Global Edge Computing for Autonomous Vehicles Market - 2024-2031

Overview

Global Edge Computing for Autonomous Vehicles Market reached US$ 7.5 billion in 2023 and is expected to reach US$ 38.4 billion by 2031, growing with a CAGR of 22.65% during the forecast period 2024-2031.

Edge computing represents an emerging paradigm in computing that encompasses various networks and devices positioned at or near the user's location. This approach focuses on processing data closer to its source, thereby enabling faster and higher-volume data handling, which leads to more actionable, real-time insights. The future of autonomous vehicles integrated with edge computing holds tremendous potential for transforming the transportation industry.

Autonomous vehicles are already reshaping travel by enhancing safety, comfort and convenience. Edge computing, a technology that facilitates local data processing and analysis directly on the device or at the network edge rather than in the cloud, introduces a new level of efficiency and speed to autonomous vehicle operations. By significantly reducing latency, bandwidth usage and data storage requirements, edge computing allows autonomous vehicles to operate more effectively and cost-efficiently.

Consequently, the convergence of autonomous vehicles and edge computing heralds a future of safer, more accessible and sustainable transportation. In this context, edge computing is poised to play a pivotal role in revolutionizing travel, solidifying its status as a critical technology for the advancement of autonomous vehicles. In November 2022, NVIDIA introduced DRIVE Thor, a centralized automotive computer that unifies functions such as clustering, infotainment, automated driving and parking into a single, cost-effective system.

Dynamics

MEC-Enabled Applications

The incorporation of Mobile Edge Computing (MEC) into autonomous vehicles is progressing swiftly, improving vehicle efficiency and facilitating new services. Organizations such as the Automotive Edge Computing Consortium (AECC) play a crucial role in advancing these innovations, advocating for the implementation of MEC in intelligent driving solutions.

Researchers anticipate that MEC will facilitate real-time data-driven applications, like dynamic mapping and driver assistance systems, supported by cloud computing. For these technologies to thrive, vehicles must be linked to high-capacity networks capable of sending substantial data quantities, ensuring uninterrupted functionality. MEC also enables the shift to mobility-as-a-service by converting each vehicle into a data repository. This creates chances for external services such as navigation assistance, ride-sharing and traffic control systems.

Moreover, vehicle edge computing may enhance the finance and insurance industries by enabling insurers to provide usage-based coverage through real-time monitoring of driving behavior. Diverse connectivity choices, such as cellular, Wi-Fi and low-power wide-area (LPWA) networks, will link automobiles to distributed computing platforms, thereby enhancing service offerings and operating efficiency.

Impact of 5G on Enhancing Efficiency and Connectivity

5G technology is poised to markedly improve edge computing capabilities for autonomous vehicles by delivering the necessary bandwidth, low latency and dependability for connected-car applications. Enhanced mobile broadband (EMBB) allows 5G to deliver speeds of up to 10 gigabits per second, which is five to ten times faster than 4G technology, facilitating high-bandwidth applications such as in-car infotainment, vehicle teleoperation and real-time human-machine interface rendering.

Moreover, 5G's extensive IoT capabilities facilitate up to one million connections per square kilometer, guaranteeing that numerous cars and interconnected infrastructure can function smoothly without network congestion or interruptions. The ultra-low-latency communications (URLLC) provided by 5G, with latency potentially reaching one millisecond-five to fifteen times superior than 4G-are essential for real-time vehicle operations, including object tracking and intelligent traffic management. This low-latency, high-reliability connection facilitates the transfer of non-safety-critical workloads, including infotainment and traffic control, from onboard systems or the cloud to the edge

High Implementing Cost

Establishing and implementing edge computing systems necessitates sophisticated gear, including high-performance CPUs, sensors and data storage solutions, which can be costly. Furthermore, the necessity for a resilient connectivity infrastructure, encompassing 5G networks, to facilitate real-time data processing contributes to the total expenditure. Significant initial investments might pose a challenge, especially for smaller automakers and technology providers who may find it difficult to validate the financial commitment necessary for extensive implementation.

Additionally, continuous maintenance and enhancements to edge computing systems escalate operational expenses. As technology advances swiftly, the necessity for ongoing enhancements and the incorporation of novel functionalities may escalate the long-term expenses of edge computing. This financial encumbrance is an obstacle for wider adoption, as companies must evaluate the expense of installation relative to the prospective advantages of enhanced vehicle autonomy and performance. Thus, the elevated expenses continue to be a significant impediment to the expansion of edge computing within the autonomous car industry.

Segment Analysis

The global edge computing for autonomous vehicles market is segmented based on component, deployment, connectivity, vehicle, application, end-user and region.

