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This report assesses the autonomous vehicle market including leading vendors, strategies, product and service offerings. The report evaluates autonomous vehicles by autonomy level, powertrain type, components, and supporting technologies. It also evaluates the impact of major technologies on autonomous vehicle markets such as 5G, AI, edge computing, IoT, data analytics, and smart building integration.
Select Report Findings:
- Key technology areas to leverage for service provider solutions include AI, 5G, and IoT
- 5G related software expenditures in support of autonomous vehicle solutions will reach $14.1 billion by 2028
- Edge computing infrastructure and services in support of autonomous vehicles will reach $53.9 billion by 2028
- Dedicated infrastructure for autonomous vehicles will serve as a proving ground for economic justification for autonomous vehicle ride-share and other green tech solutions
- Smart city market growth and innovation will be highly correlated with autonomous and connected vehicle technology funding, R&D and developments
- Driven by private and sovereign investment, certain countries outside the United States will witness surprisingly robust growth in autonomous vehicle deployments
The report provides global and regional forecasts for the autonomous vehicle market including hardware, software, and services along with emerging technologies from 2023 to 2028. The report covers major consumer and commercial categories including personal vehicles, shared vehicles (ridesharing and shared vehicles/partial ownership) and rentals. The report also evaluates autonomous control in ICE vehicles, EVs, and ICE/EV hybrids.
Autonomous Vehicle Disruption of the Automotive Industry Ecosystem
Autonomous vehicles are poised to invoke a revolution in the automobile industry including public transportation systems, car rental and sharing systems, vehicle leasing and ownership, industrial transportation, and automotive insurance practices and systems.
The extent of disruption will increase with the degree of vehicle autonomy, which is measured in levels from zero (fully human-operated) to five (fully automated system) with the evolution from levels 1 through 4 consisting of an autopilot system combined with some level of human control or intervention capability. Autonomous vehicles are anticipated to become the foundation of transportation as a service globally.
The automotive ecosystem is also faced with disruption from electric vehicles (EV), which has transformed supply chain economics at the vehicle component level as well as consumer value perception and lifecycle management. Improvements in battery cost/performance and reduction in the cost of power train components for EVs will lead to lower overall purchase cost that is more comparable with traditional internal combustion engine (ICE) vehicles.
The autonomous vehicle ecosystem will also be highly disruptive with respect to the consumer segment regarding the traditional production and sales cycle. This will be due largely to the vast amount of data produced by self-driving cars, vans, and trucks. The use of AI and big data analytics will allow both real-time decision-making as well as post-event analytics.
Autonomous Vehicle Growth Factors and Constraints
The autonomous vehicle market will grow rapidly during the remainder of this decade and will transform many industries including consumer mobility, commercial transport, industrial automation, smart cities, and transportation systems as a whole. There are many factors that will drive the growth and adoption of autonomous vehicles including cost reduction, safety improvements, and incremental advances in consumer perception.
For example, the U.S. Department of Transportation has moved forward with an Automated Vehicles Comprehensive Plan with the intention of establishing policies and regulations to ensure the safe and full integration of automated driving systems into the surface transportation system. The plan includes real-world examples of how policies and regulations will relate to emerging automated driving systems applications.
The United States is not alone in the push for a robust autonomous vehicle market. China and South Korea are two leading companies in the Asia Pacific region. For example, South Korea invested $1 billion in autonomous vehicle technology with a focus on technology and infrastructure development. Companies such as Hyundai and Samsung allow South Korea to implement vehicles more seamlessly with autonomous capabilities. South Korea desires to achieve the commercialization of level 4 autonomous vehicles by 2028.
In addition to overcoming public trust factors relative to safety, the autonomous vehicle market is also focused on the major consumer upsides to self-driving vehicles, which include less expensive transport, opportunities for ride-sharing and fractional ownership, and ultimately reduced outright leasing and ownership of cars, vans, and trucks. This is anticipated to have a major impact on OEMs and traditional automakers, despite the fact that market-leading automobile manufacturers are aggressively pursuing autonomous vehicle product offerings.
