글로벌 로봇 자동차 및 트럭 시장 규모, 점유율 및 추세 분석 보고서 – 산업 개요 및 2031년까지의 예측

로봇 자동차 및 트럭 시장 분석

로봇 자동차와 트럭 시장은 기술 발전과 자율 주행 운송 솔루션에 대한 수요 증가에 힘입어 상당한 성장을 경험하고 있습니다. 인공 지능 , 머신 러닝, 센서 기술에 대한 투자가 급증하면서 자율 주행 차량 개발이 가속화되고 있습니다. 시장 확장에 기여하는 주요 요인에는 운송의 안전성, 효율성, 편의성 향상의 필요성이 포함됩니다. 자율 주행 차량은 인적 오류 감소, 사고율 감소, 교통 관리 최적화를 약속하여 소비자와 기업 모두에게 매력적입니다. 시장은 승용차와 상용 트럭을 포함한 다양한 유형으로 세분화됩니다. 고급 운전자 지원 시스템(ADAS)과 완전 자율 주행 기능이 장착된 승용차는 혁신적이고 편리한 운송 옵션을 찾는 소비자들에게 인기를 얻고 있습니다.         

로봇 자동차 및 트럭 시장 규모

글로벌 로봇 자동차 및 트럭 시장 규모는 2023년에 8억 9,114만 달러로 평가되었으며, 2031년까지 1억 9,514만 달러에 도달할 것으로 예상되며, 2024년에서 2031년까지의 예측 기간 동안 CAGR은 10.32%입니다. Data Bridge Market Research 팀이 큐레이팅한 시장 보고서에는 시장 가치, 성장률, 시장 세그먼트, 지리적 범위, 시장 참여자, 시장 시나리오와 같은 시장 통찰력 외에도 심층적인 전문가 분석, 수입/수출 분석, 가격 분석, 생산 소비 분석, 페슬 분석이 포함되어 있습니다.

로봇 자동차 및 트럭 시장 동향

“상업용 애플리케이션의 성장”

The growth of autonomous trucks in the freight and logistics sector is poised to drive significant market expansion and revolutionize supply chain operations. As companies increasingly adopt self-driving trucks, they benefit from enhanced efficiency and cost savings in logistics. Autonomous trucks can operate around the clock without the need for driver breaks, leading to more streamlined and continuous freight operations. This capability allows for faster and more reliable deliveries, which is crucial in meeting the growing demand for timely and flexible supply chain solutions. Additionally, the integration of autonomous technology into logistics helps reduce human error, lower operational costs, and improve overall safety on the roads. The market for autonomous trucks is expected to see substantial growth as businesses recognize these benefits and invest in the technology to stay competitive. This shift not only transforms traditional logistics practices but also contributes to the broader trend of automation and digitalization within the transportation industry.

Report Scope and Market Segmentation       

Robot Cars and Trucks Market Definition

Robot cars and trucks refer to autonomous or self-driving vehicles that operate without human intervention. These vehicles use a combination of sensors, cameras, artificial intelligence (AI), and machine learning to navigate and control the vehicle, allowing them to make decisions and respond to their environment in real time.

Robot Cars and Trucks Market Dynamics

Drivers  

• Enhanced Efficiency and Cost Savings Autonomous Vehicles

Self-driving trucks and cars have the potential to significantly enhance efficiency and reduce costs in the transportation and logistics sectors. By utilizing advanced algorithms and real-time data, these autonomous vehicles can optimize routes to avoid traffic congestion and minimize travel time. This results in lower fuel consumption and reduced operational costs. Additionally, the precision of autonomous systems allows for more efficient driving patterns, further decreasing fuel usage and maintenance needs. The cumulative effect of these efficiencies translates into substantial cost savings for businesses, making autonomous vehicles a compelling option for companies aiming to streamline their logistics and reduce their overall transportation expenses.

