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市場調查報告書
商品編碼
1494738
到 2030 年自動駕駛汽車市場預測:按組件、自動化程度、車輛類型、技術、應用和地區進行的全球分析Autonomous Vehicles Market Forecasts to 2030 - Global Analysis By Component, Automation Level, Vehicle Type, Technology, Application and By Geography |
根據Stratistics MRC預測,2024年全球自動駕駛汽車市場規模將達到608億美元,預計2030年將達到1,806億美元,預測期內複合年成長率為19.9%。
自動駕駛汽車通常被稱為自動駕駛汽車或無人駕駛汽車,是配備先進感測器、軟體和人工智慧 (AI) 演算法的車輛,無需人工干預即可導航和操作。這些車輛可以感知環境、解釋感測資料並做出決策,自動駕駛道路、避開障礙物並遵守交通法規。自動駕駛汽車有潛力透過提高安全性、效率和可及性來徹底改變交通運輸。它有望減少人為失誤造成的交通事故,最佳化交通流量,並為因年齡、殘疾或其他因素而無法駕駛的人提供出行解決方案。
根據汽車業資訊領先者Automotive World預測,到2050年,全球汽車保有量將普及20億輛。根據美國環保署 (EPA) 的數據,美國75% 以上的一氧化碳是由汽車排放的。
出行即服務的興起
MaaS 將各種交通服務整合到一個統一平台中,使用戶能夠無縫存取各種移動選項,包括自動駕駛汽車。將自動駕駛技術納入 MaaS 網路將使這項技術在消費者中得到更廣泛的了解和接受。 MaaS 平台最佳化了 AV 使用、減少了停機時間並提高了營運效率。此外,MaaS 的資料驅動性質允許不斷改進 AV 演算法,並透過即時監控和分析來提高安全性。
責任和法律問題
由於不確定誰將在涉及自動駕駛車輛的事故中負責,保險和法律體制變得複雜。製造商、軟體開發商甚至車主都可能被追究責任,從而形成一個複雜的法律糾葛網路。然而,不同司法管轄區的法規會進一步加劇這個問題,並阻礙自動駕駛汽車的普及和採用。這些因素阻礙了市場的成長。
越來越關注商業應用
物流、運輸和送貨服務等商業部門正在認知到自動駕駛汽車在簡化業務、降低成本和提高效率方面的潛力。該公司正在大力投資研發,將自動駕駛技術整合到他們的車輛中,並尋求利用其優勢。商業實體日益成長的興趣正在刺激技術創新,從而推動自動駕駛汽車功能、安全功能和基礎設施支援的進步。此外,商業應用需要擴充性和可靠性,迫使製造商改進自動駕駛系統以滿足嚴格的行業標準。
資料安全問題
資料安全問題是自動駕駛汽車市場進步的主要障礙。自動駕駛汽車整合了先進的感測器、攝影機和連接功能,可產生大量資料,包括有關乘客、路線和位置的敏感資訊。這些資料很容易受到駭客攻擊、資料外洩和未授權存取等網路威脅。然而,人們擔心這些資料可能被濫用,包括身分盜竊、監視和操縱車輛功能,削弱了消費者對自動駕駛汽車的信任和信心。
最初,疫情擾亂了供應鏈,導致生產延誤,並阻礙了自動駕駛汽車的部署。社交距離措施和關門減少了對乘車服務的需求,影響了自動駕駛汽車的測試和部署。然而,疫情凸顯了安全和衛生的重要性,並促使人們關注開發用於大眾交通工具和共用出行服務的自動駕駛技術。
駕駛輔助產業預計在預測期內規模最大
駕駛員援助細分市場預計將成為預測期內最大的細分市場,駕駛員援助系統將透過整合主動式車距維持定速系統巡航控制、車道維持援助和自動緊急煞車等功能擴展到半自動駕駛功能,從而提高安全性和安全性。自動駕駛技術正在贏得消費者和監管機構的認可和信任,因為這些技術可以減少人為錯誤、減少事故並改善信任流。
預計共乘產業在預測期內將經歷最高的複合年成長率。
透過為此技術的採用和融入日常生活提供自然途徑,預計乘車共享產業在預測期內將出現最高的複合年成長率。共乘公司處於將自動駕駛汽車整合到車隊中的最前沿,以降低營運成本、提高效率並增強客戶體驗。透過利用自動駕駛技術,共乘服務可以為客戶提供更低的票價,同時保持盈利。此外,這些服務是自動駕駛汽車系統的重要測試場,使開發人員能夠收集真實世界的資料並在不同的城市環境中完善其技術。
在估計期間,亞太地區佔據了最大的市場佔有率。該地區的成長得益於將最尖端科技融入交通系統,例如 5G 網路、物聯網 (IoT) 感測器和人工智慧。增強的連接性將實現車輛、基礎設施和其他智慧設備之間的無縫通訊,從而促進全部區域更安全、更有效率的交通網路。這些進步不僅改善了道路安全並減少了堵塞,還為創新的行動服務和智慧城市計畫鋪平了道路,使該地區處於全球自動駕駛汽車市場的前沿。
透過全面的法律規範,各國政府正在為自動駕駛汽車的開發和部署創造有利的環境,預計亞太地區將在預測期內呈現有利的成長。透過提供明確的指導方針和標準,政府正在向製造商、投資者和消費者等相關人員灌輸信心,並刺激全部區域對視音頻技術的創新和投資。此外,亞太地區的法規通常包括獎勵和支持機制,例如研究津貼稅收激勵,以鼓勵產業參與者和政府機構之間的合作,並為自動駕駛開發創建一個充滿活力的生態系統。
According to Stratistics MRC, the Global Autonomous Vehicles Market is accounted for $60.8 billion in 2024 and is expected to reach $180.6 billion by 2030 growing at a CAGR of 19.9% during the forecast period. Autonomous vehicles, often referred to as self-driving cars or driverless cars, are vehicles equipped with advanced sensors, software, and artificial intelligence (AI) algorithms that enable them to navigate and