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LiDAR for Automotive Patent Landscape 2022

  • Report

  • 140 Pages
  • January 2022
  • Region: Global
  • Knowmade
  • ID: 4757853

From ADAS to Autonomous and Robotic Vehicles, What are the LiDAR Technologies and Related IP of Automotive Industry Players?

Report’s Key Features:

  • PDF with > 140 slides
  • Excel file > 11.900 patent families and hyperlink to an updated online database (legal status, documents etc.)
  • IP trends, including time evolution of published patents and countries of patent filings
  • Ranking of main patent assignees
  • Newcomers in the IP landscape
  • Patent categorization by type of LiDAR (mechanical, MEMS micromirrors, OPA, flash, ToF, FMCW, phase-shift, etc.)
  • IP position of key players, and relative strength of their patent portfolios.
  • Current main technological approaches
  • IP profiles of 35+ key players (tier one suppliers, LiDAR pure players, robotaxi/autonomous vehicle makers), including IP dynamics, legal status and geographical coverage of patents, IP strategies, key patents and recent IP developments
  • Excel database with all patents analyzed in the report, including technology segmentation and hyperlinks to an updated online database

The LiDAR-related patent landscape is very dynamic, with numerous newcomers

Over the last 7 years, the automotive industry has strongly believed that LiDAR would be one of the key sensors to develop high-level Advanced Driver Assistance Systems (ADAS) and 3D mapping solutions, unlocking the door to autonomous vehicles and robotaxis. Today, the market for LiDAR in automotive is divided between ADAS and robotic vehicles. Both applications show a high expected compound annual growth rate (CAGR) of 111% and 33% respectively over the 2020-2026 period, according to Yole Développement’s report. Players that can provide automotive-grade LiDAR with advanced 3D mapping would be in a good position to take a nice slice of the million-dollar cake. Being able to protect their position with strong intellectual property (IP) can be a big asset in this highly competitive industry.

In this context, the publisher is releasing a new patent landscape report covering the whole supply chain of LiDAR for automotive applications, from electronic components, optical systems and LiDAR devices to systems using LiDAR and computing. Patent landscape analysis is the perfect complement to market research, to fully comprehend the competitive landscape and technology roadmap, keep up with new technology developments, anticipate future technology adoption, and understand the different competitors’ strategies. This kind of patent landscape report reveals the companies, technical solutions and strategies not identified through standard market analysis.

The intellectual property (IP) landscape also confirms the strong enthusiasm for LiDAR. Indeed, since 2018 the industry has witnessed the entrance of many LiDAR pure players that contribute to the very strong acceleration in patenting activity. Furthermore, the low number of academics among patent applicants attests to the maturity of the technology. These players are today competing against well-established tier-one suppliers that benefit from their early activity related to low-level ADAS systems back in the 2000s.

The strong competition has already led to significant changes in the LiDAR-related patent landscape over the last 2 years. Indeed, Denso lost its leading IP position to Bosch. Chinese LiDAR pure players Hesai Technology and Robosense became the new IP challengers, while many smaller IP players just entered the game or closed the gap. In addition, as the LiDAR automotive market is just beginning to grow, many collaborations are occurring, and mergers and acquisitions (M&A) may happen to consolidate the players’ market and IP position.


LiDAR-related patents published worldwide and covering the whole value chain

this publisher’s analysts have selected and analyzed more than 24,000 patent applications published worldwide up to July 2021 and corresponding to 11,900+ patent families (inventions) related to LiDAR for automotive applications (ADAS and robotic cars). This report includes patents describing LiDAR components (laser, lenses, mirrors, etc.), LiDAR devices and systems using LiDAR (anticollision system, autonomous vehicles, 3D mapping systems, etc.). The publisher has identified more than 2,000 different patent assignees involved in the LiDAR for automotive.


IP players’ positions, current developments & IP strategies

The report provides a clear overview of the most active patent applicants as well as a presentation of newcomers to the patent landscape. Furthermore, patent segmentation reveals the IP position of patent assignees by LiDAR technology. The IP landscape analysis shows that where major IP players are involved, the competition is mainly focused on mechanical LiDAR. In addition, recent inventions indicate that LiDAR is a mature technology where the main innovations are no longer related to LiDAR itself but to LiDAR assembly, as well as control or calibration methods. Technologies providing embedded software to reduce interference and parasitics (including environmental hazards) and maintain LiDAR performance in all conditions are the main technologies described in recent patent applications. Despite their advantages and promises, solid-state LiDAR solutions (OPA, flash) remain very small IP segments where a limited number of IP players are competing.


Focus on key players’ patent portfolios

The report provides a detailed analysis of 36 key IP players and most promising IP newcomers: Bosch, Denso, Valeo, Continental, Quanergy, LeddarTech, XenomatiX, Luminar, Velodyne, LeiShen, Hesai, Robosense, Ibeo, Ouster, Sense Photonics, Aptiv, Innoviz, Aeva, Aeye, Innovusion, SOSLAB, Zvision, SiLC, Oradar, Blickfeld, Richbeam, Apollight, Hitronics, Olei, Vanjee, Waymo, Baidu, Uber, Cruise, Zoox and Aurora. For each player, the publisher summarizes their IP portfolio and key patents, make the links between patents and products to highlight the protected LiDAR systems, and unveil their IP strategies by analyzing their recent patents and IP collaborations.


