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Product Code MM091470946AHN
Published Date 2023/3/21
English288 PagesGlobal

Sensor Market for Automated Vehicles by Component (Hardware, Software), Offering, Software, Level of Autonomy (L2+, L3, L4), Propulsion (ICE, Electric), Vehicle Type, Sensor Platform Approach, Sensor Fusion Process and Region - Global Forecast to 2030 ‐ Automotive_Mobility Market


Report Thumbnail
Product Code MM091470946AHN◆The Mar 2026 edition is also likely available. We will check with the publisher immediately.
Published Date 2023/3/21
English 288 PagesGlobal

Sensor Market for Automated Vehicles by Component (Hardware, Software), Offering, Software, Level of Autonomy (L2+, L3, L4), Propulsion (ICE, Electric), Vehicle Type, Sensor Platform Approach, Sensor Fusion Process and Region - Global Forecast to 2030 ‐ Automotive_Mobility Market



Abstract


Summary

The Sensor Market for automated vehicles is projected to grow from USD 0.4 Billion in 2022 to USD 19.1 Billion by 2030, registering a CAGR of 62.6%. The growing demand of safer, efficient and fuel efficient vehicles have accelerated the growth of sensor market for automated vehicles. With the rapid setup of connected vehicle infrastructure worldwide, demand for automated vehicles such as passenger cars and commercial vehicles is also expected to increase. Technological breakthroughs in ADAS components and other automated driving technologies have made it possible to have safer and more convenient mode of transportation. The sensor market for automated vehicles is dominated by established players such as Robert Bosch GmbH (Germany), Continental AG (Germany), ZF Friedrichshafen AG (Germany), DENSO (Japan), and NXP Semiconductors (Netherlands), among others These players have worked on providing hardware and software components for autonomous vehicle ecosystem. They have initiated partnerships to develop their technology and provide best-in-class products to their customers. “Passenger Cars to be the largest segment in market during the forecast period” The passenger cars segment is estimated to lead the market during the forecast period due to the higher profitability of using L3 and L4 technology in luxury-segment passenger vehicles in the initial years of autonomous vehicle technology development. The demand for autonomy in commercial vehicles is also expected to grow rapidly in the coming years, with an increasing demand for road safety and regulations by countries to prevent accidents from commercial vehicles. Autonomy in the commercial vehicle segment can be seen post-2024, mainly in Europe and North America. Companies such as Stellantis are planning to launch autonomous vans in 2024. Bus manufacturers are already working on autonomous shuttles across Europe. However, trucks are expected to skip L3 and go straight for L4 autonomous driving, as mentioned by leading players such as Daimler and Volvo. Several automakers, such as Nissan, Tesla, BMW, Mercedes-Benz, Hyundai, and Audi, have already started the development of advanced autonomous applications for their passenger cars. For instance, in December 2021, Mercedes-Benz started offering automated driving technology called DRIVE PILOT in its EQS models in the first half of 2022 and on its S Class Model in select countries. The OEM claimed that these cars can commute at a speed of 60 kmph in heavy traffic or congested situations or stretches. Similarly, Hyundai Group announced its plan to launch two passenger car models with L3 autonomy level. Hyundai Motor’s Genesis G90 sedan and Kia’s EV9 will be launched with an L3 autonomy level in 2023. “Mid-level Fusion to lead demand for sensor market for automated vehicles during the forecast period” Mid-level fusion segment is expected to grow at the highest rate during the forecast period. The rise in traffic congestion, the development of roadway infrastructure, and the increasing government regulations for vehicle safety have resulted in the increased installation of sensors and sensing fusion platforms in vehicles by OEMs. In addition, the increasing focus by urban municipal authorities to develop intelligent transportation systems where vehicles are more connected will be a major boost in the development of real-time safety features. Mid-level sensor fusion in autonomous vehicles refers to the integration of multiple sensors and algorithms that aim to provide a comprehensive and accurate understanding of the vehicle's surroundings. This includes data from cameras, LiDAR, radars, GPS, and other sensors, which are then processed and combined to produce a high-fidelity representation of the environment. The mid-level sensor fusion platform acts as an intermediary between the low-level sensor data and high-level decision-making systems in autonomous vehicles. Mid-level sensor fusion systems enable AVs to better detect and track objects, such as other vehicles, pedestrians, and road signs, thereby improving the overall safety of the autonomous system. By fusing data from multiple sensors, mid-level sensor fusion also provides a more complete picture of the environment, allowing AVs to make better decisions and improve situational awareness. They also reduce the potential for errors and improve the reliability of the autonomous system, making them less likely to fail in challenging situations. By processing sensor data in real time, mid-level sensor fusion also reduces the latency between detecting an object and responding to it, allowing AVs to react more quickly to changing road conditions. Companies such as AEye, AutonomouStuff, Continental AG, and DENSO offer mid-level fusion technologies for autonomous vehicle applications. In-depth interviews were conducted with CEOs, marketing directors, other innovation and technology directors, and executives from various key organizations operating in this market. • By Respondent Type: Tier I – 67%, Tier II and Tier III – 9%, and OEMs – 24% • By Designation: CXOs – 33%, Managers – 52%, Executives – 15% • By Region: North America – 26%, Europe – 30%, Asia Pacific – 35%, Rest of the World –9% The sensor market for automated vehicles is dominated by established players such as Robert Bosch GmbH (Germany), Continental AG (Germany), ZF Friedrichshafen AG (Germany), DENSO (Japan), and NXP Semiconductors (Netherlands), among others. They have worked on providing offerings for the sensor market for automated vehicles ecosystem. They have initiated partnerships to develop their automated driving technologies and offer best-in-class products to their customers. Research Coverage: The report covers the sensor market for automated vehicles based on component, offering, software, propulsion, level of autonomy, vehicle type, sensor platform approach, sensor fusion process, and region (North America, Europe, Asia-Pacific and Rest of the World). It covers the competitive landscape and company profiles of the major players in the sensor market for automated vehicles ecosystem. The study also includes an in-depth competitive analysis of the key market players, their company profiles, key observations related to product and business offerings, recent developments, and key market strategies. Key Benefits of Buying the Report: • This report will help market leaders/new entrants in this market with information on the closest approximations of revenue numbers for the overall sensor market for automated vehicles ecosystem and its subsegments. • This report will help stakeholders understand the competitive landscape and gain more insights to better position their businesses and plan suitable go-to-market strategies. • This report will also help stakeholders understand the market’s pulse and provide information on key market drivers, restraints, challenges, and opportunities.