Real-Time Data Processing And Decision-Making in Passenger Vehicles

Edge computing facilitates local data processing within the vehicle, hence diminishing latency and enabling autonomous vehicles to make swifter, more precise judgments. This leads to improved navigation, superior obstacle recognition and enhanced traffic management, all of which augment safety and efficiency on the roadways. Edge computing enables vehicles to communicate with one another and with surrounding infrastructure, thereby augmenting situational awareness and mitigating accidents.

Besides enhancing safety, edge computing diminishes dependence on cloud systems, thereby reducing bandwidth consumption, data storage expenses and the risk of network interruptions. This enables autonomous vehicles to function more efficiently and economically, especially in regions with inadequate network connectivity. With the expansion of the autonomous vehicle market, edge computing will be essential for facilitating advanced functionalities such as predictive maintenance, tailored services and enhanced traffic management, rendering it a pivotal technology for the future of transportation.

Geographical Penetration

Rising Edge Computing In North America

The growing use of IoT devices, the increased need for low-latency processing and the development of 5G technology are all contributing to the notable rise of the edge computing industry in autonomous vehicles in North America. To enable autonomous vehicle applications that need real-time data processing for navigation, safety and operational efficiency, major industry participants are making significant investments in edge computing infrastructure.

North America's dominance in this market is further supported by the region's well-established technology hubs and robust edge computing ecosystem. North America is in a strong position to maintain its leadership in the global edge computing market for autonomous vehicles because to ongoing investments in edge infrastructure and collaborations to support creative use cases.

Competitive Landscape

The major global players in the market include NVIDIA Corporation, Intel Corporation (Mobileye), Qualcomm Technologies, Inc., Tesla, Baidu Apollo, Bosch, Huawei, Waymo (Alphabet Inc.), Amazon Web Services (AWS) and Microsoft (Azure).

Russia-Ukraine War Impact Analysis

Cyberattacks on Ukraine's digital infrastructure exposed weaknesses while simultaneously fostering breakthroughs in digital resilience, resulting in increased dependence on cloud-based systems for uninterrupted operation. The modifications have influenced edge computing, as organizations seek to provide real-time processing in autonomous vehicles via cloud integration and enhanced cybersecurity measures.

The battle has highlighted the necessity for resilient digital infrastructure, becoming edge computing a crucial component in the technological framework of autonomous vehicle development. It has expedited the transition to cloud computing, which has directly impacted the development of edge computing in autonomous vehicles. In their pursuit of developing more robust systems, particularly in edge computing organizations in North America and beyond have drawn insights from the infrastructure assaults in Ukraine to enhance the design of secure and adaptive technology.

In this context, edge computing is essential for facilitating low-latency processing and secure data transfer for autonomous cars, as the demand for real-time decision-making and operational efficiency increases. The conflict has influenced global technology firms and digital geopolitics, prompting heightened investments in solutions that guarantee digital sovereignty and safe operational continuity, hence enhancing the edge computing ecosystem for autonomous vehicles.

Component

• Hardware
• Software
• Services

Deployment

• On-Premises
• Cloud-Based
• Hybrid

Connectivity

• 5G
• 4G/LTE
• Wi-Fi
• DSRC

Vehicle

• Passenger Vehicles
• Commercial Vehicles

Application

• Autonomous Driving
• Predictive Maintenance
• Vehicle Telematics
• Traffic Management
• Fleet Management
• Infotainment and Digital Cockpits
• Others

End-User

• OEMs
• Tier 1 Suppliers
• Fleet Operators
• Others

By Region

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Rest of Europe
• South America
  • Brazil
  • Argentina
  • Rest of South America
• Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • Rest of Asia-Pacific
• Middle East and Africa

Key Developments

• In January 2023, Belden launched its Single Pair Ethernet (SPE) family of connectivity products aimed at enhancing Ethernet connectivity in challenging settings, such as industrial and transportation sectors. The SPE range comprises IP20-rated PCB jacks, patch cords and cord sets for clean-area connections, as well as IP65/IP67-rated circular M8/M12 patch cables, cord sets and receptacles for dependable industrial Ethernet connections to field devices.
• In February 2023, Digi International made an announcement. The Digi IX10 cellular router, debuting at DistribuTECH 2023, enhances its portfolio of private cellular network (PCN) solutions, providing essential connectivity for smart grid devices via the CBRS shared spectrum and Anterix Band 8 900 MHz licensed spectrum.
• In March 2022, Cisco announced a collaboration with Verizon, showcasing a successful proof-of-concept demonstration in Las Vegas that illustrated how cellular and mobile edge computing (MEC) technology can enable autonomous driving solutions without the necessity of costly physical roadside units to enhance the radio signal.

Why Purchase the Report?

• To visualize the global edge computing for autonomous vehicles market segmentation based on component, deployment, connectivity, vehicle, application, end-user and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of the edge computing for autonomous vehicles market-level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.

The global edge computing for autonomous vehicles market report would provide approximately 86 tables, 86 figures and 212 pages.

Target Audience 2024

• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies