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ADAS Sensors Global Market 2025-2035

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  • Published: September  2024
  • Pages: 375
  • Tables: 164
  • Figures: 48

 

The ADAS sensors market is experiencing rapid growth driven by increasing demand for vehicle safety features, stringent regulations, and the push towards autonomous driving. Advanced Driver Assistance Systems (ADAS) use a combination of sensors, cameras, and other technologies to gather information about the vehicle's surroundings and provide assistance to the driver. ADAS features can range from basic functionalities like cruise control to more advanced capabilities such as lane keeping assist, automatic emergency braking, and adaptive cruise control. This comprehensive market report provides an in-depth analysis of the Advanced Driver Assistance Systems (ADAS) sensors market, projecting trends and growth from 2025 to 2035. As vehicles become increasingly autonomous and safety regulations tighten globally, ADAS sensors are playing a crucial role in shaping the future of automotive technology.

Report contents include: 

  • Detailed market size projections for ADAS sensors, broken down by sensor type, units, and regional markets from 2024 to 2035.
  • In-depth examination of key ADAS sensor technologies including cameras, radar, LiDAR, ultrasonic sensors, and infrared sensors, as well as emerging technologies like event-based vision and quantum dot optical sensors.
  • Competitive Landscape: Analysis of global Tier-1 suppliers, market share data for various sensor types, and profiles of over 95 key players in the ADAS ecosystem. Companies profiled include 7invensu, Acconeer AB, Actronika, Aeva, AEye, AMS Osram, Aptiv, Arbe, Aryballe, AutoX Technologies Inc., Baidu, Baraja, Beijing Surestar Technology, Benewake, Bosch, Cepton Inc., Continental AG, Cruise, DeepWay, Denso Corporation, Echodyne Inc., EM Infinity, Emberion Oy, Emotion3D, Epicnpoc, Eyeris, Greenerwave, Hesai Technology, Huawei, Hyundai Mobis, Inceptio Technology, Innoviz Technologies, Kognic, Koito Manufacturing, LeddarTech, Leishen Intelligent System Co. Ltd., Li Auto, Lidwave, Livox, Lumentum Operations LLC, Luminar Technologies, Lumotive, Lunewave, Magna International, Melexis, Metahelios, Metawave Corporation, Mitsubishi Electric, Mobileye, Nodar, NXP, Ommatidia LiDAR, OmniVision, Onsemi, OQmented, Ouster, Owl Autonomous Imaging, OPmobility, plus.ai, Pontosense, Pony.ai, PreAct, Prophesee, Qualcomm, Quanergy, Recogni, Renesas Electronics Corporation, RoboSense, Seeing Machines, Sensrad, Seyond, SenseTime, SiLC Technologies, Smart Radar System Inc., Spartan Radar, Steerlight, Tactile Mobility, Tanway, Terabee, Texas Instruments, Tobii, Uhnder, Ultraleap, Valeo, Vayyar, Velodyne Lidar, Veoneer, Visteon, Voyant Photonics, Vueron, Waymo, Wayve, XenomatiX, XPeng Motors, Zadar Labs, Zendar, ZF Friedrichshafen AG, Zvision.
  • Overview of global ADAS-related regulations and their influence on market growth and technology adoption.
  •  Insights into potential disruptive technologies, the impact of autonomous vehicle development on the ADAS market, and long-term growth projections.
  • Market segmentation analysis by sensor type, including:
    • Cameras: Front-facing, surround-view, driver monitoring, and infrared cameras
    • Radar: Short-range, long-range, and imaging radar systems
    • LiDAR: Mechanical, solid-state, and MEMS-based LiDAR technologies
    • Ultrasonic Sensors: For parking assistance and short-range object detection
    • Infrared Sensors: For enhanced night vision and pedestrian detection
  • Market restraints such as high costs of advanced ADAS systems, technical challenges in sensor reliability, and cybersecurity concerns.
  • Technology Trends and Innovations including:
    • Cameras: Developments in high-resolution sensors, wide dynamic range capabilities, and AI-enhanced image processing.
    • Radar: Evolution of 4D imaging radar, high-resolution radar, and software-defined radar systems
    • LiDAR: Innovations in solid-state LiDAR, MEMS-based LiDAR, and FMCW LiDAR, along with cost reduction strategies
    • Sensor Fusion: Advancements in multi-sensor data fusion algorithms, edge computing, and AI-driven sensor fusion techniques
    • ADAS Controllers: Trends in high-performance computing platforms, domain controllers, and zonal architecture
  • Competitive Landscape analysis including: 
    • Global Tier-1 market share analysis
    • Market share data for specific sensor types (e.g., front cameras, LiDAR, radar)
    • Analysis of major Tier-1 suppliers and their strategies
    • Global regulatory environment for ADAS technologies.

 

Key Questions Addressed:

  1. What is the projected market size for ADAS sensors by 2035?
  2. Which sensor technologies are expected to see the highest growth rates?
  3. How will regulatory requirements drive ADAS sensor adoption in different regions?
  4. What are the key challenges facing ADAS sensor manufacturers?
  5. How will the shift towards autonomous vehicles impact the ADAS sensors market?
  6. Which companies are leading in different sensor categories, and what are their market shares?
  7. What emerging technologies could disrupt the current ADAS sensor landscape?

