Autonomous Vehicles - Thematic Research
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Autonomous Vehicles - Thematic Research
Summary
This report focuses on autonomous vehicles (AVs) - one of the four disruptive megatrends currently impacting the automotive industry.
Autonomous vehicles exist in a number of forms, from models on sale today that control the speed and steering with continuous oversight from a human driver, to fully self-driving pods with no human controls, which are currently in development.
Creating vehicles that can safely drive themselves with no oversight from humans has proven to be incredibly difficult. The complexity has pushed back optimistic deadlines for the deployment of higher-level AVs - expected to form the basis of highly profitable robotaxi networks - leading to pressure within the sector as companies burn through capital with little to show for their efforts.
We highlight key developments within the AV theme, along with its top mergers and acquisitions, and a timeline of past and future milestones. The report also features GlobalData forecast data for AV market size, including a breakdown by SAE autonomy level. Finally, in the companies section, we look at the most important players in the AV field and their key moves in the sector.
This report looks at the emerging trends in Autonomous Vehicles in the automotive sector.
Scope
- The promise of autonomous vehicles is great - they could bring mobility to sections of the market that have never before had access such as children, disabled or those otherwise unable to drive themselves. In addition, they could enable a brace of new businesses in the commercial space such as ridehail services using robotaxis, on-demand freight logistics services, or mobile retail and service spaces that can be brought directly to the customer.
- However, the challenge of commercializing autonomous vehicles has proven equally great. The leap taken from SAE level 1 autonomy to level 2, for example, is small compared to the jump in complexity needed for level 3 eyes-off AV operation. These systems look laughably simple, however, compared to the level of complexity that will be demanded by truly self-driving level 4 and level 5 models, which might not even include controls for human drivers.
- As AVs develop, consolidation is likely within the sector, with smaller players either absorbed or pushed out by the companies that crack the secret to success with self-driving vehicles. Whether that is the sci-fi vision of a network of self-driving pods that whisk any user to any destination with just a tap on a smart device? Or will a more gradual approach focused on smaller, more attainable goals such as trucks using partial autonomy on highways to increase the efficiency of freight logistics, prove to be a more viable strategy?
- This report is part of our ecosystem of thematic investment research reports, supported by our thematic engine.
- GlobalData has developed a unique thematic methodology for valuing technology, media and telecom companies based on their relative strength in the big investment themes that are impacting their industry. Whilst most investment research is underpinned by backwards looking company valuation models, GlobalDatas thematic methodology identifies which companies are best placed to succeed in a future filled with multiple disruptive threats. To do this, GlobalData tracks the performance of the top 600 technology, media and telecom stocks against the 50 most important themes driving their earnings, generating 30,000 thematic scores.
- The algorithms in GlobalDatas thematic engine help to clearly identify the winners and losers within the TMT sector. Our 600 TMT stocks are categorised into 18 sectors. Each sector scorecard has a thematic screen, a risk screen and a valuation screen. Our thematic research ecosystem has a three-tiered reporting structure: single theme, multi-theme and sector scorecard. This report is a Multi-Theme report, covering all stocks, all sectors and all themes, giving readers a strong sense of how everything fits together and how conflicting themes might interact with one another.
Reasons to Buy
- Understand the impact autonomous vehicles are having in the automotive space. Identify the emerging trends in autonomous vehicles and how these developments might advance in the future. Learn about key use cases where autonomous vehicles may soon achieve profitability. View GlobalData forecasts for the sector.
- GlobalDatas thematic research ecosystem is a single, integrated global research platform that provides an easy-to-use framework for tracking all themes across all companies in all sectors. It has a proven track record of identifying the important themes early, enabling companies to make the right investments ahead of the competition, and secure that all-important competitive advantage.
Summary
This report focuses on autonomous vehicles (AVs) - one of the four disruptive megatrends currently impacting the automotive industry.
Autonomous vehicles exist in a number of forms, from models on sale today that control the speed and steering with continuous oversight from a human driver, to fully self-driving pods with no human controls, which are currently in development.
