自动驾驶汽车和机器人的士 2020-2040：参与者、技术和市场预测

The arrival of autonomous driving will revolutionise the way people travel. Autonomous cars could liberate people from the driving tasks and potentially enhance road safety and efficiency. Autonomous driving (AD) will also improve travel convenience for those who are unable to drive. Currently the autonomous driving system cost is still very high but with the growing maturity of key technologies such as lidars, radars, cameras, artificial intelligence (AI) software and specialized computers, it is expected the cost of autonomous cars will drop significantly in the coming decade.

 

Mobility services enabled by autonomous driving technology, which allows fleet operators to eliminate the biggest operation cost - the human driver - will offer a cheaper alternative to purchasing and owning a private car. In the next two decades, we expect mobility-as-a-service (MaaS) will grow rapidly to meet the increasing travel demand and in the meanwhile gradually replace private driving. IDTechEx forecasts that in a moderate scenario, 30% of the total travel demand will be provided by MaaS by 2040 and global passenger car sales are expected to peak in 2031.

 

Autonomous driving is changing the existing automotive supply chain from the traditional system of OEMs and suppliers to a collaborative ecosystem comprising OEMs, mobility service providers, software and hardware solution providers, as well as infrastructure providers. We have recently seen competitors joining hands and forming some unlikely-sounding alliances to reduce the cost of AD development, as well as to share resources and capabilities.

 

Autonomous driving provides huge value opportunities for a wide range of stakeholders across the mobility sector. This report offers an in-depth analysis of key enabling technologies including lidars, radars, cameras, AI software, HD maps, and 5G & V2X. Key players with their latest technologies and product commercialisation plans are presented as the case studies of this report.

 

We provide a twenty-year market forecast, in both sales numbers and revenues, for both private-owned autonomous cars and shared cars for mobility services (or robotaxis). For the market value forecast, we break it down into the revenues from AV sales as well as revenues from AV mobility services. We built a twenty-year model because our forecast suggests that the transformation towards fully autonomous driving will take place over a long timescale. We also builds a twenty-year market value forecast for the key components of AV systems - lidars, radars, cameras, AI software, computers etc. According to our forecasts, by 2040 global autonomous car (SAE Level 3+) and robotaxi services will become a $2.5 trillion market. By 2030, the autonomous driving system (including lidars, radars, cameras, computers, software and maps) market will reach $57 billion; the market value will more than triple by 2040, reaching $173 billion.

 

 

 

• Introduction to autonomous driving and the passenger car market landscape

• Who are the key players in the autonomous car ecosystem? What are the progresses in terms of AD development so far and what are their commercialisation plans?

• Key enabling technologies for autonomous cars: in-depth and comprehensive analysis of technology trends of lidar, radar, camera, AI software and computing platform, HD maps, cybersecurity, teleoperation, 5G and V2X

• How MaaS and AD technologies will shape the future travel landscape? And how AD-enabled MaaS will impact the passenger car market?

• Twenty-year market forecast for autonomous cars in both unit numbers and market value

 

This report provides a comprehensive view of all the enabling constituent technologies. In terms of radars, the report develops a comprehensive technology roadmap, examining the technology at the levels of materials, semiconductor technologies, packaging techniques, antenna array, and signal processing. It demonstrates how radar technology can evolve towards becoming a 4D imaging radar capable of providing a dense 4D point cloud that can enable object detection, classification, and tracking AI.

 

In terms of lidars, IDTechEx identified and analysed more than 100 players developing 3D lidars. This report examines all the technology options for the measurement process, light source, photodetector, and beam steering mechanisms. In case of the latter, it examines mechanical, MEMS/MOEMS, optical phase arrays, liquid crystal, 3D flash, and other technologies. The report examines the key players, categorising them by technology, investment, and geography. The report provides market share projections by lidar technology as well as price evolutions within the next decade.

 

In terms of cameras, the report first focuses on trends in global shutter (GS) CMOS image sensors. Here, we consider the key technology performance levels, pixel architectures, and latest innovations including back-side illuminated GS-CIS and organic and quantum dot hybrid GS-CIS. The report also examines means of boosting the NIR sensitivity of CMOS sensors. Finally, the report outlines and analyses existing and emerging technology options for SWIR sensing such as InGaAs, silicon (IPE process), quantum dots, and organics.

 

The report further examines non-hardware elements of autonomous driving. AI, the brain for autonomous cars, has been the major focus of autonomous driving efforts. Deep learning, which mimics neuron activity, supports functions like object recognition and classification, semantic segmentation, path planning in dynamic environments, and complex decision making and execution. Working together, these functions help vehicles understand its surroundings and make the right decisions. In this report, we provide an overview of different AI approaches for autonomous driving.

 

We also review the trends in HD mapping technology. Here, we discuss the progression of maps from ADAS map towards HD maps with many localization layers. We outline the key players and highlight the differences in approach towards collection, labelling and analyses of the data. In terms of teleoperation and cybersecurity, the report identities and overviews many of the key players worldwide. In the future, infrastructure could play a key role in accelerating the deployment of autonomous driving. This report examines how 5G enabled V2X technologies could support safer and more efficient autonomous driving systems.

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