The global market for lidar in automotive will reach US$9.5 billion by 2034

Lidar 2024-2034: Technologies, Players, Markets & Forecasts

TOF or FMCW detection; mechanical, MEMS, OPA, flash, liquid crystal and other solid-state lidar for ADAS, autonomous vehicles, industrial, smart city, security and mapping with automotive focus


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In recent years, with the development and progress of autonomous-driving features, the automotive industry has witnessed remarkable advancements in sensor technologies, with one particular innovation gaining significant attention: three dimensional light detection and ranging (LiDAR), a remote sensing method that uses laser light to measure distances and create precise 3D maps of the surroundings.
 
The lidar market for automotive applications will grow to US$9.5 billion by 2034. The demand for lidars to be adopted in the automotive industry drives the huge investment and rapid progression of lidars, with the innovations in beam steering technologies, performance improvement, and cost reduction in lidar transceiver components. These efforts can enable lidars to be implemented in a wider application scenario beyond conventional usage and automobiles. IDTechEx leverages its experiences such as in laser physics, semiconductors, optics, sensors, optoelectronics, and transportation, to provide a comprehensive analysis on technologies and products. 10-year market forecasts on lidar units and market value with a focus on automotive have been provided. IDTechEx also offers major lidar adoption details such as vehicle model, launch time, lidar player, lidar model, lidar type, number of lidars adopted, location on the vehicle for current existing and near-future automotive adoptions.
 
Following a period of dedicated research by expert analysts, IDTechEx has published a report that offers unique insights into the global 3D lidar technology landscape and corresponding market. The report contains a comprehensive analysis of market status and forecasts focus on the automotive industry, with the technology analysis also potentially applied to lidars for industrial automation, robotics, smart city, security, and mapping. Importantly, the report presents an unbiased analysis of primary data gathered via our interviews with key players, and it builds on our expertise in the transport, electronics and photonics sectors.
 
This research delivers valuable insights for:
  • Companies that require lidars*
  • Companies that develop lidars
  • Companies that supply components and materials for lidars
  • Companies that invest in lidars
  • Companies that develop other technologies for machine automation
  • Companies interested in emerging technologies
*or similar and competing sensors
 
The lidar revolution: Enabling more machines to see the world
 
Lidar, which stands for light detection and ranging, is a ranging technique that has existed for decades, with a long history that dates back to the invention of the laser around the 1960s, shortly after the invention of laser. Lidar has already been used in applications such as mapping, surveying, military, archaeology, agriculture, and geology.
 
However, it was not until the 2000s that the technology started to be applied in commercial automotive applications that benefited from the development of 3D LiDAR, which provides 3D information using a beam steering system. The invention of beam steering technologies enables lidar to reach 3D space for extended use scenarios.
 
3D lidar is an optical perception technology that enables machines to see the world, make decisions and navigate. At present, machines using lidar range from small service robots to large autonomous vehicles. The rapidly evolving lidar technologies and markets leave many uncertain questions to answer. The technology landscape is cluttered with numerous options for every component in a lidar system. IDTechEx identified four important technology choices that every lidar player and lidar user must make: measurement process, laser, beam steering mechanism, and photodetector. The beam steering mechanism is the most complicated and critical choice, while the emitter and receiver (transceiver) play an important role in future lidar cost reduction and further performance enhancement.
 
Four important technology choices in designing or selecting a 3D lidar module. Source: IDTechEx
 
Which to win: Competitive technology landscape
 
With numerous technological choices for the key components and measurement methods, various technology combinations can be generated, making players working in this space distinctive to each other. Most players in the space claim to offer a unique, next-generation product that is superior to competing technologies.
 
Lidar technology choices. Source: IDTechEx
 
However, the options are not unlimited. Certain components may work better with a particular technology, such as vertical cavity surface emitting laser (VCSEL) is a more popular choice for 3D flash lidar compared with edge emitting laser (EEL). While VCSEL is mature with 905 nm wavelength, it can be very difficult to realize using short wavelength infrared (SWIR). There are also fewer common combinations such as MEMS with FMCW due to more technical challenges.
 
