![]() |
市场调查报告书
商品编码
1732173
全球自动驾驶卡车市场按自动驾驶等级、推进类型、最终用途产业、卡车类型、地区和预测划分Global Autonomous Trucks Market By Level of Autonomy, By Propulsion Type, By Truck Type, By End-User, By Geographic Scope and Forecast |
2024 年全球自动驾驶卡车市场规模为 30.4 亿美元,预计到 2032 年将达到 82.2 亿美元,2026 年至 2032 年的复合年增长率为 13.24%。
自动驾驶卡车是一种自动驾驶车辆,它使用先进的感测器、摄影机和人工智慧 (AI) 来穿越道路并运输货物,无需人工干预。
它主要用于物流和货运,以提高业务效率、降低成本和缓解司机短缺问题,但也可用于采矿、农业和废弃物管理行业的日常运输需求。
自动驾驶卡车预计将透过提高安全性和降低油耗来彻底改变物流行业。随着监管法规的变化和技术进步,随着自动驾驶卡车与远距货运、智慧城市和自动化供应链的整合不断增长,预计未来十年它将得到更广泛的应用。
影响全球自动驾驶卡车市场的关键市场动态是:
关键市场驱动因素
卡车运输业的劳动力短缺:驾驶人驾驶人(尤其是远距货运)的持续短缺是自动驾驶卡车发展的关键驱动力。各公司正在寻求减少对人类驾驶员依赖的解决方案,以满足日益增长的货物运输需求。 2024年6月,美国运输部强调北美地区驾驶员短缺问题紧迫,并重新激发了人们对自动驾驶卡车作为潜在解决方案的兴趣。
对高效且经济的物流的需求日益增长:自动驾驶卡车将降低油耗、改善路线并实现不停车行驶,从而提高整体物流和供应链效率。 2024年5月,特斯拉宣布其自动驾驶电动车Tesla Semi成功测试,证明将大幅降低物流机构远距运输的成本。
政府支持和法律规范:各国政府正在透过法律体制、试点计画和采用奖励逐步支持自动驾驶汽车技术。 2024年4月,欧盟委员会发布了自动驾驶汽车测试新标准,旨在加快在欧洲货运路线上部署自动驾驶卡车。
人工智慧和感测器技术的进步:人工智慧、感测器技术和光达系统的突破正在显着提升自动驾驶卡车的性能,使其在实际场景中更加可靠。 2024年7月,Google旗下自动驾驶公司Waymo在亚利桑那州高速公路上成功试驾后,推出了新一代人工智慧卡车,配备了升级版雷射雷达感测器和更强大的决策演算法。
主要挑战
监管与法律障碍:监管是自动驾驶卡车技术发展的主要障碍。现行的交通法规和安全标准主要针对人类驾驶员,而自动驾驶汽车的法律体制仍在不断发展。人们对事故责任、网路安全和资料隐私等问题感到担忧。在自动驾驶卡车能够广泛应用之前,政府必须制定明确的立法、测试标准和责任法规。在强有力的法律体制建立之前,自动驾驶卡车的大规模应用可能会受到限制。
高昂的前期和营运成本:开发和部署自动驾驶卡车需要在先进的感测器、雷射雷达、人工智慧系统和网路基础设施方面进行大量投资。公司在整合自动驾驶系统、校准车辆以及保持技术更新方面需要承担高昂的前期投资成本。虽然这些成本可能会随着业务的成长而下降,但对于中小型企业来说,这仍然是一个障碍。
技术限制和安全隐患:儘管自动驾驶技术正在不断发展,但全自动驾驶卡车仍然面临着许多挑战,例如如何应对复杂的路况、恶劣的天气条件以及难以预测的人类行为。安全至关重要,尤其是在混合交通区域。系统故障风险、网路安全漏洞以及应对施工区域等不断变化的情况的能力,都是必须应对的重大技术挑战。
社会接受度和劳动力流失:自动驾驶卡车可能会取代卡车驾驶人,从而导致工会和当地社区的抵制,并且需要大量的道路试验和公众意识努力才能赢得公众对安全性和可靠性的信任。
主要趋势:
人工智慧和机器学习的进步:人工智慧和机器学习对于提升自动驾驶卡车的决策能力至关重要。这些技术使车辆能够处理来自感测器和摄影机的大量数据,从而能够在充满挑战的环境中行驶。人工智慧演算法在物体检测、路线优化和避障方面不断改进,使自动驾驶卡车能够更有效率、更安全地运行,尤其是在远距货物运输方面。
伙伴关係与协作:多家汽车和科技公司已结成策略联盟,以加速自动驾驶卡车的开发和商业化。 Waymo、戴姆勒和特斯拉正在与物流公司合作,将自动驾驶卡车整合到供应链中。这些合作将人工智慧、感测器和物流知识相结合,以加速自动驾驶卡车的普及。
电动车 (EV) 整合:自动驾驶卡车技术与电动车 (EV) 平台的整合趋势日益增长。自动驾驶电动卡车为典型的柴油引擎车辆提供了更环保、更有效率的替代方案。特斯拉和尼古拉等开发商正在开发电动自动驾驶卡车,他们声称这些卡车将透过减少排放气体、降低燃料成本和提高运作效率来符合全球环境目标。
专注于远距运输和货运:远距货运因其常规路线和高速公路等受监管的环境而被视为最具前景的应用领域,因此自动驾驶卡车的开发主要集中于此。远距货运透过减少驾驶员疲劳和提高燃油效率,具有最大的成本节约潜力。各公司之所以积极布局这一领域,是因为它比都市区和最后一英里配送更容易自动化,而后者对环境的要求更高。
Global Autonomous Trucks Market size was valued at USD 3.04 Billion in 2024 and is projected to reach USD 8.22 Billion by 2032, growing at a CAGR of 13.24% from 2026 to 2032.
Autonomous trucks are self-driving vehicles that use advanced sensors, cameras, and artificial intelligence (AI) to traverse roadways and move cargo without the need for human interaction.
They are largely utilized in logistics and freight transportation to improve operational efficiency, lower costs, and address driver shortages. They can also be used in the mining, agriculture, and waste management industries for everyday transportation.
Autonomous trucks are predicted to transform the logistics business by increasing safety and lowering fuel usage. As regulations change and technology progresses, wider adoption is expected, with further integration into long-haul freight, smart cities, and automated supply chains over the next decade.
