세계의 운송용 양자 컴퓨팅 시장 평가 : 용도별, 구성요소별, 기술별, 최종사용자별, 지역별, 기회 및 예측(2018-2032년)

Global quantum computing in transportation market is projected to witness a CAGR of 19.56% during the forecast period 2025-2032, growing from USD 46.62 million in 2024 to USD 194.65 million in 2032F, owing to the pressing need for faster, more efficient supply chain operations. As logistics networks become increasingly complex, with dynamic routes, fluctuating demand, and time-sensitive deliveries, classical computing struggles to handle the sheer volume and variability of data. Quantum computing, with its unparalleled ability to process vast datasets and solve optimization problems exponentially faster than traditional systems, offers a compelling solution. The market is poised for substantial growth over the next decade, supported by advancements in quantum annealing, hybrid quantum-classical frameworks, and increased investments from both tech giants and logistics firms.

One of the most significant growth drivers are the increasing demand for real-time route optimization and predictive analytics in freight and warehousing. Major logistics companies are exploring quantum solutions to tackle last-mile delivery issues, warehouse inventory optimization, and cross-border freight coordination. Additionally, supportive government policies in regions such as North America, Europe, and parts of Asia, especially Japan and Singapore, are providing funding and infrastructure support to accelerate adoption. The integration of quantum computing through cloud-based platforms has also lowered entry barriers, allowing even mid-sized firms to experiment and prototype without heavy capital investment. However, the market is not without its restraints. High costs associated with quantum hardware, the lack of a skilled workforce, and the nascent stage of commercial quantum applications pose significant challenges. Moreover, issues related to error correction, algorithm stability, and hardware standardization continue to hamper scalability and broader deployment.

Unlike many other emerging technologies, quantum computing in logistics offers tangible, short-term use cases that directly impact cost-efficiency, sustainability, and customer satisfaction. With a growing number of successful pilot programs and strategic partnerships among quantum tech firms and logistics leaders, the market is expected to move from experimental to actionable much sooner than anticipated.

For instance, in April 2025, Quantum Computing Inc. (QCi), a leader in integrated photonics and quantum optics technology, announced the sale and shipment of its EmuCore reservoir computer to a prominent automotive manufacturer. The device will be utilized by the customer for research and development initiatives.

EmuCore, built on a field-programmable gate array (FPGA), offers a secure, flexible, and energy-efficient platform for leveraging machine learning in edge computing scenarios and validating processing workloads. This deployment allows the automotive manufacturer to explore advanced applications and serve as a testbed for QCi's upcoming PCIe-based photonic reservoir computing units, which are expected to deliver superior performance per watt in AI and sensor-intensive environments.

Advanced Optimisation for Complex Logistics Drives Market Growth

Quantum computing has emerged as a transformative force in optimization-heavy sectors such as transportation and logistics. These domains feature NP-hard problems, such as multivehicle routing, dynamic schedule adjustments, and cargo allocation, that classical systems struggle to solve efficiently at scale. Quantum annealing and hybrid quantum-classical methods can evaluate exponentially larger solution spaces in parallel.

For instance, in late 2024, D-Wave released a logistics-routing datasheet highlighting real-world deployments of its quantum annealer for vehicle routing across delivery networks, public transit, and tour vehicles. According to their findings, quantum-enabled routing reduced travel time and fuel consumption by analyzing complex, dynamic variables in real time. For example, D-Wave's annealer had been deployed to optimize driver scheduling and parcel-truck routing for Hermes Germany, coordinating trucks from 50 depots to 17,000 delivery points. This demonstrates immediate, practical gains: lower operational costs, shortened delivery times, and reduced environmental impact.

These implementations move quantum beyond theoretical promise to measurable efficiency, enabling transport operators to process dynamic constraints such as traffic delays or emergent disruptions on the fly. By handling large-scale route recalculations swiftly, quantum systems significantly enhance responsiveness in logistics chains. Quantum optimization in transportation is growing from pilot stages into early-stage rollouts, attracting interest from major LSPs (logistics service providers) and delivery firms, driving the global market demand.