With the experience in laser physics, semiconductor physics, optoelectronics, in addition to experience in advising multi-billion-dollar corporations on business growth and technology strategy, IDTechEx has built expertise in the transport, electronics and photonics sectors and can provide comprehensive technological analysis and benchmarking.
 
The technology choices made today will have immense consequences for performance, price, and scalability of lidar in the future. The present state of the lidar market is unsustainable because winning technologies and players will inevitably emerge, consolidating the technology and business landscapes.
 
Vision only or sensor fusion: Where will the market go?
 
As a representative company, Tesla stands by the vision-only camp, while the majority of automotive OEMs pursue sensor fusion with lidar included as their future answer. The demand of redundancy and increasing requirement for 3D information make lidar more and more attractive. The battle in automotive ADAS and the autonomous vehicle market helps to provide an opportunity for lidar to be accepted by other application markets with reducing price and increasing reliability. The efforts through the lidar supply chain, from materials suppliers to automotive OEMs, not only offer opportunities for conventional material and component companies, but also enables new lifestyles for the consumer with upcoming innovations.
 
 
Global lidar player distribution. Source: IDTechEx
 
Chinese players vs non-Chinese players, OEMs/ Tier1s vs Lidar companies
 
Coming to 2024, numerous lidar adoptions have been addressed by the public. The initial purpose of integrating LiDAR into the automotive industry was to leverage its unique benefits to address the limitations of existing sensors like cameras, which is often highlighted by many LiDAR startup companies. However, recent research by IDTechEx suggests that the current and near-future adoption of LiDAR in automotive applications is not primarily driven by performance considerations. The OEMs and Tier 1 companies have very different considerations compared with Tier 2 lidar companies, with the latter focusing more on technology advancement and performance improvement, while the former values other factors equally or more: costs, reliability, the possibility to pass automotive grade, supply chain, mass-production capability, scalability and ease of integration, to name a few. In addition, the market landscape shows very different behavior in the Chinese market and non-Chinese markets.
 
IDTechEx has focused on players who position themselves as automotive Tier 2 suppliers, with a coverage of component suppliers and automotive OEMs. The report explores how innovations in lidar technology affect the growth of lidar market segments. In the technical analysis chapters, IDTechEx uses its experience in physics research to explain novel technical concepts to a non-specialist audience. Market forecasts are based on the extensive analysis of primary and secondary data, combined with careful consideration of market drivers, restraints, and key player activities. The technology adoption roadmaps for six types of lidar in four types of level 3+ autonomous vehicles are evaluated to provide a balanced outlook on market opportunities.
 
IDTechEx's model of the lidar market considers how the following variables evolve during the forecast period for each beam steering technology segment: technology readiness level of lidar, lidar unit price, vehicle production volume; autonomous vehicle technology adoption; lidar technology adoption; lidar market share per autonomous vehicle segment.
 
Our report answers important questions such as:
  • What are the lidar technology choices available today, and how do these choices impact on product development and product positioning?
  • What is the present status of each lidar technology and what are the future trends and opportunities?
  • How is the lidar business landscape evolving in terms of the supply chain, efforts and partnerships?
  • How will each lidar market segment evolve in the short-term and long-term?
 