Table of Contents

  • 1 INTRODUCTION 24

    • 1.1 STUDY OBJECTIVES 24
    • 1.2 MARKET DEFINITION 25
      • 1.2.1 INCLUSIONS AND EXCLUSIONS 28
    • 1.3 MARKET SCOPE 29
      • 1.3.1 REGIONS COVERED 29
      • 1.3.2 YEARS CONSIDERED 30
    • 1.4 CURRENCY CONSIDERED 30
    • 1.5 STAKEHOLDERS 31
  • 2 RESEARCH METHODOLOGY 32

    • 2.1 RESEARCH DATA 32
      • 2.1.1 SECONDARY DATA 33
        • 2.1.1.1 Key secondary sources 34
        • 2.1.1.2 Key data from secondary sources 35
      • 2.1.2 PRIMARY DATA 35
        • 2.1.2.1 Primary interviews from demand and supply sides 36
        • 2.1.2.2 Key industry insights and breakdown of primary interviews 36
        • 2.1.2.3 List of primary participants 37
    • 2.2 MARKET SIZE ESTIMATION 38
      • 2.2.1 BOTTOM-UP APPROACH 39
      • 2.2.2 TOP-DOWN APPROACH 40
      • 2.2.3 RECESSION IMPACT ANALYSIS 41
    • 2.3 DATA TRIANGULATION 42
    • 2.4 FACTOR ANALYSIS 44
      • 2.4.1 FACTOR ANALYSIS FOR MARKET SIZING: DEMAND AND SUPPLY SIDES 44
    • 2.5 RESEARCH ASSUMPTIONS 44
    • 2.6 RESEARCH LIMITATIONS 45
  • 3 EXECUTIVE SUMMARY 46

