Automotive DMS (Driver Monitoring System) Research Report ... · Automotive DMS Research: DMS...
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Automotive DMS (Driver Monitoring System) Research Report, 2019-2020 June 2020
Transcript of Automotive DMS (Driver Monitoring System) Research Report ... · Automotive DMS Research: DMS...
Automotive DMS (Driver Monitoring
System) Research Report, 2019-2020
June 2020
METHODOLOGY
Both primary and secondary research methodologies were used
in preparing this study. Initially, a comprehensive and exhaustive
search of the literature on this industry was conducted. These
sources included related books and journals, trade literature,
marketing literature, other product/promotional literature, annual
reports, security analyst reports, and other publications.
Subsequently, telephone interviews or email correspondence
was conducted with marketing executives etc. Other sources
included related magazines, academics, and consulting
companies.
INFORMATION SOURCES
The primary information sources include Company Reports,
and National Bureau of Statistics of China etc.
STUDY GOAL AND OBJECTIVES
This report provides the industry executives with strategically significant
competitor information, analysis, insight and projection on the
competitive pattern and key companies in the industry, crucial to the
development and implementation of effective business, marketing and
R&D programs.
REPORT OBJECTIVES
To establish a comprehensive, factual, annually updated and cost-
effective information base on market size, competition patterns,
market segments, goals and strategies of the leading players in the
market, reviews and forecasts.
To assist potential market entrants in evaluating prospective
acquisition and joint venture candidates.
To complement the organizations’ internal competitor information
gathering efforts with strategic analysis, data interpretation and
insight.
To suggest for concerned investors in line with the current
development of this industry as well as the development tendency.
To help company to succeed in a competitive market, and
understand the size and growth rate of any opportunity.Room 2-626, 6th Floor, No.1, Shanyuan Street, Haidian District, Beijing, 100080Phone: +86 10 82600828 ● Fax: +86 10 82601570 ● www.researchinchina.com ● [email protected]
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AbstractAutomotive DMS Research: DMS installations shoot up, with a year-on-year upsurge of 360% in Q1 2020DMS (Driver Monitoring System) is bifurcated into active DMS and passive DMS. Passive DMS judges the driver's statebased on the steering wheel turning and driving trajectory. Active DMS, generally enabled by cameras and near-infraredtechnology, detects the driver's state from eyelid closure, blinking, gaze direction, yawning, and head movements. Onlyactive DMS is studied in this report.
In 2006, the Lexus LS 460 was packed with active DMS for the first time, and the camera was mounted on the top of thesteering column cover with six built-in near-infrared LEDs. Automakers are not interested in active DMS, because theybelieve that it increases the cost of the vehicle and consumers may be reluctant to pay for it. Yet, a train of accidents overthe recent years highlight the importance of DMS in ADAS, especially L2/L3. Active DMS started to soar from 2018, with themassive availability of the L2 system and the to-be-spawned L3 system.
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Euro-NCAP issued a roadmap for 2025, whichrequires that new cars must be equipped withDMS from July 2022. China has legislated themandatory installation of DMS for commercialvehicles, and similar stipulations for passengercars are just around the corner. The active DMSmarket is growing prosperous as relevant chip,software and algorithm vendors are vigorouslypromoting the development of DMS technology.
10,170 units of active DMSwere installed in newpassenger cars in China in2019, surging by 174% onan annualized basis. In2020Q1, the installationsskyrocketed 360% year-on-year to 5,137 units amid thewide use of active DMS inthe models priced betweenRMB150,000 andRMB200,000 and theadoption by WEY, Xpeng,Geely, to name a few.
Most Tier1 suppliers havelaunched total DMSsolutions, including Valeo,Bosch, Continental, Denso,Hyundai Mobis, Visteon,Veoneer, etc. AmongChinese companies, theDMS of Hikvision,SenseTime, Baidu, andDahua Technology havebeen found on various brandmodels.