Examples of lidar configurations considered in our market analysis and forecasts for level 3+ autonomous vehicles. Source: IDTechEx
 
Key Aspects of this report:
 
Technology analysis & trends
  • Benchmarking studies on beam steering technologies, detection methods, laser emitters and receivers
  • Business chance analysis of key technologies
  • Progression and trend in lidar technology for automotive applications
  • Lidar integration and introduction to relevant regulations
 
Market Analysis & Forecasts:
  • 10-year lidar market forecasts (units & value) by autonomy level for automotive application
  • 10-year lidar market forecasts (units & value) by beam steering technology for automotive application
  • Forecast of lidar unit price by technology
 
Supply chain
  • Automotive lidar supply chain
  • Representative players in the supply chain
  • Existing and near-future vehicle models equipping with lidars
 
Status and Trend
  • Existing and near-future adoption of lidars in Automotive models
  • Technology trend
  • Business analysis
Report MetricsDetails
Historic Data2022 - 2023
CAGRThe global market for automotive lidar will reach US$9.5 billion by 2034, which represents a CAGR of 19.5% compared with 2024.
Forecast Period2024 - 2034
Forecast UnitsVolume (unit), value (US billion)
Regions CoveredWorldwide
Segments CoveredL3 Private Vehicle: Passenger Car L4, L5 Private Vehicle: Passenger Car L4, L5 Shared Mobility: Robotaxi, Shuttle, Bus L4, L5 Off-Way Vehicle: Van, Truck Rotating Mech Non-Rotating Mech MEMS or MOEMS OPA 3D Flash Other
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Table of Contents
1.EXECUTIVE SUMMARY
1.1.Automotive lidar players by technology
1.2.Mechanical lidar players
1.3.Micromechanical lidar players
1.4.Pure solid-state lidar players: OPA & liquid crystal
1.5.Pure solid-state lidar players: 3D flash
1.6.FMCW lidar players
1.7.SWIR lidar players
1.8.IPO, direct listing, SPAC
1.9.Thoughts on lidar photo detection methods
1.10.IDTechEx's opinions on ranging method
1.11.Summary of lidars with various beam steering technologies
1.12.Comparison of common beam steering options
1.13.Summary on beam steering technologies
1.14.Battle between 905nm and 1550nm
1.15.Lidar component high level analysis
1.16.Drivers for current lidar adoption
1.17.Factors driving lidar adoption
1.18.Concerns of Lidar business
1.19.Chinese players versus non-Chinese players
1.20.Other commercialized vehicles equipped with Lidar
1.21.Manufacturing of listed / SPAC lidar companies
1.22.Representative MEMS lidar products for automotive application
1.23.Automotive grade non-rotating mechanical lidar products
1.24.Representative 3D flash lidar products for automotive application
1.25.Cost reduction approaches
1.26.BOM cost estimation
1.27.Price/cost composition
1.28.Lidar price analysis
1.29.Forecast of lidar unit price by technology 1
1.30.Forecast of lidar unit price by technology 2
1.31.Lidars per vehicle by technology
1.32.Unit forecast of vehicles with lidars
1.33.Global automotive lidar unit by technology
1.34.Global automotive lidar unit by vehicle type
1.35.Global automotive lidar market value by technology
1.36.Global automotive lidar market value by vehicle type
1.37.Global automotive lidar unit by technology in 2024 & 2031
1.38.Player geographic distribution
1.39.3D Lidar: Market segments & applications
1.40.Lidar applications
1.41.Lidar value chain
1.42.Lidar ecosystem
1.43.Automotive lidar supply chain
2.AUTONOMOUS DRIVING