  • 4 PREMIUM INSIGHTS 51

    • 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN SENSORS MARKET FOR AUTONOMOUS VEHICLES 51
    • 4.2 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY COMPONENT 51
    • 4.3 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY OFFERING 52
    • 4.4 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY SOFTWARE 52
    • 4.5 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY LEVEL OF AUTONOMY 53
    • 4.6 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY PROPULSION 53
    • 4.7 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY VEHICLE TYPE 54
    • 4.8 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY SENSOR PLATFORM APPROACH 54
    • 4.9 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY SENSOR FUSION PROCESS 55
    • 4.10 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY REGION 55
  • 5 MARKET OVERVIEW 56

    • 5.1 INTRODUCTION 56
    • 5.2 MARKET DYNAMICS 57
      • 5.2.1 DRIVERS 57
        • 5.2.1.1 Growing penetration of ADAS safety features 57
        • 5.2.1.2 Advancements in automotive sensor technology 59
        • 5.2.1.3 Development of autonomous commercial vehicles 60
        • 5.2.1.4 Government initiatives for road safety 61
      • 5.2.2 RESTRAINTS 63
        • 5.2.2.1 Lack of standardization in software architecture/hardware platforms 63
        • 5.2.2.2 Insufficient infrastructure for vehicle connectivity 64
        • 5.2.2.3 Increase in cybersecurity threats due to advancements in connectivity technology 64
      • 5.2.3 OPPORTUNITIES 65
        • 5.2.3.1 Growing development in autonomous space 65
        • 5.2.3.2 Rising popularity of electric vehicles 65
        • 5.2.3.3 Increasing adoption of 5G and connectivity 66
      • 5.2.4 CHALLENGES 67
        • 5.2.4.1 Security and safety concerns 67
        • 5.2.4.2 Environmental constraints in using LiDAR 68
        • 5.2.4.3 Hard to trade-off between price and overall quality 68
      • 5.2.5 IMPACT OF MARKET DYNAMICS 69
    • 5.3 PORTER’S FIVE FORCES ANALYSIS 69
      • 5.3.1 THREAT OF NEW ENTRANTS 71
      • 5.3.2 THREAT OF SUBSTITUTES 71
      • 5.3.3 BARGAINING POWER OF SUPPLIERS 71
      • 5.3.4 BARGAINING POWER OF BUYERS 71
      • 5.3.5 INTENSITY OF COMPETITIVE RIVALRY 72
    • 5.4 VALUE CHAIN ANALYSIS 72
      • 5.4.1 VALUE CHAIN ANALYSIS: SENSORS MARKET FOR AUTONOMOUS VEHICLES 72
    • 5.5 MACROECONOMIC INDICATORS 73
      • 5.5.1 GDP TRENDS AND FORECAST FOR MAJOR ECONOMIES 73
    • 5.6 PRICING ANALYSIS 74
    • 5.7 SENSORS MARKET FOR AUTONOMOUS VEHICLES ECOSYSTEM 75
      • 5.7.1 SENSORS 75
      • 5.7.2 PROCESSORS 76
      • 5.7.3 SOFTWARE AND SYSTEMS 76
      • 5.7.4 OEMS 76
    • 5.8 KEY STAKEHOLDERS AND BUYING CRITERIA 77
      • 5.8.1 PASSENGER CARS 77
      • 5.8.2 COMMERCIAL VEHICLES 77
      • 5.8.3 KEY STAKEHOLDERS IN BUYING PROCESS 78
      • 5.8.4 BUYING CRITERIA 78
    • 5.9 TECHNOLOGY ANALYSIS 79
      • 5.9.1 SOLID-STATE LIDAR 79
      • 5.9.2 TERRAIN SENSING SYSTEM FOR AUTONOMOUS VEHICLES 79
      • 5.9.3 V2X CONNECTED AUTONOMOUS VEHICLES 80
      • 5.9.4 AUTOMATED VALET PARKING (AVP) 80
      • 5.9.5 NIGHT VISION AND THERMAL IMAGING 80
    • 5.10 PATENT ANALYSIS 81
    • 5.11 CASE STUDY ANALYSIS 85
      • 5.11.1 CASE STUDY 1: DATASPEED AUTONOMOUS VEHICLE SOLUTION 85
      • 5.11.2 CASE STUDY 2: RENESAS BOOSTS DEEP LEARNING DEVELOPMENT FOR ADAS AND AUTOMATED DRIVING APPLICATIONS 85
      • 5.11.3 CASE STUDY 3: DEVELOPING AUTONOMOUS DRIVING FOR GLOBAL OEM 86
      • 5.11.4 CASE STUDY 4: AUTOMATED PARKING FOR STUTTGART AIRPORT 86
      • 5.11.5 CASE STUDY 5: ZF’S NEW AI-BASED SERVICE FOR ADAS DEVELOPMENT 87
      • 5.11.6 CASE STUDY 6: OPEN AUTONOMY PILOT FOR US STATE 87
      • 5.11.7 CASE STUDY 7: TRANSPORTATION FOR THE IMPAIRED 88
    • 5.12 REGULATORY OVERVIEW 88
      • 5.12.1 REGULATIONS ON AUTONOMOUS VEHICLES USAGE BY COUNTRY 89
      • 5.12.2 LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 90
    • 5.13 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 93
    • 5.14 RECESSION IMPACT 93
      • 5.14.1 INTRODUCTION 93
      • 5.14.2 REGIONAL MACROECONOMIC OVERVIEW 94
      • 5.14.3 ANALYSIS OF KEY ECONOMIC INDICATORS 94
      • 5.14.4 ECONOMIC STAGFLATION (SLOWDOWN) VS. ECONOMIC RECESSION 95
        • 5.14.4.1 Europe 95
        • 5.14.4.2 Asia Pacific 96
        • 5.14.4.3 Americas 97
      • 5.14.5 ECONOMIC PROJECTIONS 98
    • 5.15 RECESSION IMPACT ON AUTOMOTIVE SECTOR 99
      • 5.15.1 ANALYSIS OF AUTOMOTIVE VEHICLE SALES 99
        • 5.15.1.1 Europe 99
        • 5.15.1.2 Asia Pacific 99
        • 5.15.1.3 Americas 100
      • 5.15.2 AUTOMOTIVE SALES OUTLOOK 100
    • 5.16 KEY CONFERENCES AND EVENTS, 2022-2023 101
    • 5.17 SENSORS MARKET FOR AUTONOMOUS VEHICLES, SCENARIOS (2022-2030) 102
      • 5.17.1 MOST LIKELY SCENARIO 102
      • 5.17.2 OPTIMISTIC SCENARIO 103
      • 5.17.3 PESSIMISTIC SCENARIO 103
  • 6 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY COMPONENT 104