Enhancing Resilience, Sustainability, And Emissions Reduction Leads Market Growth

Global transportation systems are facing mounting pressure to decarbonize and make more efficient use of resources. Governments and transit agencies are establishing net-zero targets, then tightening fuel-efficiency and congestion norms, usually. Also, simulation and optimization based on quantum computing could make a great impact on these goals.

For instance, the UK Department for Transport released a 2024 report, estimating that up to USD 10.24 billion in value can be opened by quantum-enabled traffic and route optimization by 2035, while emissions savings could contribute USD 3.58 billion annually in reduced congestion costs. The report also draws attention to dynamic route recalculation that is capable of constantly adjusting to the flow of traffic and a surge in demand, aligning directly with emissions reduction and operational resilience goals.

Quantum-enabled planning of bus, municipal or delivery routes that adapt to traffic and avoid road disruption even while idling away and returning. Fleet managers will be able to deploy cars more efficiently, reduce the amount of fuel they use, and lower the amount of greenhouse gases they emit. In addition, the UK plan merges with international governance frameworks, such as the UN's Paris Agreement, by harmonizing quantum technology's role in green transitions.

For this driver of change, which has implications reaching far beyond logistics as cities and countries scale up electrification, smart-transport infrastructure and EV fleet deployment, quantum optimization becomes a critical tool to keep service quality up and meet environmental goals. It is a key foundation stone of next-gen sustainable transport systems.

Dynamic Optimization of Urban Traffic Signals Drives Market Growth

Quantum computing, particularly quantum-inspired optimization, is beginning to redefine how cities manage urban traffic, with real-time control of signal timings becoming a key growth frontier. Unlike traditional systems that follow present signal patterns, quantum solutions can evaluate thousands of timing combinations across multiple intersections simultaneously and adapt on the fly. This enables smarter distribution of green-light intervals, reduction of congestion, and shorter wait times.

For instance, in October 2024, the Port of Hamburg deployed a quantum-inspired Digital Annealer system, known as the MOZART project, to optimize traffic light timings across a congested port area. In a pilot wrapped up, the system dynamically adjusted signal phases across multiple intersections in near real-time. Early results showed improved traffic flow and reduced idling times during peak periods, demonstrating how quantum-based optimization can enhance existing infrastructure without physical expansion.

North America leads the Global Quantum Computing in Transportation Market

North America currently dominates the global quantum computing in logistics market in terms of revenue, accounting for a major share, driven by strong government funding, technological leadership, and early adoption by logistics giants. The U.S. and Canada lead due to initiatives such as the U.S. National Quantum Initiative Act, which has allocated USD 1.2 billion for quantum R&D, and Canada's National Quantum Strategy, fostering public-private partnerships. Major tech firms such as IBM Quantum and D-Wave are headquartered in the region, collaborating with logistics players to test quantum solutions.

For instance, in 2024, Amazon.com, Inc. integrated quantum algorithms via AWS Braket to enhance warehouse automation. It includes features such as Robotic path planning for pick-and-place systems, real-time inventory slotting to reduce retrieval times and Predictive labor allocation using quantum machine learning.

Impact of the U.S. Tariff on Global Quantum Computing in Transportation Market

U.S. tariffs on imported semiconductors, superconducting materials, and specialized electronic components can raise the cost of manufacturing and scaling quantum hardware. This directly impacts companies that rely on global supply chains for essential quantum computing parts, slowing down production and increasing end-user pricing.

Tariffs can create trade tensions and restrict the smooth flow of quantum technology and knowledge across borders. This affects international research partnerships, joint ventures, and vendor relationships, especially when logistics players in tariff-targeted countries hesitate to adopt U.S. based solutions.

Quantum computing applications in logistics often rely on shared technological developments between the U.S. and other innovation hubs. Tariff impositions may slow the transfer of quantum-enabled logistics platforms globally, affecting implementation timelines and increasing regional disparities.