2.1.Autonomous driving technologies
2.2.Autonomous driving levels
2.3.Today's automated driving market
2.4.Position navigation technology
2.5.Autonomous driving basics
2.6.Sensor fusion for ADAS/AV
2.7.Vision-only or sensor fusion?
2.8.Pure vision vs lidar sensor fusion
2.9.Challenges of pure vision solution
2.10.Optical 3D sensing: Comparison of common methods
2.11.Multi-camera
2.12.Structured light
2.13.Comparison of 3D depth-aware imaging
2.14.Are cameras alone sufficient?
2.15.Angular resolution
2.16.Resolution requirements
2.17.Radar or lidar
2.18.ADAS/AV sensor operating wavelength
2.19.Autonomous driving sensor comparison
2.20.Radar hardware
2.21.Camera hardware
2.22.Engine control unit
2.23.Minimum hardware requirements for ADAS/AV
2.24.ADAS/AV hardware general challenges
3.TECHNOLOGY ANALYSIS
3.1.Lidar subsystem
3.2.Lidar classifications
3.3.Automotive lidar: Operating process
3.4.Automotive lidar: Requirements
3.5.Lidar challenges
3.6.Lidar system
3.7.Laser range finder function for the first production car
3.8.Lidar working principle
3.9.SWOT analysis of automotive lidar
3.10.Comparison of lidar product parameters
3.11.Important parameters for lidar performance
3.12.Lidar technology combination choices
3.13.Overall technology analysis
3.14.Lidar development trend
3.15.Lidar beam steering trends
3.16.2D vs 3D lidar
4.RANGING OPTIONS/PHOTO DETECTION OPTIONS FOR LIDAR
4.1.Direct and indirect time of flight
4.2.Direct TOF: Time measurement via pulsed light
4.3.Signal attenuation in Rx
4.4.Indirect TOF: Phase measurement via amplitude modulation
4.5.FMCW vs PMCW
4.6.Frequency modulated continuous wave (FMCW)
4.7.Discussions around FMCW
4.8.Major challenges of FMCW lidars
4.9.Major challenges of FMCW lidars (cont.)
4.10.TOF vs FMCW lidar 1
4.11.TOF vs FMCW lidar 2
4.12.Application examples with velocity information
4.13.Velocity measurement for FMCW and TOF
5.BEAM STEERING OPTIONS FOR LIDAR
5.1.Lidar scanning categories
5.2.Overview of beam steering technologies
5.3.SWOT analysis of mechanical lidar
5.4.SWOT analysis of MEMS lidar
5.5.SWOT analysis of 3D flash lidar
5.6.SWOT analysis of OPA lidar
5.7.SWOT analysis of liquid crystal lidar
5.8.Mechanical Lidar
5.9.Lidar steering system: Mechanical rotating (rotating assemblies)
5.10.Lidar steering system: Mechanical rotating (nodding-mirror)
5.11.Lidar steering system: Mechanical rotating (multi-facet mirror)
5.12.Lidar steering system: Mechanical (Risley prisms)
5.13.Mechanical lidar beam steering trends
5.14.Technology trend of mechanical lidars
5.15.MEMS Lidar
5.16.Basic composition of MEMS lidar
5.17.Lidar steering system: MEMS
5.18.Classifications of MEMS scanner
5.19.Comparison of MEMS actuations
5.20.Electrostatic MEMS
5.21.Electromagnetic MEMS
5.22.Piezoelectric MEMS
5.23.Electrothermal MEMS
5.24.MEMS mirrors: Operation mode
5.25.One-dimensional MEMS lidar
5.26.Two-dimensional MEMS lidar
5.27.Analysis of MEMS-based lidars
5.28.Representative MEMS players
5.29.Flash lidar
5.30.Lidar steering system: Flash
5.31.VCSEL progress for 3D flash lidar
5.32.Optical phased array (OPA) Lidar
5.33.Lidar steering system: OPA
5.34.OPA principle
5.35.Side lobe issue improvement for OPA
5.36.OPA based on silicon nitride
5.37.Hybrid: MEMS-actuated grating OPA
5.38.Analysis of OPA-based lidars
5.39.Others that also belong to OPA
5.40.Others
5.41.Spectral deflection
5.42.Micro-motion technology
5.43.Liquid crystal lidar
5.44.Liquid crystal polarisation gratings
5.45.Liquid crystal optical phased arrays
5.46.Metamaterial based scanners 1
5.47.Metamaterial based scanners 2
5.48.GLV-based beam steering
5.49.Controlling the GLV device
5.50.Liquid lens
5.51.Electro-optical deflectors
5.52.Acousto-optical deflectors
6.LASER EMITTER OPTIONS FOR LIDAR
6.1.LED Illumination: Limited to short-range depth sensors
6.2.Laser operating principles
6.3.Laser technology choices
6.4.Introduction to laser diodes
6.5.Homojunction & heterojunction devices
6.6.Laser diode semiconductor selection
6.7.IR emitters
6.8.Edge-emitting lasers (EEL)
6.9.Vertical-cavity surface-emitting lasers (VCSEL)
6.10.External cavity & quantum cascade lasers (QCL)
6.11.IR emitters and comparisons
6.12.EEL vs VCSEL for lidar
6.13.EEL vs VCSEL
6.14.Laser diode device structure
6.15.Lidar model examples with VCSEL emitters
6.16.Optical feedback & operating temperature
6.17.Reliability & lifetime considerations
6.18.Key operating parameters
6.19.SWOT Analysis: EEL & VCSELs for lidar
6.20.SWOT Analysis: ECDLs & QCLs for lidar
6.21.SWOT Analysis: Fiber lasers & DPSSLs for lidar
6.22.Introduction to fibre lasers
6.23.Fibre laser operating principle
6.24.Wavelengths and modes
6.25.Fiber amplifiers
6.26.Fiber lasers for automotive lidar
6.27.Luminar technologies patent
6.28.Google & Waymo fiber laser patent
6.29.Diode-pumped solid-state lasers (DPSSL)
6.30.Diode-pumped solid-state lasers
6.31.Continental DPSSL lidar patent
6.32.Laser wavelength discussions
6.33.Spectral response of different emitters and photodiodes in comparison with solar spectrum
6.34.Laser source wavelengths
6.35.Wavelength comparison: 905 nm VS 1550 nm
6.36.Comparison of common laser type & wavelength options
7.RECEIVER OPTIONS FOR LIDAR
7.1.Photodetector choice for lidar
7.2.PIN photodiode
7.3.Avalanche Photo Diode (APD)
7.4.Single-photon avalanche diodes
7.5.Silicon photomultiplier
7.6.On Semicondctor SiPM trend
7.7.SPAD vs SiPM
7.8.Linear vs Geiger mode
7.9.Issues with Geiger mode APD 1
7.10.Issues with Geiger mode APD 2
7.11.Lidar detector comparison
7.12.Comparison of common photodetectors
7.13.Major lidar detector players
8.SIGNAL AND DATA PROCESSING
8.1.Point cloud
8.2.Lidar signal applications
8.3.Lidar perception hierarchy descriptions for AV
8.4.3D point cloud modelling
8.5.Reflection complication
8.6.Background noise & interference
8.7.Additional information
8.8.TOF lidar's spatial data analysis 1
8.9.TOF lidar's spatial data analysis 2
8.10.3D position & velocity data from FMCW Lidars
8.11.Poor weather performance: Challenges & solutions
8.12.Pipeline of classic lidar perception data processing
9.LIDAR INTEGRATION AND CLEANING
9.1.Lidar Integration
9.2.Lidar integration considerations
9.3.Lidar integration positions for ADAS/AV
9.4.Lidar integration in lamps
9.5.Lidar integration in the grille
9.6.Lidar integration on/in the roof
9.7.Lidars integrated in other positions
9.8.Installation location with increasing popularity
9.9.Glass for in cabin lidar
9.10.Possible lidar integration and unit numbers
9.11.Lidar cleaning
9.12.Lidar cleaning
9.13.Ford's idea
9.14.Squirt cleaning
9.15.Valeo's cleaning system
9.16.Squirt cleaning system
9.17.Ultrasonic cleaning
9.18.Other ideas
10.VALIDATION, REGULATIONS AND STANDARDS
10.1.Introduction
10.2.Safety and standards on ADAS/AV vehicles
10.3.UNECE for L3 automation regulations
10.4.Lidar certification process
 

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Report Statistics

Slides 252
Forecasts to 2034
Published Mar 2024
ISBN 9781835700235
 

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