

AI’s Down the Road: Accelerating Innovation in the Automotive Industry
09-11-2023

<p class="MsoNormal"><em><span style="font-size: 12pt; line-height: 107%; font-family: "Segoe UI", sans-serif; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-attachment: initial; background-origin: initial; background-clip: initial;"><font color="#ffffff">In recent
years, AI's integration into the automotive sector has brought about a wave of
advancements. From self-driving cars and advanced driver-assistance systems to
enhanced manufacturing processes, the impact of AI on the automotive industry
is nothing short of revolutionary.<o:p></o:p></font></span></em></p><p class="MsoNormal"><em><span style="font-size: 13.5pt; line-height: 107%; font-family: "Segoe UI", sans-serif; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-attachment: initial; background-origin: initial; background-clip: initial;"><o:p><font color="#ffffff"> </font></o:p></span></em></p><p class="MsoNormal"><b><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">Finding the answer to chip shortage<o:p></o:p></font></span></b></p><p class="MsoNormal"><font color="#ffffff"><span style="font-family:"Segoe UI",sans-serif">The
automotive industry is grappling with chip shortages. Specifically, this
shortage places immense pressure on manufacturers, resulting in a shortfall of
around 3 million vehicles in 2023 </span><a href="https://arstechnica.com/cars/2022/12/automotive-chip-shortages-to-continue-throughout-2023-industry-says/#:~:text=And%20the%20analysts%20at%20AutoForecast,million%20lost%20vehicles%20in%202021"><span style="font-family:"Segoe UI",sans-serif">[1].</span></a><span style="font-family:"Segoe UI",sans-serif"> One solution to this issue is to
reduce the amount of NAND chip storage required within vehicles, which is the
non-volatile flash memory commonly used in various electronic devices for
storing data and software.<o:p></o:p></span></font></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">In
automotive electronics and software updates, NAND chip storage plays a vital
role by holding essential software components, configurations, and necessary
data. This storage is organized into partitions within the memory, effectively
managing different types of data and software. Specifically, using dual
partitions in the endpoint memory of NAND chips is a common practice. However,
the current approach of using dual partitions demands double the NAND chip
memory and may potentially affect other Electronic Control Units (ECUs) within
the vehicle. When an update fails, it could trigger a chain reaction and
require rollbacks in other areas of the car, which may not always be feasible. <o:p></o:p></font></span></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">Therefore,
AI-powered technology offers an innovative solution by providing <b><i>differential
updates</i></b>. Instead of storing entire software packages for updates, AI
algorithms analyze the differences (or "differentials") between the
existing software version on the vehicle's NAND chip and the new version. AI
then stores only these differentials rather than the entire update package,
which can be significantly smaller. <o:p></o:p></font></span></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">Besides, AI
also provides <b><i>in-place updates</i></b>. This method writes an executable update file
to the next available space on the chip without erasing previous versions. This
substantially decreases space requirements and allows manufacturers to revert
to any previous software version without a second bank of flash memory. <o:p></o:p></font></span></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">AI can also
optimize the storage of NAND flash memory by managing memory blocks and
allocating them based on the software's usage patterns. Frequently accessed
software components are stored in readily accessible memory blocks, while
less-used elements are compressed. This adaptive memory management ensures
storage space is used more efficiently, reducing the need for larger NAND chips
in the automotive industry.<o:p></o:p></font></span></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff"> <o:p></o:p></font></span></p><p class="MsoNormal"><b><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">Ensuring drivers’ safety<o:p></o:p></font></span></b></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">One
fundamental role that AI plays in enhancing driver experience is its ability to
process data from an array of sensors, including cameras, LiDAR, and radar, to
create a comprehensive view of a vehicle's surroundings. This capability can
enhance safety by planning and adapting driving routes in real-time, steering clear
of obstacles, and optimizing the driving experience.<o:p></o:p></font></span></p><p class="MsoNormal"><font color="#ffffff"><b><i><span style="font-family:"Segoe UI",sans-serif">Advanced Driver
Assistance Systems (ADAS)</span></i></b><span style="font-family:"Segoe UI",sans-serif">
utilize various technologies, including AI as one of the prominent
applications. Through the incorporation of AI, ADAS can help drivers with
lane-keeping assist, automatic emergency braking, adaptive cruise control, and
parking assist. These systems rely on AI algorithms and sensor data to monitor
the vehicle's environment, identify potential hazards, and aid drivers in
achieving collision-free driving and parking. With a staggering 94% of all road
traffic incidents caused by human error </span><a href="https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812456"><span style="font-family:"Segoe UI",sans-serif">[2]</span></a><span style="font-family:
"Segoe UI",sans-serif">, regulatory bodies are taking action to enhance safety.
