mapflix – Via atlatec

Cut down on delivery times and budget demands for HD maps: The atlatec OpenDRIVE database gives you instant access to over 1000 km of real-world HD maps. Our founder and CEO Dr. Henning Lategahn calls atlatec database “Mapflix for Simulation”: it is as easy to access and is cost-efficient.

Honda Wins World-first Approval For Level 3 Autonomous Car – Via International Business Times

It’s actually happening: Starting in Q1 of next year, the public will be able to buy a new Honda, capable of L3 automation – the first SAE level to actually be considered “automated driving” rather than “driving support”. To start, the vehicles will only be taking over operation on highways, and only in limited situations, such as stop-and-go traffic. To me personally, that’s one of the most tedious driving situations, though, so automating it should be a great value add for people in areas prone to traffic jams.

UK to ban sales of new diesel and gasoline cars in 2030 – Via CNBC

Easily the most underreported piece of news to me this month: The UK has decided to ban the sale of new petrol/diesel driven vehicles from 2030 (hybrids from 2035). Sure, Norway is 5 years earlier – but the UK is a rather different animal, both in terms of population and economy. While I feel this is an exceptionally brave move and hope to see it turn into a success, I remain somewhat sceptical: The required infrastructure alone will be a massive feat – and ten years can be a much shorter time, especially if you are also dealing with Brexit and a worldwide pandemic right when you start.

Atlatec joined forces with TrianGraphics to Create 3D Visualization of San Francisco HD maps – Via atlatec

And some more news from atlatec: We’ve released an expanded version of our San Francisco HD map sample – one that includes 3D assets and textures, for use in CarlaVTD and other simulations, entirely free! Visit the article to read more about the data, which was created in a collaboration with Trian Graphics, see a video and grab a download link. And if you do: Be sure to tell us what you think!

Just like last month, we got on a Zoom talk with Henning Lategahn and Tom Dahlström to discuss some of these news – the video is now available on YouTube. We hope you enjoy this issue!



December 2019 in Automotive Innovation

I hope you had lovely holidays and would like to extend my best wishes for the new year! 2020 is going to be an exciting one for us at atlatec, and I hope the same is true for you. Speaking of exciting stuff, here’s some news from our industry that stuck out this month – enjoy the read:

“Bosch and Daimler Launch San Jose Robotaxi Pilot” – via Forbes

Just a few weeks after Daimler’s new chairman Ola Källenius announced the company would cut down its investment in robotaxis, the car maker has now launched a pilot service in San Jose, collaborating with Tier1 supplier Bosch. The service is only open to a select group of pilot users (who are company employees) and there’s going to be both a safety driver and a separate engineer on board with passengers. However: “Daimler and Bosch hope to begin offering service to the general public in San Jose as soon as possible” – let’s see when that will turn out to be.

“Mitsubishi, NTT to buy 30% stake in digital mapping company HERE” – via Reuters

It’s been 4 years since BMW, Daimler and Audi teamed up to buy HERE from Nokia, aiming to build proprietary mapping competence rather than relying on (and being dependent upon) US tech companies. Now they’re going to share with Mitsubishi and Japanese telco provider Nippon Telegraph and Telephone (NTT). The goal, according to HERE’s CEO Edzard Overbeek: “[F]urther diversifying our shareholder base beyond automotive, which is important given the appeal and necessity of location technology across geographies and industries.”

“Tesla Release Electric Car Patents To Public” – via IFLScience

60 years ago, when Volvo invented the 3-point seat belt, they decided to open the patent to other car makers for free: The potential for saving lives was more important than clinging to intellectual property. If you thought such decisions for the common good couldn’t happen in today’s economy (like I did), Elon Musk proved you wrong this December, opening Tesla’s EV patents to other companies. The move might also make sense from a business standpoint, however: If it helps to drive the electrification of traffic as a whole, it stands to reason that more customers will look to buy an EV – and thus consider a Tesla.

“We Need to Move Beyond the Car” – via Cruise Automation/Medium

This one’s less of a news item in the sense that it describes a new technological feat by GM’s self-driving car company Cruise – but I felt it’s an important piece, taking a step back to reflect on the automotive industry’s overall approach and asking the question whether we’re even solving for the right problems: “Despite making up less than 1% of all vehicle miles traveled, ride-sharing has added further congestion, more emissions, and potentially even decreased safety in our cities from over-tired and overworked drivers.”

“Real-world road and traffic data for simulation” – via atlatec/YouTube

In closing, I have some atlatec news to offer in the form of a video: We are now able to offer real-world traffic data (in addition to maps) for use in simulators, such as IPG’s CarMaker. We and our pilot OEM customer for this technology are confident that this kind of real-world content will be very helpful for digital validation of AV/ADAS systems that are supposed to react to traffic and other moving agents, such as adaptive cruise control, cross-traffic alerts, adaptive high-beam control and more – what do you think?