 

Who should be interested in this report?

  • Automotive OEMs and Tier-1 suppliers
  • ADAS sensor manufacturers
  • Semiconductor companies
  • Autonomous vehicle technology developers
  • Investment firms and financial analysts
  • Regulatory bodies and policymakers
  • Automotive industry consultants and researchers

 

 

1             EXECUTIVE SUMMARY            21

  • 1.1        Autonomous driving technologies   21
    • 1.1.1    Automation Levels      22
    • 1.1.2    Functions of autonomous driving    23
    • 1.1.3    Sensors in autonomous vehicles      23
    • 1.1.4    Roadmap         24
  • 1.2        Sensors for ADAS and Autonomous Technologies 25
    • 1.2.1    Sensor Requirements              26
    • 1.2.2    Sensor Suite Costs    26
    • 1.2.3    Front radar sensors   28
    • 1.2.4    Side Radars    29
    • 1.2.5    Vehicle Cameras         30
    • 1.2.6    LiDARs in Automotive               31
  • 1.3        Successful ADAS Implementation in Mass-Market Vehicles          33
  • 1.4        Challenges Faced by OEMs in ADAS Integration     35
  • 1.5        Innovative ADAS Solutions in Premium Vehicles    36
  • 1.6        ADAS Performance in Real-World Conditions          36
  • 1.7        Market Drivers               37
    • 1.7.1    Safety Regulations and NCAP Requirements           38
    • 1.7.2    Consumer Demand for Advanced Safety Features               39
    • 1.7.3    Progress Towards Vehicle Autonomy             39
    • 1.7.4    Cost Reductions in Sensor Technologies    40
  • 1.8        Market Restraints       41
    • 1.8.1    High Costs of Advanced ADAS Systems       42
    • 1.8.2    Technical Challenges in Sensor Reliability 43
    • 1.8.3    Consumer Trust and Acceptance Issues     44
    • 1.8.4    Cybersecurity Concerns         45
  • 1.9        Market Opportunities               47
    • 1.9.1    Integration of ADAS with V2X Technologies                48
    • 1.9.2    Aftermarket ADAS Solutions                49
    • 1.9.3    ADAS in Commercial Vehicles and Fleets   50
    • 1.9.4    Emerging Markets for ADAS Technologies   50
  • 1.10     Market Challenges     51
  • 1.11     Competitive landscape          52
    • 1.11.1 Competitive Positioning of Key Players         52
    • 1.11.2 Investment Trends in ADAS Technologies    53

 

2             INTRODUCTION          55

  • 2.1        Autonomous driving  55
    • 2.1.1    Overview           55
    • 2.1.2    Autonomous driving development in the industry 56
      • 2.1.2.1 Evolutionary Approach            57
      • 2.1.2.2 Revolutionary Approach         57
    • 2.1.3    Position navigation technology          58
    • 2.1.4    Electric Vehicles and Autonomy       59
    • 2.1.5    Passive and Active Sensors  60
    • 2.1.6    Sensor fusion 62
      • 2.1.6.1 Evolution of Sensor Suite       64
      • 2.1.6.2 Vison-only and Multi-sensor Fusion Approaches  66
      • 2.1.6.3 Trends 67
      • 2.1.6.4 Hybrid AI           67
      • 2.1.6.5 Pure vision vs lidar sensor fusion     69
    • 2.1.7    Optical 3D sensing    70
    • 2.1.8    Multi-camera 71
      • 2.1.8.1 Overview           72
      • 2.1.8.2 Structured light            73
      • 2.1.8.3 3D depth-aware imaging technologies         73
      • 2.1.8.4 Resolution       75
    • 2.1.9    Radar and lidar             76
    • 2.1.10 Emerging Sensor Technologies          77
      • 2.1.10.1            Event-based Cameras             77
      • 2.1.10.2            Quantum Sensors      77
      • 2.1.10.3            Metamaterial-based Sensors              78
      • 2.1.10.4            Sensor-on-Chip Solutions    79
  • 2.2        Importance of ADAS in Modern Vehicles     79
  • 2.3        Key Players in the ADAS Supply Chain          80

 

3             MARKET OVERVIEW  83

  • 3.1        Global ADAS Market Size and Growth           83
    • 3.1.1    By type                83
    • 3.1.2    By region           84
      • 3.1.2.1 Regional ADAS Adoption Trends        85
  • 3.2        Regulatory Landscape Driving ADAS Adoption        86
  • 3.3        Impact of Autonomous Vehicle Development on ADAS Market    87

 

