FUNDING ($K) FY05 FY06 FY07 FY08 FY09 AFOSR Funds150K 150K 150K AFOSR/DURIP 150K
Road to Robots...2017 8k units $200k 10k units $1B $2B $2B 2022 65k units $150k 150k units $15B $30B...
Transcript of Road to Robots...2017 8k units $200k 10k units $1B $2B $2B 2022 65k units $150k 150k units $15B $30B...
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Road to RobotsSensors and Computing for Autonomous
Vehicle
Guillaume GIRARDINDivision Director
Photonics, Sensing and Display
Yole Developpement
Yohann TSCHUDILead Analyst
Software and Computing
Yole Developpement
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Robotic
car
players
0 2 3 541ADAS Levels
20172010 2025 2035
Traditional ADAS
car makers
While traditional car makers are
integrating autonomous
functions in consumer cars little
by little, new-comers have
challenged this approach by
short-cutting technological
developments and proposing a
new business model:
transportation as a service, TaaS.
This move has triggered new
investments in sensor
technologies.
Fully
autonomous
vehicles in
2017
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AUTONOMOUS VEHICLES - THE DISRUPTION CASE
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0
20
40
60
80
100
120
140
160
AD
AS
vehic
le s
ales
(Munits)
Robotic and Light vehicle sales breakdown forecast by level of autonomy
ADAS Level 0 ADAS Level 1 ADAS Level 2 ADAS Level 3 ADAS Level 4 ADAS Level 5 Robotic cars
02 3
541
By 2045, more than 70% of all vehicles sold will integrate autonomous capabilities!
Now
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2017 AUTOMOTIVE LANDSCAPE - MAJOR PLAYERS’ REVENUE
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SENSORS IN AUTOMOTIVE - THREE MAIN SENSOR CATEGORIES
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AUTOMATION LEVELS - ROADMAP
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SENSOR MODULE ASP FOR EACH AUTOMATION LEVEL – ONLY SENSORS!
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FREQUENCY REGULATION
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AUTOMOTIVE LIDAR PLAYERS
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BIG PICTURE OF LIDAR MARKET OPPORTUNITIES TIMELINE
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SENSORS FOR THE AUTOMOTIVE INDUSTRY – ECOSYSTEM VALUE
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ROBOTIC VEHICLE TECHNOLOGY
Main player sensor suite
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ROBOTIC VEHICLE MARKET TREND
Emergence of the robotic vehicle market
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Year Production Vehicle cost
per unit
On the road Revenue @
$0.43/mile
Revenue @
$0.86/mile
Vehicle capital
on the road
2017 8k units $200k 10k units $1B $2B $2B
2022 65k units $150k 150k units $15B $30B $22B
2027 350k units $110k 1M units $100B $200B $110B
2032 1,200k units $95k 5M units $500B $1T $475B
Average speed
40km/h
30mph
Distance covered
~900km/day
~700miles/day
Distance covered
~300,000km/year
~230,000miles/year
Revenue
€100,000/year
$100,000/year
@ €0.33/km
@ $0.43/mile23h per day10% down time
330 days /yearEuropean city
American city
Assumptions
Expected use case takes into account ~$0.43 to $0.86 per mile
ROBOTIC VEHICLE ECONOMICS
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ROBOTIC VEHICLE SENSING TECHNOLOGY TREND
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ROBOTIC VEHICLE SENSOR REVENUE FORECAST
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AUTOMOTIVE ADAS SUPPLY CHAINS
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AUTOMOTIVE ADAS VISION PROCESSING
Vision processing for automotive will triple revenues before 2021
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COMPUTING FOR ROBOTIC VEHICLES ECOSYSTEM
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WHAT IS FUSION ? • Sensor fusion uses sophisticatedartificial intelligence (AI) and deeplearning-based algorithms;
• Complex use-case scenarios expectedof driverless cars can be understood.
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WHICH SET OF SENSORS FOR AUTONOMY?
• Cameras, Radars, LiDAR & Ultrasonic sensors• Combination of 2 or more type of sensors are
needed to reach autonomy
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WHICH HARDWARE SOLUTION TO CHOOSE?
Example of Audi’s solution
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• Convoluted Neural Networks (CNN) approach is king. Mobileye along with its foundry partnerSTMicroelectronics has proved the superiority of CNN to bring real time image analysis on the road.All players are therefore investing in such approaches. New alliance between Mobileye and Intel showsthe appetite for automotive vision processing.
• GPU power is well used by infotainment system and data handling. The involvement of NVIDIA issignificant in this domain. Following the Mobileye Tesla divorce, NVIDIA will provide an integratedapproach with home brewed CNN inference processors.
• Multicore CPU based DSPs are still heavily used and are bringing all computing aspects. Intel,Renesas, Toshiba, TI, ST and NXP are among the numerous players in this field. The merge of NXPwith Qualcomm would create a heavyweight in this domain.
• FPGA are very well suited to the high end segment and implementation of emerging features. Thisflexible platform should have access to the emerging autonomous vehicle market. Xilinx leads thisdomain by far.
• The Manycore approach such as the one by Kalray emerges as a great proposition for addressing theautonomous vehicle trend.
WHICH HARDWARE SOLUTION TO CHOOSE?
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ROBOTIC VEHICLE COMPUTING SUITE
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MARKET MAP – AI FOR AUTONOMOUS AUTOMOTIVE
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FROM SENSORS TO FUSION
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www.i-micronews.com [email protected]
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FIELDS OF EXPERTISE COVERED BY OUR 40+ ANALYSTS WITHIN 4 DIVISIONS
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3 BUSINESS MODELS
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6 COMPANIES TO SERVE YOUR BUSINESS
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OUR GLOBAL ACTIVITY
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SERVING THE ENTIRE SUPPLY CHAIN
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REPORTS COLLECTION
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OUR 2018 REPORTS COLLECTION (1/3)
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OUR 2018 REPORTS COLLECTION (2/3)
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OUR 2018 REPORTS COLLECTION (3/3)