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Rise of DMS algorithm developers
DMS is used mainly to monitor drivers’ fatigue and distraction. Yet a larger number of sensors, vision + infraredcameras, and even radars mean availability of more functions, e.g., face recognition, age and gender recognition,emotion recognition, seat belt detection, posture, position and forgetting detection, cabin abnormality detection, andinfant detection. Face, gender and expression recognition helps with identity authentication and offers richer interactionbetween human and vehicle. DMS that is now used just for early warning will enable personalized body control andmore functions once it is coupled with ADAS/AD systems.
In Valeo’s case, its AI-driven DMS uses convolutional neural network (CNN) algorithms for emotion recognition andallows unique settings by recognizing the driver’s face.
The versatility, however, cannot be met only by Tier1 suppliers in the short run. That’s why DMS is often co-developedby Tier1 suppliers and algorithm companies.
With years of efforts on development of computer vision technology, ArcSoft Corporation Limited has developed DMS,ADAS and BSD, among others, to meet automobile industry’s needs for vision-related capabilities. The developer’sintelligent driving algorithm business expanded rapidly in 2019, contributing revenue of RMB16.0566 million, asubstantial increase as compared to 2018 (RMB2.2021 million), and rang in RMB17.0076 million in the first quarter of2020, more than the full-year revenue of 2019.
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ArcSoft’s peers such as EyeSight, Smart Eye, FotoNation and Seeing Machine all have been working on developmentof software algorithms for years. Even so, use of DMS technology still faces plenty of tough challenges:
The highest technical barrier before application of vision-based DMS technology is its performance in high or lowlight which may lead to all white or all black images, respectively. In this case, even the most advanced algorithmswon’t work.
How to quantitatively define fatigue and drowsiness also creates a bottleneck to use of DMS. The most effective wayto measure fatigue and define the relation between fatigue and temperature, dermal resistance, eye movement,respiratory rate, heart rate and brain activity, is measurement of pulse and heart rate variability (HRV), but thetechnology is still not mature enough.
Widely varying signal-to-noise ratio and contrast, obscured and dithered images, and light difference in differentweathers and time periods will issue in images of differing brightness.
Face detection challenges: in-plane rotation of face; out-of-plane rotation of face; existence of cosmetics, beard andglasses; expression (happy, cry, etc.); obscured face; real-time processing requirements.
DMS latency caused by insufficient computing power, communication, etc..Interference to users caused by too many false alarms.
Few sample databases for training algorithms.
Companies are trying to add more sensors and more powerful chips to solve the problems that vision cameras fail toaddress in multiple scenarios.
Hardware improvement and cockpit monitoring
In May 2019, OmniVision Technologies and Shanghai Fullhan Microelectronics announced a joint solution for capturingand processing high quality color (RGB) and infrared (IR) automotive interior images, day and night, with a single camera.This solution combines OmniVision’s OV2778 2MP RGB-IR image sensor which offers high sensitivity across all lightingconditions with Fullhan’s FH8310 image signal processor (ISP). The result is high quality video for both machine vision in-cabin monitoring systems (IMS) and viewing applications, simultaneously, providing integrated solutions for facialrecognition, the detection of objects and unattended children, remote monitoring, and recording for ride-hailing androbotaxi vehicles.
In June 2019, Vayyar, an Israeli startup, announced the launch of the first automotive 4D point cloud application on asingle radar chip. The single chip with point cloud displays the dimension, shape, location and movement of people andobjects, enabling the complete classification of the car’s environment, regardless of bad lighting or harsh weatherconditions. In-cabin solutions include seat belt reminders, optimized airbag deployment, gesture control, driverdrowsiness alerts, and infant detection alarms.
In September 2019, ON Semiconductor rolled out a complete in-cabin monitoring system inclusive of driver monitoringand occupant monitoring functions. The demonstration includes three ON Semiconductor 2.3-megapixel RGB-IR imagesensors. This multi-camera system utilizes Ambarella’s CV2AQ System-on-Chip (SoC) and integrates Eyeris’ AI softwareperforming complex body and facial analytics, occupant activity monitoring, object detection, among others.