4             ADAS SENSOR TECHNOLOGIES       88

  • 4.1        Overview of Key ADAS Sensor Types               88
    • 4.1.1    Sensors in Autonomous Vehicles     88
      • 4.1.1.1 Number of sensors    88
      • 4.1.1.2 Cost     88
      • 4.1.1.3 V2X, 5G, advanced digital mapping, and GPS in autonomous driving      89
        • 4.1.1.3.1           V2X Communication 89
        • 4.1.1.3.2           5G Networks   89
        • 4.1.1.3.3           Advanced Digital Mapping    89
        • 4.1.1.3.4           GPS in Autonomous Driving 89
    • 4.1.2    Cameras           90
      • 4.1.2.1 External Cameras       90
      • 4.1.2.2 E-mirrors           91
      • 4.1.2.3 Internal Cameras        92
      • 4.1.2.4 Front camera 93
      • 4.1.2.5 RGB/Visible light camera       94
      • 4.1.2.6 CMOS image sensors               95
        • 4.1.2.6.1           Front vs backside illumination           96
        • 4.1.2.6.2           Image capture               97
          • 4.1.2.6.2.1      Rolling Shutter               97
          • 4.1.2.6.2.2      Global Shutter               97
        • 4.1.2.6.3           Companies     98
      • 4.1.2.7 IR Cameras     100
      • 4.1.2.8 Driver Monitoring Systems (DMS) and Occupant Monitoring Systems (OMS)     102
        • 4.1.2.8.1           Overview           102
        • 4.1.2.8.2           2D Cameras   106
        • 4.1.2.8.3           3D Cameras   106
          • 4.1.2.8.3.1      ToF Cameras  108
          • 4.1.2.8.3.2      Occupant Monitoring System (OMS) cameras         112
          • 4.1.2.8.3.3      Flash LiDAR    113
        • 4.1.2.8.4           NIR/IR Imaging             114
          • 4.1.2.8.4.1      IR cameras/sensors  115
          • 4.1.2.8.4.2      Infrared (IR) in DMS    115
          • 4.1.2.8.4.3      Thermal Cameras in Autonomous Vehicles               116
          • 4.1.2.8.4.4      Short-Wave Infra-Red (SWIR) Imaging           118
          • 4.1.2.8.4.5      VCSEL 119
          • 4.1.2.8.4.6      Market for IR Cameras             122
          • 4.1.2.8.4.7      Costs  122
        • 4.1.2.8.5           Eye Movement Tracking          123
          • 4.1.2.8.5.1      Overview           123
          • 4.1.2.8.5.2      Event-Based Vision for Eye-Tracking              124
        • 4.1.2.8.6           Brain Function Monitoring     126
          • 4.1.2.8.6.1      Overview           126
          • 4.1.2.8.6.2      Magnetoencephalography    127
      • 4.1.2.8.7           Cardiovascular Metrics           129
      • 4.1.2.9 E-mirrors           129
      • 4.1.2.10            Companies     130
    • 4.1.3    Radar  131
      • 4.1.3.1 Radar in Autonomous Vehicles          133
        • 4.1.3.1.1           Localization    133
        • 4.1.3.1.2           Radar mapping             133
        • 4.1.3.1.3           Waveforms      134
        • 4.1.3.1.4           Frequencies    135
      • 4.1.3.2 Front Radar     138
      • 4.1.3.3 Side Radars    138
      • 4.1.3.4 Components  139
      • 4.1.3.5 Radar trends   140
        • 4.1.3.5.1           Imaging             140
        • 4.1.3.5.2           Resolution       140
        • 4.1.3.5.3           Automotive radar boards       142
        • 4.1.3.5.4           Volume and Footprint               142
        • 4.1.3.5.5           Packaging and Performance 142
        • 4.1.3.5.6           Increasing Range        143
        • 4.1.3.5.7           Field of View   144
        • 4.1.3.5.8           Virtual Channel Count             144
          • 4.1.3.5.8.1      Digital Beamforming (DBF)   145
          • 4.1.3.5.8.2      Sparse Array Designs               145
      • 4.1.3.6 In-Cabin Radars          146
      • 4.1.3.7 4D Radars and Imaging Radars         147
        • 4.1.3.7.1           Overview           147
        • 4.1.3.7.2           Commerical examples            147
        • 4.1.3.7.3           Drivers for 4D and imaging radars    149
        • 4.1.3.7.4           Approaches to Achieve 4D Imaging Radar Capabilities     150
      • 4.1.3.8 Transceivers   152
        • 4.1.3.8.1           Commercial examples            152
        • 4.1.3.8.2           Transceiver technology evolution     154
          • 4.1.3.8.2.1      CMOS 155
          • 4.1.3.8.2.2      SiGe BiCMOS 155
          • 4.1.3.8.2.3      FD-SOI                156
      • 4.1.3.9 Radomes          157
        • 4.1.3.9.1           Overview           157
        • 4.1.3.9.2           Materials           158
          • 4.1.3.9.2.1      Dielectric Constant   159
          • 4.1.3.9.2.2      Loss Tangent  159
        • 4.1.3.9.3           Commercial examples            161
      • 4.1.3.10            Antennas          162
        • 4.1.3.10.1        Designs             163
        • 4.1.3.10.2        Phased Array Antennas           164
        • 4.1.3.10.3        Metamaterials               164
        • 4.1.3.10.4        3D Printed Antennas 165
      • 4.1.3.11            Semiconductors          167
      • 4.1.3.12            Companies     168
      • 4.1.3.13            Markets for Radar       170
      • 4.1.3.14            Radar versus LiDAR   172