Creating vehicles that can safely drive themselves with no oversight from humans has proven to be incredibly difficult. The complexity has pushed back optimistic deadlines for the deployment of higher-level AVs - expected to form the basis of highly profitable robotaxi networks - leading to pressure within the sector as companies burn through capital with little to show for their efforts.
We highlight key developments within the AV theme, along with its top mergers and acquisitions, and a timeline of past and future milestones. The report also features GlobalData forecast data for AV market size, including a breakdown by SAE autonomy level. Finally, in the companies section, we look at the most important players in the AV field and their key moves in the sector.
This report looks at the emerging trends in Autonomous Vehicles in the automotive sector.
Scope
- The promise of autonomous vehicles is great - they could bring mobility to sections of the market that have never before had access such as children, disabled or those otherwise unable to drive themselves. In addition, they could enable a brace of new businesses in the commercial space such as ridehail services using robotaxis, on-demand freight logistics services, or mobile retail and service spaces that can be brought directly to the customer.
- However, the challenge of commercializing autonomous vehicles has proven equally great. The leap taken from SAE level 1 autonomy to level 2, for example, is small compared to the jump in complexity needed for level 3 eyes-off AV operation. These systems look laughably simple, however, compared to the level of complexity that will be demanded by truly self-driving level 4 and level 5 models, which might not even include controls for human drivers.
- As AVs develop, consolidation is likely within the sector, with smaller players either absorbed or pushed out by the companies that crack the secret to success with self-driving vehicles. Whether that is the sci-fi vision of a network of self-driving pods that whisk any user to any destination with just a tap on a smart device? Or will a more gradual approach focused on smaller, more attainable goals such as trucks using partial autonomy on highways to increase the efficiency of freight logistics, prove to be a more viable strategy?
- This report is part of our ecosystem of thematic investment research reports, supported by our thematic engine.
- GlobalData has developed a unique thematic methodology for valuing technology, media and telecom companies based on their relative strength in the big investment themes that are impacting their industry. Whilst most investment research is underpinned by backwards looking company valuation models, GlobalDatas thematic methodology identifies which companies are best placed to succeed in a future filled with multiple disruptive threats. To do this, GlobalData tracks the performance of the top 600 technology, media and telecom stocks against the 50 most important themes driving their earnings, generating 30,000 thematic scores.
- The algorithms in GlobalDatas thematic engine help to clearly identify the winners and losers within the TMT sector. Our 600 TMT stocks are categorised into 18 sectors. Each sector scorecard has a thematic screen, a risk screen and a valuation screen. Our thematic research ecosystem has a three-tiered reporting structure: single theme, multi-theme and sector scorecard. This report is a Multi-Theme report, covering all stocks, all sectors and all themes, giving readers a strong sense of how everything fits together and how conflicting themes might interact with one another.
Reasons to Buy
- Understand the impact autonomous vehicles are having in the automotive space. Identify the emerging trends in autonomous vehicles and how these developments might advance in the future. Learn about key use cases where autonomous vehicles may soon achieve profitability. View GlobalData forecasts for the sector.
- GlobalDatas thematic research ecosystem is a single, integrated global research platform that provides an easy-to-use framework for tracking all themes across all companies in all sectors. It has a proven track record of identifying the important themes early, enabling companies to make the right investments ahead of the competition, and secure that all-important competitive advantage.
TABLE OF CONTENTS
Table of Contents
Executive summary
Players
Reality check for autonomous vehicles
Autonomous vehicles in a post-COVID-19 world
Regulations governing AVs are set to tighten
Technology briefing
Trends
Industry analysis
Mergers and acquisitions
Timeline
Value chain
Companies
Sector scorecards
Further reading
Our thematic research methodology
Executive summary
Players
Reality check for autonomous vehicles
Autonomous vehicles in a post-COVID-19 world
Regulations governing AVs are set to tighten
Technology briefing
Trends
Industry analysis
Mergers and acquisitions
Timeline
Value chain
Companies
Sector scorecards
Further reading
Our thematic research methodology
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