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In February 2020, Analog Devices, Inc. (ADI) announced a collaboration with Jungo to develop a Time-of-Flight (ToF) and2D infrared- (IR) based camera solution to enable driver- and in-cabin monitoring in vehicles. The combination of ADI’sToF technology with Jungo’s Codriver software is expected to enable the monitoring of vehicle occupants for levels ofdrowsiness and distraction by observing head and body position as well as eye gaze.
Valeo has also rolled out its cockpit monitoring technologies, such as vision-based rear seat monitoring solution andradar-based living beings detection solution.
EyeSight Cabin Sense in-car Occupancy Monitoring System (OMS) detects occupants, their posture or whether theywear seatbelts or not, as well as whether any child or object like a bag is forgotten in car or not.
In a nutshell, DMS will be thriving with wide use of L2/L3 automated driving in the upcoming several years. In future, it willevolve into cockpit monitoring system which will play a crucial role even in the era of L4 autonomy.
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Table of contents
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1 Automotive DMS Technology
1.1 Infrared Technology1.1.1 Introduction to Infrared1.1.2 Infrared Use in Automobile1.2 DMS Technology1.2.1 Introduction to DMS1.2.2 Passive DMS1.2.3 Active DMS1.2.4 Operating Principle and Installation Position of Active DMS1.2.5 Active DMS Based on Cameras and NIR1.2.6 Hardware Architecture and Technical Requirements of DMS1.2.7 Software & Algorithm Architecture and Technical
Requirements of ArchDMS1.3 Advances in Related Chip Technology1.3.1 Technical Progress 11.3.2 Technical Progress 21.3.3 Technical Progress 31.3.4 Technical Progress 41.3.5 Technical Progress 5
2 Automotive DMS Industry Chain and Market Analysis
2.1 Active DMS Industry Chain2.2 Players in the Industrial Chain
2.3 Comparison of Some Active DMS Suppliers’ Products2.4 DMS Market Sales2.5 Market Features
3 Development Trends of Automotive DMS
3.1 DMS Technology Trends3.1.1 Technology Trend 13.1.2 Technology Trend 23.1.3 Technology Trend 33.1.4 Technology Trend 43.1.5 Technology Trend 53.1.6 Technology Trend 63.1.7 Technology Trend 73.2 DMS Market Trends3.2.1 Market Trend 13.2.2 Market Trend 23.3 Tendencies of DMS Software and Algorithms3.3.1 Software and Algorithm Trend 13.3.2 Software and Algorithm Trend 23.3.3 Software and Algorithm Trend 3
4 DMS Application of OEMs4.1 DMS Technology Solutions of Major OEMs 4.2 Cadillac CT6
Table of contents
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4.3 SUBARU FORESTER4.4 BMW X54.5 DS74.6 Leapmotor S014.7 EXEED TXL4.8 Geely Xingyue4.9 XPeng G34.10 WEY VV74.11 GAC NE Aion LX4.12 NIO ES8
5 Tier1 Suppliers of Automotive DMS5.1 Valeo5.1.1 Profile5.1.2 Valeo DMS and In-car Monitoring System5.1.3 Main Features of Valeo DMS5.1.4 Applied Scenarios of Valeo DMS5.2 DENSO5.2.1 Profile5.2.2 DENSO Driver Monitoring Cameras5.2.3 DENSO Commercial Vehicle DMS5.3 Hyundai Mobis5.3.1 Profile5.3.2 Hyundai Mobis DMS5.3.3 Occupant Detection System