    • 4.1.4    LiDAR  173
      • 4.1.4.1 Automotive LiDAR       173
        • 4.1.4.1.1           Operating process      174
        • 4.1.4.1.2           Requirements                174
      • 4.1.4.2 LiDAR systems              175
        • 4.1.4.2.1           Commercialization    175
        • 4.1.4.2.2           Automotive LiDAR Supply Chain       176
        • 4.1.4.2.3           Pricing and costs         177
      • 4.1.4.3 Lidar integration in ADAS/AV 179
        • 4.1.4.3.1           Lamps 179
        • 4.1.4.3.2           Grille    179
        • 4.1.4.3.3           On/In the Roof              180
        • 4.1.4.3.4           Other Positions            180
      • 4.1.4.4 LiDAR Certification     181
      • 4.1.4.5 2D vs 3D lidar 183
      • 4.1.4.6 Ranging and photodetection               184
        • 4.1.4.6.1           Direct TOF        186
        • 4.1.4.6.2           Indirect TOF    187
      • 4.1.4.7 Frequency Modulated Continuous Wave (FMCW) and Pseudo-Random Noise Modulated Continuous Wave (PMCW)   187
      • 4.1.4.8 Beam steering               189
        • 4.1.4.8.1           Mechanical Lidar        190
        • 4.1.4.8.2           MEMS Lidar     190
          • 4.1.4.8.2.1      Commercial MEMS-based LiDAR systems 192
        • 4.1.4.8.3           Flash lidar        192
        • 4.1.4.8.4           Optical phased array (OPA) Lidar     193
          • 4.1.4.8.4.1      Overview           193
          • 4.1.4.8.4.2      Approaches    194
        • 4.1.4.8.5           Other technologies    195
          • 4.1.4.8.5.1      Spectral deflection     195
          • 4.1.4.8.5.2      Micro-motion technology      195
          • 4.1.4.8.5.3      Liquid crystal lidar      196
          • 4.1.4.8.5.4      Metamaterials               197
          • 4.1.4.8.5.5      GLV-based beam steering     200
          • 4.1.4.8.5.6      Liquid lens       201
          • 4.1.4.8.5.7      Electro-Optical Deflectors    201
          • 4.1.4.8.5.8      Acousto-optical deflectors   202
      • 4.1.4.9 Lasers 203
        • 4.1.4.9.1           IR emitters       205
        • 4.1.4.9.2           Edge-emitting lasers (EEL)    206
        • 4.1.4.9.3           Vertical-cavity surface-emitting lasers (VCSEL)     206
        • 4.1.4.9.4           External cavity & quantum cascade lasers (QCL)  207
        • 4.1.4.9.5           Fiber lasers     209
          • 4.1.4.9.5.1      Laser Source Wavelengths   210
          • 4.1.4.9.5.2      Fiber Amplifiers            211
        • 4.1.4.9.6           Diode-pumped solid-state lasers (DPSSL) 212
      • 4.1.4.10            Receivers          212
      • 4.1.4.11            Signal and data analysis/processing             215
        • 4.1.4.11.1        Point cloud      215
          • 4.1.4.11.1.1   3D Point Cloud Modeling       216
          • 4.1.4.11.1.2   Reflection Complication        216
          • 4.1.4.11.1.3   Background Noise & Interference     217
          • 4.1.4.11.1.4   TOF LiDAR's Spatial Data Analysis  217
          • 4.1.4.11.1.5   FMCW LiDAR data processing            218
      • 4.1.4.12            Lidar cleaning                220
        • 4.1.4.12.1        Overview           220
        • 4.1.4.12.2        Types   220
      • 4.1.4.13            LiDAR challenges        221
      • 4.1.4.14            Companies     222
  • 4.2        ADAS Controllers and ECUs 222
    • 4.2.1    Role of ADAS Controllers and ECUs in Autonomous Driving          222
    • 4.2.2    ADAS Controllers: Functions and Technologies      223
    • 4.2.2.1 Core Functions of ADAS Controllers               223
    • 4.2.2.2 Key Technologies in ADAS Controllers           224
  • 4.3        Key Technologies in ADAS Controllers           224
    • 4.3.1.1 ADAS Controller Architectures           224
    • 4.3.1.2 Types of ECUs in Autonomous Vehicles       225
      • 4.3.1.2.1           ECU Integration and Communication           225
    • 4.3.2    Thermal Management             226
      • 4.3.2.1 Thermal Management Strategies      226
      • 4.3.2.2 Emerging Technologies in Thermal Management   227
      • 4.3.2.3 Thermal Interface Materials in ECUs              227
      • 4.3.2.4 Commercial solutions             228
    • 4.3.3    Challenges in ADAS Controllers and ECUs for Autonomous Driving         234
    • 4.3.4    Future Trends and Developments    234
      • 4.3.4.1 Advanced AI and Machine Learning                234
      • 4.3.4.2 Edge Computing and Distributed Intelligence          235
      • 4.3.4.3 Software-Defined Vehicles   235
      • 4.3.4.4 Integration of V2X Communication 236
      • 4.3.4.5 Future Trends 236
  • 4.4        Emerging Sensor Technologies          236
    • 4.4.1    Event-based Vision    237
      • 4.4.1.1 Data     237
      • 4.4.1.2 Event-based Sensing                238
    • 4.4.2    Quantum Dot Optical Sensors           239
      • 4.4.2.1 Properties         239
      • 4.4.2.2 Infrared (IR) and near-infrared (NIR) sensing             240
      • 4.4.2.3 Commercial examples            240
    • 4.4.3    Hyperspectral Imaging            243

