Hi, everyone, and welcome back.
My name is Janet Ooi, and I'll be taking you on a journey
to understand the complex challenges automotive OEMs and Tier 1 suppliers face
in testing ADAS and AV functions in modern vehicles.
Before that, let's hear from Steffen Schmidt, the CEO of IPG Automotive,
who will share more about the development trends of autonomous driving
and how testing will evolve along with the technology advancements.
Future development trends and topics such as autonomous driving or electrification
are strongly driven by software.
The focus of vehicle development is therefore shifting from hardware to software.
Automation in vehicles with ADAS Level 3+
increases and requires testing and validation of a steadily growing number of scenarios,
including their environment.
Not only does the number of tests to be performed rise,
but their complexity is also getting higher.
In the past, with adaptive cruise control,
it was sufficient to pay attention to the vehicle up front.
Nowadays, many different road users have to be taken into account in tests,
for example, for the Highway Pilot.
In addition to following the lead vehicle and keeping a safe distance,
automated maneuvers such as exiting the lane, overtaking, and re-entering the lane
also have to be considered in this example.
The complexity increases even more when driving in cities.
Think about all the different intersection and turning scenarios with pedestrians,
cyclists, mopeds, e-scooters, and so on.
The real test drive on its own cannot represent this level of complexity and variability.
Therefore, the use of simulation is absolutely essential
to develop and validate AV systems.
In addition to camera and lidar sensors, the radar sensor plays a key role.
Radar technology is becoming more and more intelligent and complex.
This makes validation and release
of radar-based assistance systems more challenging.
Due to the high number and complexity of scenarios,
they cannot only be performed in the physical vehicle anymore.
That's right, Steffen.
Radar sensors have evolved significantly over the last decade
and are becoming more and more intelligent and complex.
Radar technology continues to evolve with higher frequency,
wider bandwidth, and better resolution.
In fact, advances in the radar sensor technology
are what's pushing the automation level in vehicles toward Level 3 or 4.
Getting to Level 5 full driving automation
will require representation of total roadway scenes,
ensuring the ADAS and AV decision-making algorithms
are reliable enough for us to trust them with our lives.
The vision is for this technology to fully replace the human behind the wheel
and make reliable, accurate, and safe decisions on the road
under any circumstances.
Let's take a sneak peek into what we will learn in Lesson 3
and how we can achieve the vision of full driving automation in the near future.
Forecasts are optimistic for the growth of the autonomous vehicle market.
Those forecasts depend on the confidence in the minds of consumers,
regulators, and the insurance industry.
Confidence in the safety of advanced driver assistance systems
is built on detailed testing,
but it can take hundreds of millions of miles of road testing, actual or simulated,
to explore corner cases and qualify new designs.
Autonomous operation depends on high-resolution radar and camera systems
working in concert with incoming navigation data.
Business goals for size, weight, and cost are driving the sensor fusion of discrete elements
into compact but complex subsystems.
A typical testing process involves a vehicle on a test track.
Whenever the vehicle approaches a physical target,
the sensor system can be tested.
This open-loop, single-unit method is slow, labor-intensive, costly, and insufficient.
The complementary approach is time-synchronized testing
of complete sensor subsystems.
Using detailed simulations and a closed-loop approach,
this method exercises sensors, electronic control units,
and AI algorithms as an integrated unit.
Working in collaboration, Keysight Technologies, IPG Automotive,
and Nordsys have created an innovative solution
called the Autonomous Drive Emulator (ADE) platform.
Here's how it works:
Each subsystem is mounted in an ADE simulator rig.
The real-time 3D engine creates a virtual environment
that includes full-motion video, dynamic radar signals,
and congested C-V2X scenarios,
4G today and 5G NR in the near future.
The unit under test responds with actions such as braking, steering, and acceleration,
just as it would on the road.
This expedites testing through cumulative hours of simulation
and the measurement of feedback from every element of the ADAS system.
With state-of-the-art realism, the ADE platform enables developers
to confidently test their designs and then focus on the debugging
and fine-tuning of system behavior.
Because the ADE platform is open, it simplifies integration
with a wide range of commercial 3D modelers, hardware-in-the-loop systems,
and existing test and simulation environments.
With AVs, market growth depends on confidence,
and confidence comes from highly realistic testing.
The ADE platform is ready to streamline the test pipeline.
This is just one of the ways Keysight is helping OEMs and their suppliers
realize their vision of mobility.
That's all we have for this lesson.
Join me in the next lesson as we discuss the gaps
between real-world testing and software simulation
of autonomous vehicles or advanced driver assistance systems.