• Convenience-Driven Adoption of Autonomous Vehicles

The appeal of autonomous vehicles is largely driven by the demand for greater convenience in transportation. Features such as hands-free driving and automated parking address common pain points for consumers, providing a smoother and more enjoyable driving experience. The ability to handle routine tasks without human intervention reduces the stress associated with driving, particularly in urban environments with heavy traffic. Furthermore, autonomous vehicles can offer additional conveniences such as real-time traffic updates and personalized route recommendations. As consumers increasingly seek out technology that simplifies their lives, the convenience offered by self-driving cars is a significant factor driving their adoption and market growth.

Opportunities

• Advancements in AI and Machine Learning

Advancements in artificial intelligence (AI) and machine learning are crucial to the evolution of autonomous vehicles. Continued progress in these fields enhances the vehicles' ability to process and interpret vast amounts of data from sensors and cameras. Improved algorithms enable better decision-making and more accurate predictions, which are essential for navigating complex driving environments and adapting to dynamic road conditions. As AI and machine learning technologies advance, autonomous vehicles will become more adept at handling a wider range of driving scenarios, improving safety, reliability, and overall performance. This ongoing innovation is a key driver of market growth and a factor that will shape the future capabilities of autonomous transportation.

• Integration with Ride-Sharing Services

Autonomous vehicles can enhance the efficiency of ride-sharing services by providing a cost-effective solution for transporting passengers without the need for a human driver. This integration can lead to reduced operational costs for ride-sharing companies and lower fares for consumers. Furthermore, autonomous vehicles can improve the availability and accessibility of ride-sharing services, offering a more convenient and reliable transportation option. As the ride-sharing market continues to grow, the adoption of autonomous vehicles is expected to play a pivotal role in shaping the future of urban mobility and transportation services. The rise of ride-sharing platforms presents significant opportunities for the integration of autonomous vehicles.

Restraints/Challenges

• High Development Costs

One of the primary barriers to the widespread adoption of autonomous vehicles is the high development costs associated with their research, development, and testing. The creation of reliable and safe self-driving technology requires significant investment in advanced sensors, software development, and rigorous testing procedures. These costs can be prohibitive for new entrants and smaller companies, limiting their ability to compete in the market. Additionally, the long timeline required to bring autonomous vehicles from concept to market-ready products further compounds the financial challenges.    

• Technological Limitations

Despite the rapid progress in autonomous vehicle technology, current systems still face limitations in handling complex driving environments and unpredictable road conditions. Challenges such as navigating through heavy rain, fog, or snow, and managing interactions with unpredictable human drivers and pedestrians can affect the performance of autonomous vehicles. Additionally, the ability of these systems to process and respond to unusual or unexpected situations is still a developing area. These technological limitations can impact the reliability and safety of self-driving vehicles, hindering their widespread adoption.

This market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Global Robot Cars and Trucks Market Scope

The market is segmented on the basis of vehicle type, classification, technology, and application. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Vehicle Type

• Heavy Commercial Vehicles
• Light Commercial Vehicles
• Passenger Vehicles

Classification

• Level 0
• Level 1
• Level 2
• Level 3
• Level 4
• Level 5

Technology

• Simultaneous Localization and Mapping
• Real-Time Locating System

Application

• Domestic
• Commercial
• Industrial

Global Robot Cars and Trucks Market Regional Analysis

The market is analyzed and market size insights and trends are provided by country, vehicle type, classification, technology, and application as referenced above.

The countries covered in the market are U.S., Canada, Mexico, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, rest of Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, rest of Asia-Pacific, Saudi Arabia, U.A.E., South Africa, Egypt, Israel, rest of Middle East and Africa, Brazil, Argentina, and rest of South America.

Asia-Pacific is expected to dominate the market due to the presence of highly advanced countries like Japan, South Korea, and China, which are at the forefront of robotics and automation technologies. These nations have made significant investments in autonomous vehicle development, leveraging their strong technological capabilities and innovation-driven environments. The region's dominance is further supported by the increasing adoption of autonomous vehicles for both passenger and commercial applications, driven by the growing demand for efficient transportation solutions and smart city infrastructure.