Key Players Landscape and Outlook

The competitive landscape of the global quantum computing in logistics market is characterized by a blend of established technology giants and emerging quantum-focused firms. Competition among top players primarily revolves around technological capability, qubit performance, error correction methods, algorithm efficiency, and scalability of quantum hardware and software platforms. Additionally, the ability to offer end-to-end solutions-including cloud-based quantum access, hybrid quantum-classical algorithms, and integration with existing logistics systems-plays a vital role in determining market positioning. Strategic collaborations, R&D investments, intellectual property strength, and partnerships with logistics providers are also key differentiators. The market outlook remains promising, with increasing interest from logistics companies seeking to leverage quantum computing for solving complex routing, supply chain optimization, and predictive analytics challenges. As quantum hardware matures and quantum-as-a-service models gain traction, competition is expected to intensify, leading to broader adoption and commercialization. However, market success will heavily depend on overcoming current technological constraints, regulatory clarity, and demonstrating real-world value across logistics functions.

In June 2025, at the 49th annual Honeywell Users Group event, Honeywell International Inc. introduced a new suite of digital technologies leveraging artificial intelligence, aimed at accelerating the transition from automation to autonomy in industrial sectors. Among the highlights were the launch of Honeywell Cyber Proactive Defense and the Honeywell OT Security Operations Center, AI-enabled cybersecurity solutions specifically designed to strengthen operational technology (OT) environments against increasingly sophisticated cyber threats. According to the company, these offerings help organizations minimize cyberattack risks, enhance resiliency, and ensure uninterrupted industrial operations.

Table of Contents

1. Project Scope and Definitions

2. Research Methodology

3. Impact of U.S. Tariffs

4. Executive Summary

5. Voice of Customers

• 5.1. Technical Expertise and Track Record
• 5.2. Application Fit and Use Case Relevance
• 5.3. Scalability and Hardware Readiness
• 5.4. Ecosystem and Partnerships

6. Global Quantum Computing in Transportation Market Outlook, 2018-2032F

• 6.1. Market Size Analysis & Forecast
  • 6.1.1. By Value
• 6.2. Market Share Analysis & Forecast
  • 6.2.1. By Application
    • 6.2.1.1. Traffic Management Systems
    • 6.2.1.2. Logistics Optimization
  • 6.2.2. By Component
    • 6.2.2.1. Hardware
    • 6.2.2.2. Software
    • 6.2.2.3. Services
  • 6.2.3. By Technology
    • 6.2.3.1. Quantum Annealing
    • 6.2.3.2. Quantum Gate Model
  • 6.2.4. By End-user
    • 6.2.4.1. Public Transportation
    • 6.2.4.2. Freight & Logistics
    • 6.2.4.3. Automotive
    • 6.2.4.4. Aerospace
    • 6.2.4.5. Others
  • 6.2.5. By Region
    • 6.2.5.1. North America
    • 6.2.5.2. Europe
    • 6.2.5.3. Asia-Pacific
    • 6.2.5.4. South America
    • 6.2.5.5. Middle East and Africa
  • 6.2.6. By Company Market Share Analysis (Top 5 Companies and Others - By Value, 2024)
• 6.3. Market Map Analysis, 2024
  • 6.3.1. By Application
  • 6.3.2. By Component
  • 6.3.3. By Technology
  • 6.3.4. By End-user
  • 6.3.5. By Region

