Automotive LIDAR Sensors Market 2018 Analysis By Region, Key Players - Quanergy Systems, Ibeo Automotive, PulsedLight, Delphi Automotive, Texas Instruments, Bosch, And Trilumina

Automotive LIDAR Sensors Market Report 2018 provides Global Automotive LIDAR Sensors Market Size, Share, Growth, Trends, And Region Analysis By Application Type (Semi-Autonomous Vehicles, Autonomous Vehicles), By Image Type (2D Image, 3D Image), By Placement (Headlight & Taillight, Bumpers, Roof, Others), and by end market (OEMs, Aftermarket) Forecast To 2023

The prominent players in the automotive LIDAR sensors market include Valeo S.A. (France), Denso (Japan), PulsedLight (U.S.), Teledyne Optech (Canada), LeddarTech (Canada), Trilumina (U.S.), TetraVue (U.S.), Princeton Lightwave (U.S.), and HELLA GmbH  (Germany), Delphi Automotive (U.K.), Continental AG (Germany), ZF Friedrichshafen (Germany), Infineon Technologies (Germany), Velodyne LiDAR (U.S.), Texas Instruments Incorporated (U.S.), First Sensor AG(Germany), Robert Bosch (Germany), Ibeo Automotive (Germany), Quanergy Systems (U.S.).

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The market for automotive LIDAR sensors is also largely driven by its increasing use in the self-driving cars. LIDAR sensors enable the differentiation between a person on a bike and a person walking, and even at the speed and direction they are going in. LIDAR is the key sensor in self-driving cars with the combination of navigation system, predictability and high resolution object tracking. 

The increase in number of automated vehicles and the decrease in the manufacturing cost of the LIDAR sensors, will immensely contribute in the growth of the market. Increase in the manufacturing and adoption of connected cars in the developed economies, is further expected to generate huge opportunities for the growth of the automotive LIDAR sensors market. However, the growth of this market might be restrained by the huge cost associated with the use of expensive components such as navigation systems, laser scanners and high resolution 3D camera systems.  

Geographically, the global automotive LIDAR sensors market has been divided into four major regions of North America, Europe, Asia Pacific and Rest of the World. Amongst these, Europe region is expected to dominate the global market owing to the existence of a large number of OEMs and LIDAR manufacturers in the region. The major players in the Europe market are taking initiatives to geographically expand their presence by entering into partnerships and collaborations with both, global and regional players.

The report for global automotive LIDAR sensors market of Market Research Future comprises of extensive primary research along with the detailed analysis of qualitative as well as quantitative aspects by various industry experts, key opinion leaders to gain the deeper insight of the market and industry performance. The report gives the clear picture of current market scenario which includes historical and projected market size in terms of value and volume, technological advancement, macro economical and governing factors in the market. The report provides details information and strategies of the top key players in the industry. The report also gives a broad study of the different market segments and regions.

Table Of Contents:

1 Executive Summary

2 Scope Of The Report

2.1 Market Definition

2.2 Scope Of The Study

2.2.1 Definition

2.2.2 Research Objective

2.2.3 Assumptions

2.2.4 Limitations

2.3 Research Process

2.3.1 Primary Research

2.3.2 Secondary Research

2.4 Market Size Estimation

2.5 Forecast Model

3 Market Landscape

3.1 Porter’s Five Forces Analysis

3.1.1 Threat Of New Entrants

3.1.2 Bargaining Power Of Buyers

3.1.3 Threat Of Substitutes

3.1.4 Segment Rivalry

3.1.5 Bargaining Power Of Buyers

3.2 Value Chain/Supply Chain Analysis

List Of Figures:

FIGURE 1 Research Process Of MRFR

FIGURE 2 Top Down & Bottom Up Approach

FIGURE 3 Market Dynamics

FIGURE 4 Impact Analysis: Market Drivers

FIGURE 5 Impact Analysis: Market Restraints

FIGURE 6 Porter’s Five Forces Analysis

FIGURE 7 Value Chain Analysis

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