    • 6.1 INTRODUCTION 105
      • 6.1.1 ASSUMPTIONS 106
      • 6.1.2 RESEARCH METHODOLOGY 106
    • 6.2 HARDWARE 106
      • 6.2.1 GROWING DEMAND FOR ADAS SAFETY SYSTEMS TO DRIVE SEGMENT 106
    • 6.3 SOFTWARE 108
      • 6.3.1 GROWING DEMAND FOR AUTONOMOUS VEHICLE PLATFORMS AND RELATED SOFTWARE TO DRIVE SEGMENT 108
    • 6.4 KEY INDUSTRY INSIGHTS 109
  • 7 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY OFFERING 110

    • 7.1 INTRODUCTION 111
      • 7.1.1 ASSUMPTIONS 112
      • 7.1.2 RESEARCH METHODOLOGY 113
    • 7.2 CAMERAS 113
      • 7.2.1 GROWING DEMAND FOR NIGHT VISION SYSTEMS AND INTELLIGENT PARKING SYSTEMS TO INCREASE DEMAND 113
    • 7.3 CHIPS/SEMICONDUCTORS (ECU, SOC) 114
      • 7.3.1 GROWING DEMAND FOR ADVANCED AUTOMOTIVE FEATURES TO DRIVE SEGMENT 114
    • 7.4 RADAR SENSORS 115
      • 7.4.1 GROWING DEVELOPMENT OF AUTONOMOUS TECHNOLOGY TO INCREASE DEMAND FOR RADAR SYSTEMS IN VEHICLES 115
    • 7.5 LIDAR SENSORS 117
      • 7.5.1 INCREASING COST-EFFECTIVENESS OF LIDAR SYSTEMS TO INCREASE THEIR DEMAND IN AUTONOMOUS VEHICLES 117
    • 7.6 OTHERS 118
    • 7.7 KEY INDUSTRY INSIGHTS 119
  • 8 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY SOFTWARE 120