That’s it for this month – have a happy new year and see you at CES in Vegas!

If you have any remarks about the pieces linked above, please don’t hesitate to leave a comment or reach out! I’m always happy to have a conversation and remain available by email or on LinkedIn. Speak soon!

Reminder: We also offer this monthly Automotive Innovation overview as a newsletter – if that sounds interesting to you, you’re more than welcome to sign up here.



ADAS /自動運転車の分野で働いている場合は、おそらくHDマップ(3Dプロファイル、運転規則、車線の相互接続性などを含む実際の道路の仮想再現)に精通しているでしょう。

これらのHDマップの多くは シミュレーション ドメインに存在し、自動車メーカーやサプライヤーはそれらを活用して新しいADAS / AVシステムをトレーニングしたり、これらのドメインの機能の検証及び妥当性確認(V&V)を行います。ここで、ゼロから作成された一般的な架空のルートではなく、実際の道路のHDマップを使用する理由は非常にシンプルです。最終的には、システムを現実の世界で実用化する必要があるため、シミュレーションから始めて、できるだけ早く現実世界に合わせて最適化する必要があります。ご存知のとおり、現実の世界ではランダムに事象が発生し、全く同じ事象は起こりません。ですので、実際の道路を元に生成されたHDマップを使用すると、 一般的なデータセットではめったに見られない多くの状況に遭遇するかと思います。これが多くのケースで実際の道路を元に生成されたHDマップが活用されている理由になります。

ここまでは問題無いです。これらのHDマップを使用して、車線維持支援システムまたは車線逸脱警報システムを適切にトレーニングし、制限速度標識の検出やその他の多くのシステムを妥当性検証を行う事が出来ます。 ただし、マップに含まれているのは静的な地物情報のみで、このままでは周辺の交通参加者に反応する様なADAS / AVシステムへの活用については疑問が残ります。緊急ブレーキシステム、クロストラフィックアラート、またはアダプティブクルーズコントロールはすべて、車両周辺の他の車、自転車、または歩行者の行動に応じて、異なるパフォーマンスを発揮する必要があります。その為、シミュレーションでこのようなシステムを適切にトレーニングまたはテストするには、HDマップだけでは不十分であると言えます。

シナリオデータ:HDマップ + 交通流データ



おそらく、現実世界の交通流(動的)は、現実世界の地図(静的)よりも複雑と言えます。 一般的に単純と思われる交差点の交通状況を再現する場合においても、交差点で停車する車両の数などは殆どの場合再現する事は難しいです。 実際のドライバーは、それぞれが独自の運転スタイル、好み、非常に多様な経験、無限の複雑さを持つ人間です。 更には、機嫌の悪い日もあります。


自車両が走行するルートに接続する全ての道路がシナリオデータ(HDマップ化して使用)として使用されるとは限りません。その為このシナリオのケースではいくつかの車両がHDマップの外で表示されたり、非表示となったりします。これは、特定のケースに関係する機能のみを再現する、またはよりまれなケースのテストを可能にする方法でデータを操作する代表的な一例です。 例えば、路上に停車している車、たとえそれがどこからともなく現れた車であっても、正確に識別する為には、フロントビュー/レーダーシステムを必要とするでしょう。これにより、実際のデータを使用して、より極端な状況や事故をシミュレートするにはどうすればよいかという次のトピックに進みます。


システムの限界を知る場合、そのシステムのパフォーマンスを超えたシナリオをシミュレーションする必要があります。 1つの例としてイマージェンシーブレーキアシスト(EBA)を挙げると、現実世界でこのシステムが機能しなかった場合のデータを取得する事は非常に難しい事は容易に想像できます。その機能の評価用データの収録の為に、事故の発生を期待しながら運転を続ける事は現実的ではありません。 ここで、シナリオのファジングが必要になります。

シナリオベースのシミュレーション用に最適化されたツールチェーンを使用して、シナリオの特定の変数を選択し、それらを微調整する事が出来ます。 例えば、測定用車両の速度を数km/h上げる事も出来ますし、他の車両が前方にCut-inする距離を短くする事も出来ます。 これを少しずつ繰り返していくと、最終的にEBAが衝突を回避出来ないシナリオにたどり着きます。そしてその結果、(一般的に)エッジケースやシステム限界として参照されるシナリオの抽出が可能となります。 2つの変数(自車両の車速とCut-in車両との距離)の組み合わせにより、最小距離を実現する車速、そしてその逆も特定出来ます。その結果として、2つの変数に依存するエッジケースを複合的に発生させる事で、コーナーケースを再現する事が出来ます。


atlatec hd map scenario fuzzing


このトピックをより深く探求する為に、いくつかのビデオのサンプル(上のスクリーンショットが取られたものを含む)を確認されたい場合は、今年のIPG Automotive社主催「Apply&Innovate」に於けるプレゼンテーション「Edge Case Hunting in Scenario Based Virtual Validation of AVs」をご覧になることをお勧めします。

