Autonomous Vehicle Engineering - March 2021 - 3

The Navigator
Mapping the way to safe and natural
automated driving
When it comes to automated driving systems
(ADS), Tesla CEO Elon Musk often runs counter
to the consensus of almost everyone else in the
sector. His disdain for lidar sensing is well-known,
but during Tesla's April 2019 Autonomy Day, Musk
said " high-precision GPS maps are a really bad
idea. " Almost every other AV developer is on the
other side of that idea - including sensor-systems
powerhouse Mobileye - and makes extensive use
of high-definition maps.
During his now-annual keynote at the CES
conference, Mobileye CEO Amnon Shashua
discussed several aspects of the SAE
Level 4 automated driving system
the company is developing, but one
section was devoted exclusively to
mapping. In December 2020, Mobileye
expanded its automated-driving
development program to Detroit, with
Tokyo, Shanghai and possibly New
York being added this year.
For most ADS developers,
expanding operations into a new area
typically starts with spending four to
six weeks just building a high-definition map of the area. Shashua
claimed that Mobileye can begin
testing almost immediately because
of its crowd-sourced AV maps. Note
that Shashua refers to them as " AV
maps " rather than simply HD maps.
The typical approach to building HD maps is
for the automated-development team to drive the
roads in the area multiple times, capturing all of the
raw sensor data. From this, the map is built with
information about the road configuration, drivable
paths, speed limits, traffic signals and static landmarks that can be used for localization. This is the
physical map.
Since 2018, vehicles from BMW, Volkswagen,
Nissan and Nio equipped with Mobileye's

EyeQ4-based driver assistance have been
collecting data and feeding it back to the Road
Experience Management (REM) platform, where
it is aggregated into these maps. More than one
million vehicles have now built up more than 700
million km (435 million miles) of physical maps
with 8 million more km (5 million miles) being
updated daily.
But what sets Mobileye apart from most other
AV companies - and allows for quick startup - is
the semantic map. Vehicles contributing to REM
are providing data on the actual path driven by
vehicles on the road, typical speeds
and actual stop and yield points. This
is important to enable an AV to fit in
seamlessly with driving patterns in a
particular region.
For example, a vehicle may
stop at the designated line before
making a turn and then ease forward
to get a clearer view of cross traffic
before executing the turn. Capturing
the position where other vehicles
actually stop and replicating that
with the AV allows the development teams to quickly start testing
as they move from Jerusalem to
Detroit to Shanghai.
It's never that simple, of course.
As recent winter weather in Michigan
has demonstrated, systems also need understanding of road conditions and other variables
to safely manage driving behavior. All of that is
doable. Building this semantic understanding of
the environment into the ADS can make these
systems safer and more robust. Other ADS entities
need to think about this as they build their own
map systems.
Those relying on artificial intelligence to simply
guess only from what cameras can see in real time
probably will not succeed. ■

Sam Abuelsamid
Principal Analyst,
eMobility
Guidehouse Insights
sam.abuelsamid@
guidehouse.com

Winter weather
demonstrates
that ADS
also need
understanding
of road
conditions
and other
variables to
safely manage
driving
behavior.

AUTONOMOUS VEHICLE ENGINEERING

March 2021 3

Autonomous Vehicle Engineering - March 2021

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