operate without human intervention. These vehicles can perceive their environment, interpret sensory data, and make decisions to navigate roads, avoid obstacles, and adhere to traffic laws autonomously. Autonomous vehicles have the potential to revolutionize transportation by offering increased safety, efficiency and accessibility. They hold promise for reducing traffic accidents caused by human error, optimizing traffic flow, and providing mobility solutions for people who cannot drive due to age, disability, or other factors.
According to Automotive World Ltd., a leader in automotive industry information, there would be more than 2 billion cars across the globe in 2050. According to Environmental Protection Agency (EPA), in the U.S. more than 75% of the carbon monoxide is emitted by motor vehicles.
Rise of mobility as a service
MaaS integrates various transportation services into a unified platform, providing users with seamless access to diverse mobility options, including AVs. By incorporating AVs into MaaS networks, the technology gains broader exposure and acceptance among consumers. MaaS platforms optimize AV utilization, reducing downtime and increasing operational efficiency. Moreover, the data-driven nature of MaaS enables continuous improvement of AV algorithms and enhances safety through real-time monitoring and analysis.
Liability and legal issues
Uncertainty regarding who bears responsibility in the event of accidents involving autonomous vehicles complicates insurance and legal frameworks. Manufacturers, software developers, and even vehicle owners could potentially be held liable, creating a complex web of legal entanglements. However, differing regulations across jurisdictions further exacerbate the problem, hindering widespread adoption and deployment of autonomous vehicles. These elements are hindering the market growth.
Increasing focus on commercial applications
Commercial sectors such as logistics, transportation, and delivery services are recognizing the potential of autonomous vehicles to streamline operations, reduce costs, and enhance efficiency. Businesses are investing heavily in research and development to integrate autonomous technology into their fleets, aiming to capitalize on its benefits. This heightened interest from commercial entities is spurring innovation, leading to advancements in autonomous vehicle capabilities, safety features, and infrastructure support. Moreover, as commercial applications demand scalability and reliability, manufacturers are compelled to refine autonomous systems to meet rigorous industry standards.