Field Operational Testing中のシナリオの収録

現実世界で対象のシステムに関連するシナリオの多数または、エッジケースに相当するシーンに遭遇する一つの機会はField Operational Testing(FOT)になります。 これはOEMやTier1サプライヤーもしくはそれらのパートナー企業が実施する何千kmにも渡る公道試験を指します。これらのテストドライブは、規制当局による最終承認の前提条件として、システムが公の場でテストするのに十分安全であると見なされたときに実行されます。


このような状況が発生した場合、それはシステムの妥当性確認や検証をしているエンジニアにとっての情報の宝庫です。これらのドライブ中に記録されたすべてのオンボード・データは、少しでも問題が有れば原因を特定し、エラーがあれば修正するために、可能な限り詳細に分析されます。 ただし、オンボードデータは、システムの「思考」が何を起こしたかを示すだけです。不検知または誤検知を探している場合(センサーデータ上などで)、このデータを実際に起こったことと照合する必要があります。


atlatec scenarios hd maps


ご不明な点がある場合や、シナリオの活用方法についてご質問がある場合は、メールにてご連絡いただくか、ソリューションタブ内のシミュレーションのパートにある email or request a meeting with us. 

Author: Tom Dahlström, atlatec Gmbh



Netflix is great. You browse the catalog and pick the movies you like. It takes minutes only. It’s quick, it’s easy and it’s cheap. Selecting a movie and start watching is a lot faster than producing one and, well, less expensive. 

We offer real-world data for simulation just like netflix, too. We have a データベース of ready-to-use 3D maps that serve as content in virtual environments and are in use for ADAS and AV simulation around the globe. These 3D maps are augmented with real-world traffic and enable scenario-based virtual validation. You, too, can look around and pick what suits your specific needs, pay for the subscription and only as long as you need it. You start testing immediately.

The image below shows the real world and its digital clone side-by-side.


Using simulation to validate ADAS and AVs is commonplace today. The burden of testing every feature, every update and every setting in the real world is unbearable whereas validation and testing in virtual environments can be done overnight. Many excellent software suites have emerged over the last years and the list in the comments section below shows many of them.

Software alone, however, is not enough. Simulation becomes as random as the real world only when backed by real-world data such as 3D maps and scenarios. Waymo is a prime example of following this approach. Combining state-of-the-art simulation software with real-world content is key. A recent TrechCrunch article suggests to prioritize and invest in virtual testing.

Prioritize and invest in virtual testing. Developing and operating a robust system of virtual testing may present a high expense to AV companies, but it also presents the opportunity to dramatically shorten the pathway to commercial deployment through the ability to test more complex, higher risk and higher number scenarios.

Mountains of canned, real-world content reduce the price for an entry ticket into this ability to test more complex, higher risk and higher number scenarios

We offer a database of 3D maps from North America, Europe and Japan and offer it as a subscription. These 3D maps capture the real world and make it available for use in your existing simulation ecosystem. In addition to the 3D maps we add an additional layer containing moving objects. Maps and moving objects form scenarios of short length (seconds to minutes) that stress-test your ADAS or AV stack. Scenarios can be modified with our software to form edge- and corner cases. The best part is: The database grows continuously providing more and more cases over time. And, you pay only for what you need. 

The world-to-simulator transform is shown in the images below.


We launch our database subscription with pilot customers now and we need your help. Just like netflix, too, we need to understand what you would like to have (is it Lord of the Rings, Frozen or Sharknado?). If you would like to talk to one of our experts then please contact us via email or schedule a meeting with one of our mapping experts.

This blog article was written by atlatec founder and CEO Dr. Henning Lategahn. Feel free to reach out to Henning via LinkedIn.



There are a lot of differences of opinion in the autonomous vehicle space, but one thing everyone can agree on:

Virtual training and validation of AV/ADAS systems and components are a key factor in achieving the massive scale of testing which is necessary.

To this end, we at atlatec are always working to support more simulation tools, allowing our customers to continue working with their toolchain of choice when leveraging our HD maps.

Today, we are happy to announce the newest addition to our list of supported simulation software: Cognata.

Cognata is a cloud-based simulation platform designed specifically for autonomous driving and ADAS applications and is used for AV training, validation and analysis. It offers several datasets to test AV components against, such as traffic lights, signs, pedestrians and vehicles.