    • 8.1 INTRODUCTION 121
      • 8.1.1 ASSUMPTIONS 122
      • 8.1.2 RESEARCH METHODOLOGY 122
    • 8.2 OPERATING SYSTEM 123
      • 8.2.1 NEED FOR EFFICIENT DATA MANAGEMENT TO INCREASE OPERATING SYSTEM APPLICATION IN AUTONOMOUS VEHICLES 123
    • 8.3 MIDDLEWARE 123
      • 8.3.1 INCREASED USE OF SENSOR FUSION IN AUTONOMOUS VEHICLE APPLICATIONS TO INCREASE MIDDLEWARE USE 123
    • 8.4 APPLICATION SOFTWARE 124
      • 8.4.1 GROWING LEVEL OF AUTOMATION TO INCREASE DEMAND FOR APPLICATION SOFTWARE 124
    • 8.5 KEY INDUSTRY INSIGHTS 125
  • 9 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY LEVEL OF AUTONOMY 126

    • 9.1 INTRODUCTION 127
      • 9.1.1 ASSUMPTIONS 129
      • 9.1.2 RESEARCH METHODOLOGY 129
    • 9.2 L3 129
      • 9.2.1 INCREASING SAFETY MANDATES TO FUEL DEMAND FOR L3 AUTONOMOUS VEHICLES 129
    • 9.3 L4 130
      • 9.3.1 GROWING SHIFT TOWARD FULL AUTOMATION TO INCREASE DEMAND FOR SENSORS FOR L4 AUTONOMOUS VEHICLES 130
    • 9.4 L5 131
      • 9.4.1 DEMAND FOR L5 AUTONOMY IN TAXIS AND PASSENGER VEHICLES TO DRIVE MARKET 131
    • 9.5 KEY INDUSTRY INSIGHTS 132
  • 10 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY PROPULSION 133

    • 10.1 INTRODUCTION 134
      • 10.1.1 ASSUMPTIONS 135
      • 10.1.2 RESEARCH METHODOLOGY 135
    • 10.2 ICE 136
      • 10.2.1 INCREASING SAFETY REGULATIONS TO FUEL DEMAND FOR SENSORS IN ICE AUTONOMOUS VEHICLES 136
    • 10.3 ELECTRIC 136
      • 10.3.1 ELECTRIFICATION TARGETS BY COUNTRIES TO DRIVE OEMS TOWARD DEVELOPING L4 AND ABOVE FEATURES MAINLY FOR EVS 136
    • 10.4 KEY INDUSTRY INSIGHTS 137
  • 11 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY VEHICLE TYPE 138

    • 11.1 INTRODUCTION 139
      • 11.1.1 OPERATIONAL DATA 140
      • 11.1.2 ASSUMPTIONS 141
      • 11.1.3 RESEARCH METHODOLOGY 141
    • 11.2 PASSENGER CARS 141
      • 11.2.1 MANDATES FOR LDW, DMS, AND FCW FEATURES TO INCREASE ADAS AND AUTONOMOUS VEHICLE DEMAND IN PASSENGER CARS SEGMENT 141
    • 11.3 COMMERCIAL VEHICLES 142
      • 11.3.1 PLANS BY COUNTRIES TO MANDATE ADAS FEATURES TO INCREASE DEMAND FOR AUTONOMOUS COMMERCIAL VEHICLES 142
    • 11.4 KEY INDUSTRY INSIGHTS 143
  • 12 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY SENSOR PLATFORM APPROACH 144

    • 12.1 INTRODUCTION 145
      • 12.1.1 ASSUMPTIONS 148
      • 12.1.2 RESEARCH METHODOLOGY 148
    • 12.2 LOW-LEVEL FUSION 148
      • 12.2.1 RAPID DEVELOPMENT OF ADVANCED SENSORS AND NEED FOR ACCURATE OBJECT DETECTION TO DRIVE SEGMENT 148
    • 12.3 MID-LEVEL FUSION 149
      • 12.3.1 DEMAND FOR SAFETY FEATURES IN VEHICLES TO DRIVE SEGMENT 149
    • 12.4 HIGH-LEVEL FUSION 150
      • 12.4.1 INCREASING DEVELOPMENT OF BASIC SENSOR FUSION IN AUTOMOBILES TO DRIVE SEGMENT 150
    • 12.5 KEY INDUSTRY INSIGHTS 151
  • 13 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY SENSOR FUSION PROCESS 152