 

5             KEY MARKET PLAYERS AND MARKET SHARE            244

  • 5.1        Global Tier-1 Market Share Analysis               244
  • 5.2        Overall ADAS Sensor Market Share 244
  • 5.3        Regional Market Share Variations    246
  • 5.4        Front Camera Market Share 246
  • 5.4.1    Leading Suppliers and Their Market Positions         246
  • 5.4.2    Technology Differentiators Among Top Players        247
  • 5.4.3    OEM Partnerships and Supply Agreements               247
  • 5.5        Driver Monitoring Systems (DMS) / Occupant Monitoring Systems (OMS) Market Share             248
    • 5.5.1    Key Players in the DMS/OMS Space                248
  • 5.6        Technological Advancements Driving Market Growth         249
  • 5.7        Regulatory Impacts on DMS/OMS Adoption             249
  • 5.8        LiDAR Market Share   249
    • 5.8.1    Current Market Leaders in Automotive LiDAR          249
    • 5.8.2    Emerging Players and Disruptive Technologies       250
    • 5.8.3    LiDAR Adoption Trends Among OEMs           250
  • 5.9        Radar Market Share   251
    • 5.9.1    Market  Players in Automotive Radar              252
      • 5.9.1.1 All Radar           252
      • 5.9.1.2 Front Radar     253
      • 5.9.1.3 Side Radar       254
      • 5.9.1.4 Regional trends            255
      • 5.9.1.5 Commercial radar models    257
      • 5.9.1.6 Future Trends 258
      • 5.9.1.7 Challenges      259
    • 5.9.2    Imaging Radar vs. Traditional Radar Market Dynamics      265
      • 5.9.2.1 Trends 266
      • 5.9.2.2 Packaging and Integration Trends     268
    • 5.9.3    Frequency Trends (24GHz, 77GHz, 79GHz)               268
  • 5.10     Other ADAS Sensors 269
    • 5.10.1 Ultrasonic Sensors     269
    • 5.10.2 Infrared Sensors          269
    • 5.10.3 GNSS and IMU Suppliers       270
  • 5.11     ADAS Controllers and ECUs Market Share 270
    • 5.11.1 Leading Suppliers of ADAS Computing Platforms 271
    • 5.11.2 Trends in Centralized vs. Distributed ADAS Architectures                271
  • 5.12     Analysis of Major Tier-1 Suppliers     271

 

6             TECHNOLOGY TRENDS AND INNOVATIONS            273

  • 6.1        Advancements in Camera Technology          273
    • 6.1.1    High-Resolution Sensors       273
    • 6.1.2    Wide Dynamic Range (WDR) Capabilities  273
    • 6.1.3    Low-Light Performance Improvements        274
    • 6.1.4    AI-Enhanced Image Processing         274
  • 6.2        Radar Technology Evolution 274
    • 6.2.1    4D Imaging Radar       275
    • 6.2.2    High-Resolution Radar            275
    • 6.2.3    Software-Defined Radar        276
  • 6.3        LiDAR Innovations      276
    • 6.3.1    Solid-State LiDAR       276
    • 6.3.2    MEMS-based LiDAR   277
    • 6.3.3    FMCW LiDAR 278
    • 6.3.4    Cost Reduction Strategies     279
  • 6.4        Sensor Fusion Advancements            279
    • 6.4.1    Multi-Sensor Data Fusion Algorithms            280
    • 6.4.2    Edge Computing for Sensor Fusion 280
    • 6.4.3    AI and Machine Learning in Sensor Fusion 281
  • 6.5        ADAS Controller Innovations               281
    • 6.5.1    High-Performance Computing Platforms    281
    • 6.5.2    Domain Controllers   282
    • 6.5.3    Zonal Architecture Trends     282

 

7             FUTURE OUTLOOK AND MARKET FORECASTS        284

  • 7.1        Market Forecast (2024-2035)             284
  • 7.1.1    Market Size Projections           285
      • 7.1.1.1 By Sensor Type              285
      • 7.1.1.2 Robotaxis         286
      • 7.1.1.3 By Units             287
        • 7.1.1.3.1           Cameras           287
        • 7.1.1.3.2           Radar  288
        • 7.1.1.3.3           LiDAR  290
    • 7.1.2    Regional Growth Forecasts  291
    • 7.1.3    Expected Technology Adoption Rates           292
  • 7.2        Impact of Autonomous Vehicle Development on ADAS Market    293
  • 7.3        Potential Disruptive Technologies and Their Impact            293

 

8             REGULATORY LANDSCAPE   295

  • 8.1        Global ADAS-Related Regulations   295
    • 8.1.1    Legislation for autonomous vehicles             296
      • 8.1.1.1 Europe                296
      • 8.1.1.2 US         296
      • 8.1.1.3 China  297
      • 8.1.1.4 Japan  297
    • 8.1.2    Driver Monitoring Systems (DMS)     298
  • 8.2        Future Regulatory Trends and Their Impact on the Market               300