Europe is expected to be the fastest growing due to significant advancements in autonomous vehicle technology, strong support from regulatory frameworks, and an increasing focus on sustainable and smart transportation solutions.  

보고서의 국가 섹션은 또한 개별 시장 영향 요인과 국내 시장의 현재 및 미래 트렌드에 영향을 미치는 규제 변화를 제공합니다. 다운스트림 및 업스트림 가치 사슬 분석, 기술 트렌드 및 포터의 5가지 힘 분석, 사례 연구와 같은 데이터 포인트는 개별 국가의 시장 시나리오를 예측하는 데 사용되는 몇 가지 포인터입니다. 또한 글로벌 브랜드의 존재 및 가용성과 지역 및 국내 브랜드와의 대규모 또는 희소한 경쟁으로 인해 직면한 과제, 국내 관세 및 무역 경로의 영향은 국가 데이터에 대한 예측 분석을 제공하는 동안 고려됩니다.

글로벌 로봇 자동차 및 트럭 시장 점유율

시장 경쟁 구도는 경쟁자에 대한 세부 정보를 제공합니다. 포함된 세부 정보는 회사 개요, 회사 재무, 창출된 수익, 시장 잠재력, 연구 개발 투자, 새로운 시장 이니셔티브, 글로벌 입지, 생산 현장 및 시설, 생산 용량, 회사의 강점과 약점, 제품 출시, 제품 폭과 범위, 애플리케이션 우세입니다. 위에 제공된 데이터 포인트는 시장과 관련된 회사의 초점에만 관련이 있습니다.

시장에서 운영되는 로봇 자동차 및 트럭 시장 리더는 다음과 같습니다.

• Bayerische Motoren Werke AG (독일)
• 포드 자동차 회사(미국)
• 토요타 자동차 주식회사(일본)
• 제너럴 모터스(미국)
• 메르세데스-벤츠(독일)
• 테슬라(미국)
• 폭스바겐(독일)
• IBM(미국)
• 카이로스 오토노미(미국)
• AUDI AG. (독일)
• Continental AG(독일)
• DENSO CORPORATION. (일본)
• Aptiv. (아일랜드)
• 웨이모 LLC(미국)
• PACCAR Inc. (미국)
• 엔비디아 코퍼레이션(미국)
• ZF 프리드리히스하펜 AG(독일)
• AB 볼보(스웨덴)
• 로버트 보쉬 GmbH (독일)
• 후지전기 주식회사(일본)
• 구글(미국)
• 닛산 자동차 주식회사(일본)
• 콩스베르그(노르웨이)
• FCA US LLC.(미국)
• 포르쉐 인디아(독일)

로봇 자동차 및 트럭 시장의 최신 동향

• 2024년 5월, Volvo Autonomous Solutions는 최초의 양산형 자율 주행 트럭을 출시하여 라스베이거스에서 열린 ACT Expo에서 선보였습니다. VNS Autonomous Truck은 Volvo의 상용차 전문성과 Aurora Innovation Inc에서 개발한 자율 주행 기술을 결합했습니다.   
• 2023년 12월, 트럭 운송 및 국방 분야를 위한 자율주행 기술의 저명한 개발사인 Kodiak Robotics, Inc.는 미국 국방부(DoD)에 맞춰 제작된 최초의 자율 주행 테스트 차량을 공개했습니다. Kodiak Driver라는 Kodiak의 자율 시스템으로 개조된 Ford F-150인 이 차량은 군용 지상 차량으로 작동하는 데 필요한 하드웨어와 소프트웨어를 모두 갖추고 있습니다.    
• 2023년 12월, ABB는 볼보 자동차와의 오랜 파트너십을 확대하여 차세대 전기 자동차 생산을 위한 1,300대 이상의 로봇과 기능 패키지를 공급하기로 약속했습니다. 이 이니셔티브는 볼보의 야심찬 지속 가능성 목표를 지원하는 것을 목표로 합니다.

SKU-61658