7. North America Quantum Computing in Transportation Market Outlook, 2018-2032F

• 7.1. Market Size Analysis & Forecast
  • 7.1.1. By Value
• 7.2. Market Share Analysis & Forecast
  • 7.2.1. By Application
    • 7.2.1.1. Traffic Management Systems
    • 7.2.1.2. Logistics Optimization
  • 7.2.2. By Component
    • 7.2.2.1. Hardware
    • 7.2.2.2. Software
    • 7.2.2.3. Services
  • 7.2.3. By Technology
    • 7.2.3.1. Quantum Annealing
    • 7.2.3.2. Quantum Gate Model
  • 7.2.4. By End-user
    • 7.2.4.1. Public Transportation
    • 7.2.4.2. Freight and Logistics
    • 7.2.4.3. Automotive
    • 7.2.4.4. Aerospace
    • 7.2.4.5. Others
  • 7.2.5. By Country Share
    • 7.2.5.1. United States
    • 7.2.5.2. Canada
    • 7.2.5.3. Mexico
• 7.3. Country Market Assessment
  • 7.3.1. United States Quantum Computing in Transportation Market Outlook, 2018-2032F*
    • 7.3.1.1. Market Size Analysis & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share Analysis & Forecast
      • 7.3.1.2.1. By Application
        • 7.3.1.2.1.1. Traffic Management Systems,
        • 7.3.1.2.1.2. Logistics Optimization
      • 7.3.1.2.2. By Component
        • 7.3.1.2.2.1. Hardware
        • 7.3.1.2.2.2. Software
        • 7.3.1.2.2.3. Services
      • 7.3.1.2.3. By Technology
        • 7.3.1.2.3.1. Quantum Annealing
        • 7.3.1.2.3.2. Quantum Gate Model
      • 7.3.1.2.4. By End-user
        • 7.3.1.2.4.1. Public Transportation
        • 7.3.1.2.4.2. Freight and Logistics
        • 7.3.1.2.4.3. Automotive
        • 7.3.1.2.4.4. Aerospace
        • 7.3.1.2.4.5. Others
  • 7.3.2. Canada
  • 7.3.3. Mexico

All segments will be provided for all regions and countries covered

8. Europe Quantum Computing in Transportation Market Outlook, 2018-2032F

• 8.1. Germany
• 8.2. France
• 8.3. Italy
• 8.4. United Kingdom
• 8.5. Russia
• 8.6. Netherlands
• 8.7. Spain
• 8.8. Turkey
• 8.9. Poland

9. Asia-Pacific Quantum Computing in Transportation Market Outlook, 2018-2032F

• 9.1. India
• 9.2. China
• 9.3. Japan
• 9.4. Australia
• 9.5. Vietnam
• 9.6. South Korea
• 9.7. Indonesia
• 9.8. Philippines

10. South America Quantum Computing in Transportation Market Outlook, 2018-2032F

• 10.1. Brazil
• 10.2. Argentina

11. Middle East and Africa Quantum Computing in Transportation Market Outlook, 2018-2032F

• 11.1. Saudi Arabia
• 11.2. UAE
• 11.3. South Africa

12. Demand Supply Analysis

13. Value Chain Analysis

14. Porter's Five Forces Analysis

15. PESTLE Analysis

16. Market Dynamics

• 16.1. Market Drivers
• 16.2. Market Challenges

17. Market Trends and Developments

18. Policy and Regulatory Landscape

19. Case Studies

20. Competitive Landscape

• 20.1. Competition Matrix of Top 5 Market Leaders
• 20.2. SWOT Analysis for Top 5 Players
• 20.3. Key Players Landscape for Top 10 Market Players
  • 20.3.1. IBM Corporation
    • 20.3.1.1. Company Details
    • 20.3.1.2. Key Management Personnel
    • 20.3.1.3. Products and Services
    • 20.3.1.4. Financials (As Reported)
    • 20.3.1.5. Key Market Focus and Geographical Presence
    • 20.3.1.6. Recent Developments/Collaborations/Partnerships/Mergers and Acquisition
  • 20.3.2. Google LLC
  • 20.3.3. Microsoft Corporation
  • 20.3.4. Honeywell International Inc.
  • 20.3.5. Intel Corporation
  • 20.3.6. D-Wave Systems Inc.
  • 20.3.7. Quantinuum Ltd.
  • 20.3.8. Rigetti Computing
  • 20.3.9. Quantum Computing Inc.
  • 20.3.10. Xanadu Quantum Technologies Inc.

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.

21. Strategic Recommendations

22. About Us and Disclaimer