By importing atlatec HD maps, Cognata customers will have the added benefit of training and testing on road environments that are highly accurate digital twins of real-world routes, ensuring a more robust system performance and similar results to a real drive-test. The maps are supplied in the OPENdrive format.  

If you are a Cognata user and interested in learning more about how to leverage our HD maps, please reach out via email or schedule a call with us.



Another month is over – and while Covid-19 seems to be flaring up again all over the world, it’s not the only news out there: The automotive industry, which was hit hard by the Corona crisis has produced some interesting news items this October. Here’s my personal overview of what stuck out:

European Safety Assessment Slams Tesla Autopilot for Its Inability to Keep Drivers’ Attention – via The Drive

This month, Tesla released the beta version of its “Full Self-Driving” system to a limited batch of paying customers. The resonance has been mixed and there’s lots of video and more out there, showing situations which FSD apparently handles well – or not. This article got a bit lost in the wake of all this – but I feel it emphasizes an underlying conflict of any self-driving tech relying on drivers’ attention: The better the self-driving performance and user experience, the less attention “drivers” will pay – and the less they’ll be prepared to take over in critical situations. Tesla’s user experience is apparently the worst at keeping drivers’ attention in auto mode, as per this recent NCAP analysis.

Bonus: I also recommend a look at this Twitter thread by Voyage CEO Oliver Cameron who took the time to analyze footage from one of the first test drives in detail.

Waymo will allow more people to ride in its fully driverless vehicles in Phoenix – via The Verge

Waymo, arguably a leader in the autonomous vehicles domain reached another milestone this month: The Google company will open up its driverless robotaxi service in Phoenix to about 1 000 app users, who can now request rides without safety drivers onboard. Remote operators will be on standby to take control of the vehicles if necessary, but Waymo expects little work for them.

Cruise can now test driverless vehicles on the streets of San Francisco – via The TechCrunch

Cruise, a subsidiary of General Motors, is not yet offering rides to the public but got approval by the Californian DMV “to test five autonomous vehicles without a driver behind the wheel on specified streets within San Francisco.” This is the fifth permit for driverless testing after Waymo, AutoX, Nuro and Zoox and it comes with some restrictions: “The Cruise vehicles are designed to operate on roads with posted speed limits not exceeding 30 miles per hour, during all times of the day and night, but will not test during heavy fog or heavy rain, the DMV said.” 

There’s an ongoing discussion about the ethics of these public-roads tests: On the one hand, companies are supposed to “verify vehicles are capable of operating without a driver” to get a permit, but on the other hand those tests are being conducted with the specific purpose to verify this in the first place – they are tests, after all. This has potential for further controversy, and further underlines the need for comprehensive, real-word-based simulation ahead of on-road operations.

Lynk & Co’s compact SUV costs €500 a month but might earn you a profit – via The Verge

This was relatively unnoticed news this month, but I find it worth noting because GEELY’s Lynk & Co. brand is attempting to redesign one of the basic fundamentals in automotive: The relation between car ownership and access to (car-based) mobility.

What Lynk & Co. is offering with the new “01” model is a built-in car-sharing platform, complete with mobile apps to unlock vehicles by phone etc. Individuals can take out a lease on a 01 (around 500 EUR a month, including service by Volvo dealerships) and then offer it for use via the platform – defining when it’s available and how much they want to charge to rent it out to other users, who don’t pay for vehicles/leases themselves. Sure, car sharing is nothing new – but if done right, this could bring a new level of convenience to the game which might really make a difference.

I find this move a) very brave, because it essentially means a commitment to sell less cars by GEELY and b) very innovative to come from an OEM because it doesn’t attempt to solve any and every mobility challenge by adding more, or better vehicles but instead truly treats mobility as a commodity. The new car – and service – will pilot in Amsterdam, arguably one of the major European cities which has done most to move away from traditional car ownership models.

How Accurate Are HD Maps for Autonomous Driving and ADAS Simulation? – via atlatec

It’s definitely one of the most frequently asked questions for us here at atlatec: “How accurate are HD maps”? It sounds innocent, but answering it correctly is rather complex. However, we feel that the question is important, both when it comes to safety in autonomous vehicle operations and regarding the validity of simulations based on real-world maps.

This month, we’ve therefore taken the time to answer the question comprehensively; taking a close look at what accuracy really means in the context of HD maps – and of course we’re also putting numbers to what atlatec achieves in this domain.

As a first this month, we took to Zoom to discuss some of these news items internally – and we recorded it: Tune in to hear what our CEO, Henning Lategahn thinks about the developments at Tesla and Lynk & Co. and for a some more explanation on the topic of HD map accuracy on our YouTube channel!