    • 13.1 INTRODUCTION 153
      • 13.1.1 ASSUMPTIONS 154
      • 13.1.2 RESEARCH METHODOLOGY 155
    • 13.2 SIGNAL-LEVEL FUSION 155
      • 13.2.1 DEVELOPMENT OF NEW SENSORS WITH HIGHER ACCURACY AND LOWER COST TO INCREASE DEMAND FOR SIGNAL-LEVEL SENSOR FUSION 155
    • 13.3 OBJECT-LEVEL FUSION 156
      • 13.3.1 ADVANCEMENTS IN AI TECHNOLOGIES TO DRIVE DEMAND FOR OBJECT-LEVEL SENSOR FUSION 156
    • 13.4 FEATURE-LEVEL FUSION 157
      • 13.4.1 NEED FOR MORE ACCURATE AND RELIABLE DATA FOR DECISION-MAKING IN COMPLEX AND DYNAMIC DRIVING ENVIRONMENTS TO DRIVE SEGMENT 157
    • 13.5 DECISION-LEVEL FUSION 158
      • 13.5.1 GOVERNMENT REGULATIONS FOR SAFER DRIVING SYSTEMS AND INCREASING DEMAND FOR AUTONOMOUS TRANSPORTATION TO DRIVE SEGMENT 158
    • 13.6 KEY INDUSTRY INSIGHTS 159
  • 14 SENSORS MARKET FOR AUTONOMOUS VEHICLES, BY REGION 160

    • 14.1 INTRODUCTION 161
    • 14.2 ASIA PACIFIC 163
      • 14.2.1 CHINA 165
        • 14.2.1.1 Increasing deployment of autonomous vehicles for testing by ride-hailing aggregators to increase demand for sensors 165
      • 14.2.2 JAPAN 167
        • 14.2.2.1 Government initiatives for road safety and push for autonomous vehicles to drive market 167
      • 14.2.3 SOUTH KOREA 168
        • 14.2.3.1 Government focus on autonomous vehicle deployment to drive market 168
      • 14.2.4 INDIA 169
        • 14.2.4.1 Increasing prices of petrol and diesel to drive market 169
    • 14.3 EUROPE 170
      • 14.3.1 GERMANY 172
        • 14.3.1.1 Strong autonomous vehicle development ecosystem to drive market 172
      • 14.3.2 FRANCE 173
        • 14.3.2.1 Government mandates for road safety to increase demand for autonomous vehicle sensing systems 173
      • 14.3.3 ITALY 175
        • 14.3.3.1 Growing consumer demand for luxury automobiles with advanced safety features to drive market 175
      • 14.3.4 UK 175
        • 14.3.4.1 Increasing demand for advanced safety and leisure features on luxury vehicles to drive market 175
      • 14.3.5 REST OF EUROPE 177
    • 14.4 NORTH AMERICA 177
      • 14.4.1 US 179
        • 14.4.1.1 Government support for developing and testing autonomous vehicles to drive market 179
      • 14.4.2 CANADA 181
        • 14.4.2.1 Strong start-up ecosystem and presence of leading tier 1 component manufacturers to drive market 181
    • 14.5 REST OF THE WORLD 182
      • 14.5.1 BRAZIL 184
        • 14.5.1.1 Expansion of R&D centers for autonomous vehicle development due to export demand to drive market 184
      • 14.5.2 UAE 185
        • 14.5.2.1 Increasing development in autonomous driving to boost market 185
      • 14.5.3 OTHERS 186
  • 15 COMPETITIVE LANDSCAPE 187