 

9             COMPANY PROFILES                302 (98 company profiles)

 

10          APPENDICES  371

  • 10.1     Research Methodology           371
  • 10.2     List of Abbreviations  371

 

11          REFERENCES 373

 

List of Tables

  • Table 1. Automation Levels. 22
  • Table 2. Functions of Autonomous Driving at Different Levels.     23
  • Table 3. "Big Three" sensors used in Advanced Driver Assistance Systems (ADAS).       25
  • Table 4. Sensor Requirements for Different Levels of Autonomy. 26
  • Table 5. Sensor Suite for Autonomous Cars-Costs.             26
  • Table 6. Estimated Sensor Suite Costs for Different Levels of Autonomy.             27
  • Table 7. Front Radar Applications in ADAS.                28
  • Table 8. Vehicle Camera Applications in ADAS.      30
  • Table 9. LiDAR Types and Characteristics. 31
  • Table 10. LiDAR Applications in Automotive Systems.       32
  • Table 11. Examples of advanced safety features in mainstream models.             34
  • Table 12. Challenges Faced by OEMs in ADAS Integration.             35
  • Table 13. Innovative ADAS Solutions in Premium Vehicles.             36
  • Table 14. ADAS Performance in Real-World Conditions.  36
  • Table 15. Market drivers for ADAS sensors. 37
  • Table 16. Safety Regulations and NCAP Requirements.    38
  • Table 17. Cost reductions in key sensor technologies.       41
  • Table 18. Market Restraints for ADAS sensors.        41
  • Table 19. Costs of Advanced ADAS Systems.           43
  • Table 20. Technical Challenges in Sensor Reliability.          43
  • Table 21. Market opportunities in ADAS sensors.  47
  • Table 22. ADAS in Commercial Vehicles and Fleets.            50
  • Table 23. Emerging Markets for ADAS Technologies.            51
  • Table 24. Market challenges in ADAS sensors.        51
  • Table 25. Emerging Players and Startups in the ADAS Ecosystem.             53
  • Table 26. Key autonomous driving technologies.   55
  • Table 27. Position navigation technologies.               58
  • Table 28. Autonomous driving sensor comparison.             62
  • Table 29. Recommended Sensor Suites For SAE Level 2 to Level 4 & Robotaxi. 65
  • Table 30. Sensor Fusion Technology Trends for Applications.       67
  • Table 31. Pure vision vs lidar sensor fusion.              69
  • Table 32. Pure vision solution challenges.  70
  • Table 33. Optical 3D sensing methods.        71
  • Table 34. Automotive camera hardware.     72
  • Table 35. 3D depth-aware imaging technologies.  73
  • Table 36. General resolution requirements for different sensors and applications.        75
  • Table 37. ADAS/AV sensor operating wavelength.  76
  • Table 38. Radar hardware.    76
  • Table 39. ADAS/AV hardware challenges.    80
  • Table 40. Key Players in the ADAS Supply Chain.   82
  • Table 41. Global market for ADAS sensors 2022-2035 (by type), billions USD.   83
  • Table 42. Global market for ADAS sensors 2022-2035 (by type), billions USD.   84
  • Table 43. Regional ADAS Adoption Trends  85
  • Table 44. Regulatory Landscape Driving ADAS Adoption. 86
  • Table 45. No. of Sensors Required for Autonomous Cars - Level 0 to Level 4 and Robotaxis/   88
  • Table 46. Estimated Cost Range of Sensors for Autonomous Vehicles (in USD).              88
  • Table 47.Vehicle camera applications in a table:   90
  • Table 48. ADAS Camera Sensors vs Radar Sensors vs Lidar Sensors.      93
  • Table 49. CMOS image sensors vs CCD cameras. 95
  • Table 50. Advantages and disadvantages of IR Cameras. 102
  • Table 51. Applications of DMS.          103
  • Table 52. Sensing Technologies by Features.            103
  • Table 53. Technology Comparison of Radar, ToF and IR Cameras.             104
  • Table 54. Comparison of In-Cabin Sensing Technologies.               105
  • Table 55. 3D Imaging Systems.          106
  • Table 56. 3D imaging systems.          114
  • Table 57. IR VS. VCSEL Light Sources.           116
  • Table 58. Comparative analysis of LEDS and VCSEL.          119
  • Table 59. Applications of IR Imaging.             120
  • Table 60.Companies in VCSEL.          121
  • Table 61. Average IR Camera Per Passenger Car: 2020-2035.       121
  • Table 62. Global Market for IR Cameras for Passenger Cars 2020-2035 (Million Units).              122
  • Table 63. Global Market for IR Cameras, 2020-2035  (US$ Millions).        122
  • Table 64. Cost per IR Camera for DMS, 2020-2035 (US$). 122
  • Table 65. Eye-Tracking Sensor Categories. 123
  • Table 66. Eye-tracking companies. 124
  • Table 67. Event-Based Vision: Pros and Cons.        124
  • Table 68. Market players in cameras and thermal cameras.          130
  • Table 69. Main Methods of Localization.     133
  • Table 70. Front Radar ADAS Applications.  138
  • Table 71. Side Radar ADAS Applications.    138
  • Table 72. Key Radar Components.  139
  • Table 73. Comparison of In-Cabin Radars. 147
  • Table 74. Comparing 4D imaging radar systems.   148
  • Table 75. Vehicles Using 4D Imaging Radars.           149
  • Table 76. Transceiver suppliers.        152
  • Table 77. Typical supply chain for automotive radar transceivers.              153
  • Table 78. Additional participants in the supply chain.        154
  • Table 79. Key Radome Material Suppliers.  162
  • Table 80. Phased array antenna.       164
  • Table 81. Market players in automotive radar.          168
  • Table 82. Global Volume Sales of Radar: 2020-2035 (in millions).             170
  • Table 83. Radar Per Vehicle 2020-2035.      170
  • Table 84. Cost per In-Cabin Radar (in USD) 2020-2035.   171