The European Commission, for instance, has introduced new rules with specific
ADAS requirements in all vehicles by 2024, requiring automakers to adopt the
requisite software and technology to meet these standards </span><a href="https://ec.europa.eu/commission/presscorner/detail/en/IP_22_4312"><span style="font-family:"Segoe UI",sans-serif">[3]</span></a><span style="font-family:
"Segoe UI",sans-serif">.<o:p></o:p></span></font></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff"> </font></span></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">Furthermore,
AI extends its influence to <b><i>Advanced Driver Monitoring</i></b> systems,
which can continuously assess driver behavior for signs of distraction or
fatigue. These systems typically use a combination of sensors, including
cameras, infrared sensors, and steering angle sensors. These sensors
continuously collect data on the driver's actions and the vehicle's
environment.<o:p></o:p></font></span></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">For example,
AI can identify patterns such as erratic steering, frequent lane departures,
long periods without any steering input, eye movements, facial expressions, and
head movements. When necessary, these systems can issue visual and auditory
warnings, or even take control to ensure the safety of all occupants. Thus, AI
can redefine the driving experience, making it not only more convenient but
also significantly safer.<o:p></o:p></font></span></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff"> </font></span></p><p class="MsoNormal"><b><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">Visioning the car of the future<o:p></o:p></font></span></b></p><p class="MsoNormal"><font color="#ffffff"><span style="font-family:"Segoe UI",sans-serif">AI can help
manufacturers develop smarter cars. Using AI-powered simulations, companies can
test designs virtually before making physical prototypes. By automatically
generating 3D models of car components from 2D drawings, AI allows quicker
design iterations. This can expedite the development cycle and result in fewer
expenses and faster time-to-market. According to research, generative design
can help reduce design time by up to 50% and cut material costs by 20% </span><a href="https://gpiengineers.com/using-ai-in-engineering-design/"><span style="font-family:"Segoe UI",sans-serif">[4]</span></a><span style="font-family:
"Segoe UI",sans-serif">.<o:p></o:p></span></font></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">Additionally,
AI can be used to detect and correct errors in design models. AI-powered vision
systems can inspect parts and products with incredible precision, detecting
even the slightest defects or inconsistencies. Machine learning algorithms are
trained to recognize defects based on a large dataset, ensuring high accuracy
in quality control. In an automotive manufacturing plant, AI-based vision systems
inspect painted car bodies for imperfections such as scratches, dents, or color
mismatches. Any faulty parts are automatically flagged for rework or removal,
ensuring that only high-quality products reach the assembly line.<o:p></o:p></font></span></p><p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">AI-powered
analytics and insights enable automakers to track the performance of their
vehicles in real-time, making it easier to anticipate potential issues. This
ensures that any problems can be addressed quickly and prevents costly recalls.
AI-driven predictive maintenance systems use sensors and data analytics to
monitor the condition of machinery and equipment in real-time.<o:p></o:p></font></span></p><p class="MsoNormal"><b><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff"> <o:p></o:p></font></span></b></p><p class="MsoNormal"><b><span style="font-family:"Segoe UI",sans-serif"><font color="#ffffff">Driving the potential of AI<o:p></o:p></font></span></b></p><p class="MsoNormal">
</p><p class="MsoNormal"><font color="#ffffff"><span style="font-family:"Segoe UI",sans-serif">The future
of the automotive industry appears promising, yet it's important to acknowledge
that AI is an emerging technology. In fact, the AI market within the automotive
industry was valued at USD 6 billion in 2022, and it is projected to experience
a remarkable CAGR of 55% from 2023 to 2032 </span><a href="https://www.gminsights.com/industry-analysis/artificial-intelligence-ai-in-automotive-market#:~:text=Industry%20Statistics,will%20drive%20the%20industry%20growth.]"><span style="font-family:"Segoe UI",sans-serif">[5]</span></a></font><span style="font-family:
"Segoe UI",sans-serif"><font color="#ffffff">. Thus, the automotive sector must utilize AI with great
caution to fully unlock its potential.</font><o:p></o:p></span></p>