    • 15.1 OVERVIEW 187
    • 15.2 MARKET RANKING ANALYSIS 187
    • 15.3 MARKET EVALUATION FRAMEWORK: REVENUE ANALYSIS OF TOP LISTED/PUBLIC PLAYERS 189
    • 15.4 COMPETITIVE SCENARIO 190
      • 15.4.1 DEALS 190
      • 15.4.2 PRODUCT DEVELOPMENTS 191
      • 15.4.3 OTHERS, 2020-2023 192
    • 15.5 COMPETITIVE LEADERSHIP MAPPING FOR SENSORS MARKET FOR AUTONOMOUS VEHICLES 193
      • 15.5.1 STARS 193
      • 15.5.2 EMERGING LEADERS 193
      • 15.5.3 PERVASIVE PLAYERS 194
      • 15.5.4 PARTICIPANTS 194
    • 15.6 COMPANY EVALUATION QUADRANT: SENSORS MARKET FOR AUTONOMOUS VEHICLES 195
    • 15.7 SENSORS MARKET FOR AUTONOMOUS VEHICLES: COMPANY APPLICATION FOOTPRINT FOR MANUFACTURERS, 2022 195
    • 15.8 SENSORS MARKET FOR AUTONOMOUS VEHICLES: REGIONAL FOOTPRINT FOR MANUFACTURERS, 2022 196
    • 15.9 COMPETITIVE EVALUATION QUADRANT: SMES AND START-UPS 197
      • 15.9.1 PROGRESSIVE COMPANIES 197
      • 15.9.2 RESPONSIVE COMPANIES 197
      • 15.9.3 DYNAMIC COMPANIES 197
      • 15.9.4 STARTING BLOCKS 197
  • 16 COMPANY PROFILES 200

    • 16.1 KEY PLAYERS 200
      • 16.1.1 ROBERT BOSCH GMBH 200
      • 16.1.2 CONTINENTAL AG 206
      • 16.1.3 ZF FRIEDRICHSHAFEN AG 212
      • 16.1.4 DENSO 217
      • 16.1.5 NXP SEMICONDUCTORS 222
      • 16.1.6 ALLEGRO MICROSYSTEMS 227
      • 16.1.7 STMICROELECTRONICS 231
      • 16.1.8 APTIV PLC 235
      • 16.1.9 LEDDARTECH 239
      • 16.1.10 VELODYNE LIDAR 243
      • 16.1.11 INFINEON TECHNOLOGIES 245
      • 16.1.12 NVIDIA 249
      • 16.1.13 QUALCOMM 254
      • 16.1.14 DATASPEED INC. 259
      • 16.1.15 BASELABS 261
    • 16.2 OTHER PLAYERS 264
      • 16.2.1 CTS CORPORATION 264
      • 16.2.2 MEMSIC SEMICONDUCTOR (TIANJIN) CO., LTD. 264
      • 16.2.3 KIONIX, INC. 265
      • 16.2.4 TDK CORPORATION 265
      • 16.2.5 MICROCHIP TECHNOLOGY INC. 266
      • 16.2.6 MONOLITHIC POWER SYSTEMS, INC. 266
      • 16.2.7 IBEO AUTOMOTIVE SYSTEMS GMBH 267
      • 16.2.8 RENESAS ELECTRONICS CORPORATION 267
      • 16.2.9 MOBILEYE 268
      • 16.2.10 MAGNA INTERNATIONAL 269
      • 16.2.11 ANALOG DEVICES 269
      • 16.2.12 VISTEON CORPORATION 270
      • 16.2.13 PHANTOM AI 270
      • 16.2.14 TESLA 271
      • 16.2.15 NEOUSYS TECHNOLOGY 271
      • 16.2.16 ALPHABET INC. 272
      • 16.2.17 INTEL CORPORATION 273
      • 16.2.18 MICROSOFT CORPORATION 274
      • 16.2.19 TE CONNECTIVITY LTD. 275
      • 16.2.20 MICRON TECHNOLOGY 276
      • 16.2.21 XILINX, INC. 277
      • 16.2.22 IBM 278
  • 17 RECOMMENDATIONS BY MARKETSANDMARKETS 279

    • 17.1 ASIA PACIFIC TO BE MOST LUCRATIVE REGION FOR SENSORS MARKET FOR AUTONOMOUS VEHICLES 279
    • 17.2 TECHNOLOGICAL ADVANCEMENTS TO HELP DEVELOP MARKET FOR AUTONOMOUS VEHICLES 279
    • 17.3 SOFTWARE SEGMENT TO WITNESS SIGNIFICANT OPPORTUNITIES IN COMING YEARS WITH INCREASED VIABILITY OF LOW AND MID-LEVEL SENSOR FUSION 280
    • 17.4 CONCLUSION 280
  • 18 APPENDIX 281

    • 18.1 KEY INSIGHTS FROM INDUSTRY EXPERTS 281
    • 18.2 DISCUSSION GUIDE 281
    • 18.3 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 284
    • 18.4 CUSTOMIZATION OPTIONS 286
    • 18.5 RELATED REPORTS 286
    • 18.6 AUTHOR DETAILS 287
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