Understand the current dynamics and technological trends

Current patenting activities, geographical coverage and technological segments are analyzed. In this report, the publisher highlights the main technical challenges faced by the industry to enhance the LiDAR and sensing systems’ performances. The report focuses especially on LiDAR architecture and hardware solutions such as optical path arrangements, VCSEL array and detector arrangements. Methods to drive the emitter to enhance the LiDAR field of view, reduce power consumption or enhance detector sensitivity are described.


Useful Excel patent database

The report also includes an Excel database with the 11,900+ patent families (inventions) analyzed in this study. This useful patent database allows for multi-criteria searches and includes patent publication numbers, hyperlinks to an updated online database (original documents, legal status, etc.), priority dates, title, abstract, patent assignees, patent’s current legal status, and segments (mechanical, MEMS micromirrors, OPA, flash, ToF, FMCW, phase shift, etc.).


Table of Contents

Introduction
  • Market Data
  • Definition & Principle
Scope of the Report
  • Scope of the Report
  • Key Feature of the Report
  • Objectives of the Report
Methodology
  • Patent Search, Selection and Analysis
  • Terminologies for Patent Analysis
Executive Summary
Patent Landscape Overview
  • Time Evolution of Patent Publications
  • Main Patent Assignees and Their Typology (Tier-1 Suppliers, Car Makers, LiDAR Pure Players, Robotaxis Makers, Electronics Company, R&D Labs)
  • Well-Established IP Players and IP Newcomers
  • IP Landscape Evolution from 2018 to 2021
  • Current Legal Status of Patents
  • Main Countries of Filings for Granted Patent and Pending Applications
  • Geographical Coverage of Main Patent Assignees’ Patent Portfolio
  • Technical Segmentation (Mechanical, MEMS Micromirrors, OPA, Flash, ToF, FMCW, Phase Shift, Etc.)
  • Main Patented Technologies for Automotive LiDAR Pure Players and Tier One Suppliers
Tier One Suppliers
  • IP Leadership of Patent Assignees
  • Main Trends & Dynamics
  • IP Profile of Bosch, Continental, Valeo, Denso
  • IP Portfolio Overview, IP Strategy, IP Collaborations, Key Patents and Related Technologies, Recent Patenting Activities, Etc.
LiDAR Pure Players
  • IP Leadership of Patent Assignees
  • Main Trends & Dynamics
  • IP Profile of Quanergy, Leddartech, Xenomatix, Luminar, Velodyne, Leishen, Hesai, Robosense, Ibeo, Ouster, Sense Photonics, Aptiv, Innoviz, Aeva, Aeye,, Innovusion, Soslab, Zvision, Silc, Oradar, Blickfeld, Richbeam, Apollight, Hitronics, Olei, Vanjee
  • IP Portfolio Overview, IP Strategy, IP Collaborations, Key Patents and Related Technologies, Recent Patenting Activities, Etc.
Robotic Car Makers (Robotaxis)
  • IP Leadership of Patent Assignees
  • Main Trends & Dynamics
  • IP Profile of Waymo, Zoox, Uber, Baidu, Cruise, Aurora
  • IP Portfolio Overview, IP Strategy, IP Collaborations, Key Patents and Related Technologies, Recent Patenting Activities, Etc.
Conclusion

Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • Bosch
  • Denso
  • Mitsubishi
  • Nissan
  • Toyota
  • Sick
  • Daimler
  • Omron
  • General Motors
  • Valeo
  • Ford
  • Honda Motor
  • Hyundai
  • Continental
  • Mazda Motor
  • Sanyo
  • Ricoh
  • BMW
  • Daihatsu
  • Waymo
  • Hitachi
  • Volkswagen
  • Xenomatix
  • NEC
  • Panasonic
  • Google
  • Audi
  • Nikon
  • Fujitsu
  • Changan University
  • Omron Automotive Electronics
  • Kansei
  • Ibeo Automotive
  • Volvo
  • Chery Automobile
  • Shenzhen Leishen Intelligent Systems
  • Raytheon
  • Sharp
  • Hokuyo Automatic
  • Shiny Technology
  • Uber
  • Nippon Soken
  • Velodyne
  • Qualcomm
  • Shanghai Slamtec
  • BASF
  • Philips
  • Fraunhofer
  • Zoox
  • Quanergy Systems
  • Apple
  • Texas Instruments
  • LG Innotek
  • Scania
  • Qinetiq
  • Luminar Technologies
  • Hesai Photonics
  • Robosense
  • AEYE
  • AEVA
  • HITQZ
  • Richbeam
  • Fexa
  • Nvidia
  • Huawei
  • Nuro
  • Pony AI
  • Vanjee
  • Innovusion
  • Blickfeld
  • Aptiv

Methodology

For patent landscape analysis, the patent information is extracted from the FamPat worldwide patent database (Questel-ORBIT) which provides 100+ million patent documents from 95 worldwide patent offices.

The search strategy combines keyword-based searches with expert review and manual screening of the patents. Keywords are searched in the title, abstract, claims and description. Relevant IPC (International Patent Classification) and CPC (Cooperative Patent Classification) are also used for the patent search. The dataset of identified patents is manually cleaned of non-relevant patents. Citing and cited patents of selected relevant patents are also included in the search strategy. The search strategy (keywords and search equations) and the dataset of selected patents is provided in our reports.

The publisher's analysts (PhD team) combine their technical and patent expertise with powerful analytics tools and proprietary methodologies to deliver the most relevant patent analyses.

 

 

 

 

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