The above-mentioned market forces, availability of cost-effective and safe technology, and appropriate governmental oversight are all key factors coming together to enable a robust autonomous vehicle ecosystem. Accordingly, the autonomous vehicle market is beginning to move into the next market cycle beyond the early-adopter phase. The estimates indicate end-users will not fully embrace self-driving vehicles until the 2028 time frame.
The Juxtaposition of Fully Autonomous Vehicles, Connected Drivers and Passengers
Paradoxically, automotive vendors are also continuously upgrading their fleets to offer more connected vehicles, which provide drivers with a substantially more safe, enjoyable, and informative driving experience. However, autonomous vehicles are also connected via IoT technologies and various broadband and narrowband wireless solutions.
In the near future, the publisher anticipates that automobile vendors will offer next-generation connected vehicle apps to human occupants within autonomous vehicles that capitalize upon hands-free operation, and in some cases, offer fully immersive experiences for longer trips.
Autonomous Vehicles for Commercial Fleets and Other Business Operations
The evolution of self-driving vehicles for the fleet market will be human-controlled fleets to machine/human-controlled fleets to completely autonomous (e.g. machine-driven) vehicles that leverage various technologies including sensors, AI, cognitive computing, geo-fencing, GIS/mapping, and more. Ultimately, the market will achieve level 4 autonomy, which is similar to level 3, but the human behind the wheel is considered to be a “passenger” rather than a “driver.”
Market-leading autonomous vehicle use cases will be found primarily within the business realm with an emphasis on shipping and commercial fleets. Important within this segment is heavy haul trucking, which refers to the transport of oversize or overweight freight equipped with specialized trailers and transporting heavy equipment.
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Table of Contents
1. Executive Summary
Companies Mentioned
- AImotive
- Alibaba (SAIC Motors)
- Alphabet Inc. (Waymo)
- Amazon.com Inc.
- Apple Inc.
- APTIV
- Arbe Robotics
- Audi AG
- Aurora
- Autoliv Inc.
- Autotalks Ltd.
- Baidu Inc. (NIO)
- Beijing Trunk Tech Co. Ltd.
- Blackberry QNX
- BMW AG
- Cisco System Inc.
- Cognata
- Cohda Wireless
- Commsignia
- Continental AG
- Cruise LLC
- DAF Trucks
- Daimler AG (Mercedes Benz)
- Deep Vision
- Deepmap
- Deepscale
- DENSO Corporation
- Didi Chuxing Technology Co. Ltd.
- Fiat Chrysler Automobiles
- Ford Motor Company
- General Motors
- GrabTaxi Holdings Pte. Ltd.
- Groupe PSA
- Groupe Renault
- Hitachi
- Honda Motor Company Ltd.
- Huawei Technology Co. Ltd.
- Hyundai
- Idriverplus
- Innoviz Technologies
- Innovusion
- Intel Corporation (Mobileye)
- IVECO
- Jaguar Land Rover
- LeddarTech
- Lyft Inc.
- Magna International Inc.
- Metawave
- Microsoft Corporation
- Mighty AI
- Mitsubishi Motors Corporation
- Nikola Corporation
- Nissan Motor Corporation
- Nuro
- NVidia Corporation
- NXP Semiconductors NV
- PACCAR
- Panasonic Corporation
- Porsche AG
- Prophesee
- Robert Bosch GmbH
- Robosense
- Samsung Electronics Co. Ltd.
- Scania AB
- Telefonaktiebolaget LM Ericsson
- Tencent
- Tesla Inc.
- Toshiba
- Toyota Motor Corporation
- Uber Technologies Inc.
- Valeo
- Velodyne Lidar, Inc.
- Visteon
- Volkswagen AG
- Volvo Car Corporation
- Voyage
- WeRide
- Zenuity
- ZF Friedrichshafen
- Zhejiang Geely Holding Group
Methodology
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