5.4 Visteon5.4.1 Profile5.4.2 Visteon DMS5.5 Bosch5.6 Veoneer5.6.1 Profile5.6.2 Veoneer DMS 5.7 OSRAM5.8 Mitsubishi Electric5.9 Aptiv5.9.1 Profile5.9.2 Aptiv DMS5.10 Continental5.11 Harman5.12 Autocruis5.12.1 Profile5.12.2 Autocruis ADAS Products 5.12.3 Autocruis Product & Technology Roadmap5.12.4 Autocruis DMS5.12.5 Features of Autocruis DMS5.12.6 Functional Safety Design Architecture of Autocruis DMS5.12.7 Autocruis Eye Gaze Estimation Model5.13 Roadefend5.13.1 Profile5.13.2 Roadefend’s Technologies
Table of contents
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5.13.3 Roadefend’s Recognition of Driver State5.13.4 Driver Behavior Acquisition, Analysis and Warning System5.13.5 Big Data Analysis of Driver Behaviors5.13.6 Roadefend’s Successful Cases5.14 SinoChipAi5.14.1 Profile5.14.2 SinoChipAi Vision Products5.14.2 SinoChipAi Vision Product: DSM5.14.2 SinoChipAi Vision Product: 3D Face Recognition5.15 MINIEYE5.15.1 Profile5.15.2 MINIEYE DMS5.16 Zhejiang Dahua Technology5.16.1 Profile5.16.2 Products5.17 Hikvision5.18 Baidu5.18.1 Profile5.18.2 Baidu Driver Fatigue Monitoring System5.18.3 Baidu DMS Software
6 Automotive DMS Suppliers6.1 Seeing Machines6.1.1 Seeing Machines -- Profile6.1.2 Seeing Machines -- Revenue
6.1.2 Seeing Machines -- Revenue6.1.3 Seeing Machines -- Products6.1.4 Seeing Machines -- DMS Operating Principle6.1.5 Seeing Machines -- DMS Business Overview6.1.6 Seeing Machines -- DMS Roadmap6.1.7 Seeing Machines -- Evolution of Core Technologies6.2 Affectiva6.2.1 Profile6.2.2 Application of Affectiva Technology6.2.3 Emotional AI Use in Automobile6.2.4 Driver and Occupant Monitoring6.2.5 Tracking of Driver Emotions and Cognitive State6.2.6 Emotional AI and Mood Measurement6.2.7 Emotion Database6.2.8 Affectiva Driver Emotion Tracking Studies6.2.9 Driver Dejection Detection6.2.10 Driver Fatigue Monitoring with Facial Expression and
Voice6.3 EyeSight6.3.1 Profile6.3.2 EyeSight Automotive Solution: Drive Sense6.3.3 EyeSight Automotive Solution: Cabin Sense6.3.4 EyeSight Automotive Solution: Fleet Sense6.3.5 EyeSight’s Technologies6.3.6 EyeSight’s Automotive Products
Table of contents
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6.3.7 EyeSight’s Clients and Partners6.4 Smart Eye6.4.1 Profile6.4.2 General Hardware Development Platform of Smart Eye6.4.3 Smart Eye DMS -- Detection of Facial Expression6.4.4 Smart Eye DMS -- Detection of Human Pose and Gesture Recognition6.4.5 Smart Eye DMS -- Object Classification6.4.6 Smart Eye DMS -- Feature Detection6.4.7 Smart Eye’s R&D of Next-generation Eye-tracking Technology6.5 FotoNation6.5.1 Profile6.5.2 FotoNation DMS6.5.3 FotoNation DMS Core Technology6.6 Untouch Technologies6.6.1 Profile6.6.2 Untouch Tech’ Product: U-Drive Smart Cockpit Monitoring6.6.3 Untouch Tech at 2020 CES: Exhibition of U-SAFE Smart Safe Cockpit6.6.4 Untouch Tech at 2020 CES: Exhibition of U-COMFORT Smart Cozy
Cockpit6.7 SenseTime6.7.1 Profile6.7.2 SenseTime DMS6.8 ArcSoft6.9 Eyeris
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