全球自動駕駛 (AD) 產業的展望:2019年
Global Autonomous Driving (AD) Industry Outlook, 2019
|出版商||Frost & Sullivan||商品編碼||851172|
|出版日期||內容資訊||英文 62 Pages
|全球自動駕駛 (AD) 產業的展望:2019年 Global Autonomous Driving (AD) Industry Outlook, 2019|
|出版日期: 2019年05月09日||內容資訊: 英文 62 Pages||
本報告提供全球自動駕駛 (AD) 產業的展望調查，產業及技術定義和概要，主要趨勢與相關對市場的影響，案例研究，技術供應商、供應商、OEM的市場機會，企業及企業間的投資、聯盟等趨勢，市場規模的變化與預測，成長機會、成功策略分析等資料彙整。
1 in 4 Cars Sold (18 Million) Globally is Expected to be Automated (L3 and Above) by 2030, with L4 Driving the Growth of Ownership
The autonomous driving industry is evolving at a rapid pace on various fronts such as advancements in technology as well as emergence of new business models. Traditionally, most major OEMs and Tier I suppliers have strived to explore the benefits of developing applications focused on the convergence of the three technology pillars: Connected, Autonomous, and Electric. However, the true potential of each of these technology pillars can be tapped only by the marriage of technology and service sectors of the industry. Technology and service integration has picked up pace in the recent years, with leading OEMs making investments and acquisitions in service-based companies.
Technologically, 2018 witnessed advancements in shared mobility platform, consolidation of E/E architecture, and advancements in integration of AI in every aspect of autonomous development. In 2019, Frost & Sullivan expects sensor solutions and teleoperation to emerge as key developments, while on the business front, OEMs and Tier I companies to prioritize pushing L2+ features in the market.
In this 2019 outlook, Frost & Sullivan has highlighted 1 Mega Trend and 3 key sub trends in each of the market and technological advancements, which will be impacted by autonomous driving.
Market trends include mobility services, peripheral services, logistics services, and vehicle services. Impact of autonomy will change these traditional business models while focusing on ways to monetize and personalize data.
In terms of technology, trends include autonomous vehicle platforms, sensor fusion solutions, data computing and storage, and testing and validation. With the industry evolving from ADAS-level sensors, the focus will be on developing L4 and L5 autonomous platform and building the necessary computational ecosystem.
This study highlights these trends and explains the impact along with use cases.