Data security concerns
Data security concerns pose a significant hurdle in the advancement of the autonomous vehicles market. The integration of sophisticated sensors, cameras, and connectivity features in autonomous vehicles generates vast amounts of data, including sensitive information about passengers, routes, and locations. This data becomes vulnerable to cyber threats such as hacking, data breaches, and unauthorized access. However, concerns about the potential misuse of this data, including identity theft, surveillance, and manipulation of vehicle functions, undermine consumer trust and confidence in autonomous vehicles.
Initially, the pandemic disrupted supply chains, leading to production delays and hindering the deployment of autonomous vehicles. Social distancing measures and lockdowns reduced demand for ride-hailing services, affecting autonomous vehicle testing and adoption. However, the pandemic highlighted the importance of safety and hygiene, prompting a greater focus on the development of self-driving technology for public transportation and shared mobility services.
The Driver Assistance segment is expected to be the largest during the forecast period
Driver Assistance segment is expected to be the largest during the forecast period, by integrating features such as adaptive cruise control, lane-keeping assistance, and automatic emergency braking, driver assistance systems enhance vehicle safety and comfort while gradually familiarizing users with semi-autonomous capabilities. These technologies mitigate human errors, reduce accidents, and improve traffic flow, thus fostering greater acceptance and trust in autonomous driving technology among consumers and regulators.
The Ride Share segment is expected to have the highest CAGR during the forecast period
Ride Share segment is expected to have the highest CAGR during the forecast period by providing a natural avenue for the adoption and integration of this technology into everyday life. Ride-sharing companies are at the forefront of incorporating autonomous vehicles into their fleets, aiming to reduce operational costs, increase efficiency, and enhance customer experience. By leveraging autonomous technology, ride-share services can offer lower fares to customers while still maintaining profitability. Additionally, these services act as a crucial testing ground for autonomous vehicle systems, allowing developers to collect real-world data and refine their technology in diverse urban environments.
Asia Pacific region commanded the largest share of the market over the extrapolated period. This regional growth is underpinned by the integration of cutting-edge technologies such as 5G networks, Internet of Things (IoT) sensors, and artificial intelligence into transportation systems. Enhanced connectivity enables seamless communication between vehicles, infrastructure, and other smart devices, fostering safer and more efficient transportation networks across the region. These advancements not only improve road safety and reduce congestion but also pave the way for innovative mobility services and smart city initiatives, positioning the region at the forefront of the global autonomous vehicles market.
Through comprehensive regulatory frameworks, governments are fostering an environment conducive to AV development and deployment, Asia Pacific region is estimated to witness profitable growth during the projection period. By providing clear guidelines and standards, governments instill confidence among stakeholders, including manufacturers, investors and consumers, thus stimulating innovation and investment in AV technologies across the region. Moreover, regulations in the Asia Pacific region often include incentives and support mechanisms, such as research grants and tax breaks, which encourage collaboration between industry players and government agencies, fostering a vibrant ecosystem for AV development.
Key players in the market
Some of the key players in Autonomous Vehicles market include Audi, BMW, Continental AG, Daimler Group, Delphi, Ford Motor, General Motors, Hyundai Motor Group, Jaguar, Renault, Tesla, Uber, Volkswagen and Volvo.
In August 2023, GTMC is expected to provide Pony.ai with a fleet of battery electric vehicles branded by Toyota. These vehicles are expected to feature sophisticated redundant systems of Toyota designed for Level 4 autonomous driving research and development. The autonomous driving technology of Pony.ai is expected to be seamlessly incorporated into these vehicles, and they are anticipated to be utilized on the PonyPilot + robotaxi network platform.
In July 2023, Volkswagen Group of America, Inc. (VWGoA) is commencing its inaugural autonomous vehicle testing initiative in Austin. The program is expected to launch with a fleet of 10 all-electric ID. Buzz vehicles equipped with an autonomous driving (AD) technology system, jointly developed by the global Volkswagen Group in collaboration with the technology firm Mobileye.
In July 2023, Tesla announced an investment of USD 1 billion for the development of project Dojo that aims to manage extensive volumes of data, with a specific focus on video feeds originating from Tesla vehicles, a crucial element in the advancement of autonomous driving software of the company.