  • Table 85. Market Size for In-Cabin Radar: 2020-2035 (in billion USD)      171
  • Table 86. Number of Radars Shipped per Vehicle, 2020-2035.    171
  • Table 87. Number of Radars Used in SAE Levels 0, 1 & 2. 171
  • Table 88. Global Radar Unit Sales for Different SAE Levels 2020-2035 (Million Units). 171
  • Table 89.Global Revenues From Radar by SAE Level 2020-2035  (Billion USD). 172
  • Table 90. Radar versus LiDAR.            172
  • Table 91. LiDAR classifications.        173
  • Table 92.Comparison of lidar product parameters.              175
  • Table 93. Automotive lidar players by technology. 176
  • Table 94. Cost Reduction Approaches for LiDAR systems.              177
  • Table 95. BOM cost for LiDAR.            177
  • Table 96. Typical price composition for LiDAR system.      178
  • Table 97. Forecast for LiDAR Unit Price by Technology to 2030.   178
  • Table 98. 2D versus 3D LiDAR.           183
  • Table 99. Time of Flight (TOF) vs. Frequency Modulated Continuous Wave (FMCW).     185
  • Table 100. Direct ToF and Indirect ToF.          185
  • Table 101. Comparison of TOF and FMCW LiDAR technologies. 188
  • Table 102.  LiDAR beam steering technologies.      189
  • Table 103. Classifications of MEMS Scanner.           190
  • Table 104. Comparative analysis of different MEMS actuation methods:              191
  • Table 105. Optical phased array (OPA) Lidar.            194
  • Table 106. Technology options for laser illumination.         203
  • Table 107. Comparing laser choices based on key parameters.  204
  • Table 108. IR emitter technologies. 205
  • Table 109. EEL vs VCSEL Comparison.         208
  • Table 110. Wavelength Comparison: 905 nm vs 1550 nm.              210
  • Table 111. Comparison of Common Laser Type & Wavelength Options.               211
  • Table 112. Photodetector Choice for LiDAR.             213
  • Table 113. LiDAR Detector Comparison.     213
  • Table 114. Comparison of Common Photodetectors.         214
  • Table 115. LiDAR Detector Companies.       214
  • Table 116. LiDAR Signal Applications.           215
  • Table 117. TOF LiDAR's Spatial Data Analysis          217
  • Table 118. LiDAR challenges.              221
  • Table 119. Automotive LiDAR players.           222
  • Table 120. Core Functions of ADAS Controllers.    224
  • Table 121. ADAS Controller Architectures. 224
  • Table 122. Types of ECUs in Autonomous Vehicles.             225
  • Table 123. Thermal Conductivity of TIMs in ECUs/Computers.    232
  • Table 124. Typical operating temperature ranges for different types of TIMs used in ECUs.      233
  • Table 125. Typical density and thermal conductivity ranges for various TIMs used in ECUs.    233
  • Table 126. TIM market for ECUs/ADAS computers 2020-2035 (Millions USD).   234
  • Table 127. Challenges in ADAS Controllers and ECUs for Autonomous Driving.               234
  • Table 128. Event-based sensing: Pros and cons.   238
  • Table 129. Top 10 Tier-1 Suppliers by Revenue 2023.          245
  • Table 130. Leading Suppliers and Their Market Positions 247
  • Table 131. Technology Differentiators Among Top Players.              247
  • Table 132. OEM Partnerships and Supply Agreements.     248
  • Table 133. Key Players in the DMS/OMS Space.      248
  • Table 134. Technological Advancements Driving Market Growth.               249
  • Table 135. Current Market Leaders in Automotive LiDAR. 250
  • Table 136. Emerging Players and Disruptive Technologies.             250
  • Table 137. LiDAR Adoption Trends Among OEMs. 250
  • Table 138.Tier One Market Share by Volume (All Radar).   252
  • Table 139. Tier One Market Share by Revenue (All Radar).               253
  • Table 140. Tier One Market Share by Revenue (Front Radar)          253
  • Table 141.Top OEM Front Radar Choices     253
  • Table 142. Tier One Market Share by Revenue - Side Radar             254
  • Table 143. Top OEM Side Radar Choices.    255
  • Table 144. Emerging Radar Players. 261
  • Table 145. Imaging Radar vs. Traditional Radar Market Dynamics.            265
  • Table 146. Main Players in Ultrasonic Sensors.       269
  • Table 147. Main Players in Infrared Sensors.             269
  • Table 148. Main Players in GNSS Receivers and IMUs.       270
  • Table 149. Leading Suppliers of ADAS Computing Platforms.       271
  • Table 150. Trends in Centralized vs. Distributed ADAS Architectures.      271
  • Table 151. Key LiDAR cost reduction strategies.     279
  • Table 152. Global market size for autonomous vehicles by SAE level from 2022-2035 (Millions).         284
  • Table 153. Global Market Size Projections by Sensor Type, Millions USD, 2024-2035. 285
  • Table 154. Global Market Size Projections by Sensor Type, Million Units, 2024-2035,  286
  • Table 155.Robotaxi Service Revenue 2024-2035 (in million USD)               286
  • Table 156. Market Size Projections: Cameras, Million Units, 2024-2035.              287
  • Table 157. Market Size Projections: Radar, Million Units, 2024-2035.     288
  • Table 158. Radar Unit Sales by SAE Levels 2022-2035 (in millions).         289
  • Table 159. Global Market Size Projections: LiDAR, Million Units, 2024-2035.     290
  • Table 160. Global Market Size Projections by Region, Millions USD, 2024-2035.             291
  • Table 161. Expected Technology Adoption Rates for ADAS.            292
  • Table 162. Global ADAS-Related Regulations.         295
  • Table 163. Regional Variations in ADAS Requirements       299
  • Table 164. Common abbreviations used in the ADAS (Advanced Driver Assistance Systems) sensors market.              371

 

List of Figures

  • Figure 1. Autonomous vehicles.        22
  • Figure 2. Roadmap of Autonomous Driving Functions in Private Cars.    25
  • Figure 3. Evolution of Sensor Suites.              27
  • Figure 4. Automotive 3D sensing.     32
  • Figure 5. Evolution of ADAS availability.       33
  • Figure 6.. Autonomous Driving Integration with V2X.           48
  • Figure 7.Types of ADAS sensors.       61
  • Figure 8. Perception and sensing for autonomous vehicles under adverse weather conditions.           64
  • Figure 9. Global market for ADAS sensors 2022-2035 (by type), billions USD.    84
  • Figure 10. Global market for ADAS sensors 2022-2035 (by type), billions USD. 85
  • Figure 11. Toyota external camera.  91
  • Figure 12. Side E-Mirror.          92
  • Figure 13. Internal ADAS camera.    92
  • Figure 14. RGB Cameras for Autonomous Vehicles              95
  • Figure 15. Front vs backside illumination.  96
  • Figure 16. OmniVision Global Shutter Sensor chip.              100
  • Figure 17. ADAS thermal camera images.  101
  • Figure 18. Driver Monitoring System.             103
  • Figure 19. Driver Monitoring Systems (DMS) with S32V234 Vision Processor.     105
  • Figure 20. Infineon DMS - REAL3™ ToF Imager IRS2877A(S).          109
  • Figure 21. Exploded view of Magna's driver monitoring system built into a rearview mirror.      110
  • Figure 22. LG Innotek ToF Camera for DMS.              111
  • Figure 23. PreAct Mojave Flash LiDAR for OMS.      113
  • Figure 24. ADAS/AV Thermal Camera.           117
  • Figure 25. TriEye.          119
  • Figure 26. LANXESS Concept Radar.              140
  • Figure 27. OPMobility Functionalized Bumper.        151
  • Figure 28. Echodyne metamaterial radar mounted on automobile.          165
  • Figure 29. Lunewave 3D printed radar.         166
  • Figure 30. LiDAR working principle. 175
  • Figure 31. Automotive lidar supply chain.   176
  • Figure 32. Metamaterials in automotive applications.       199
  • Figure 33. Lumotive advanced beam steering concept.    199
  • Figure 34. Illustration of EchoDrive operation.         200
  • Figure 35. Emberion Sensor. 241
  • Figure 36. Global market size for autonomous vehicles by SAE level from 2022-2035 (Millions).          285
  • Figure 37. Market Size Projections: Cameras, Million Units, 2024-2035.               288
  • Figure 38. Market Size Projections: Radar, Million Units, 2024-2035.      289
  • Figure 39. Radar Unit Sales by SAE Levels 2022-2035 (in millions).          290
  • Figure 40. Global Market Size Projections: LiDAR, Million Units, 2024-2035.      291
  • Figure 41. Market Size Projections by Region, Millions USD, 2024-2035.              292
  • Figure 42. Continental ARS540.        312
  • Figure 43. Schematic of MESA System.        315
  • Figure 44. EchoGuard Radar System.            316
  • Figure 45. (Hesai AT512 LiDAR).        321
  • Figure 46.  Koito Manufacturing LiDAR.        326
  • Figure 47. LIDAR system for autonomous vehicles.              331
  • Figure 48. Light-control metasurface beam-steering chips.           332

 

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