The key market dynamics that are shaping the global autonomous trucks market include:
Key Market Drivers:
Labor Shortages in the Trucking Industry: The persistent lack of truck drivers, particularly in long-haul freight, is a significant motivator for autonomous trucks. Companies are seeking for solutions to lessen their reliance on human drivers in order to fulfill the increasing demand for goods transportation. In June 2024, the US Department of Transportation emphasized the urgent driver shortage in North America, reigniting interest in self-driving trucks as a possible solution.
Increasing Demand for Efficient and Cost-Effective Logistics: Autonomous trucks have the ability to cut fuel consumption, improve routes, and run without stopping, hence enhancing total logistics and supply chain efficiency. In May 2024, Tesla announced successful testing of their self-driving electric vehicle, the Tesla Semi, demonstrating considerable cost reductions in long-haul transportation for logistics organizations.
Government Support and Regulatory Frameworks: Governments are progressively backing autonomous car technology through legal frameworks, pilot programs, and adoption incentives. In April 2024, the European Commission issued new criteria for autonomous vehicle testing, seeking to accelerate the deployment of self-driving trucks in Europe's freight corridors.
Technological Advancements in AI and Sensors: Breakthroughs in AI, sensor technology, and LiDAR systems have considerably increased autonomous trucks' capabilities, making them more trustworthy in real-world scenarios. In July 2024, Waymo, Google's self-driving company, launched a new generation of AI-driven trucks, with upgraded LiDAR sensors and more powerful decision-making algorithms, following successful test runs on Arizona highways.
Key Challenges:
Regulatory and Legal Barriers: Regulation presents substantial hurdles for autonomous truck technology. Current traffic regulations and safety standards are largely intended for human drivers, and the legal framework for autonomous cars is still growing. There are concerns about liability in the event of an accident, cybersecurity, and data privacy. Governments must set clear legislation, testing standards, and liability laws before autonomous trucks may be extensively used. Until a strong legal framework is built, mass adoption will be limited.
High Initial Investment and Operational Costs: Developing and implementing self-driving trucks necessitates considerable investments in advanced sensors, LiDAR, AI systems, and network infrastructures. Companies incur significant upfront expenditures when integrating autonomous systems, adapting fleets, and maintaining modern technology. Although these expenses may decrease with growth, they remain a barrier for small and medium-sized firms.
Technological Limitations and Safety Concerns: While autonomous technology has advanced, fully autonomous trucks continue to confront obstacles like as managing complex road conditions, inclement weather, and unpredictable human behavior. Safety is crucial, especially in mixed-traffic areas. The risk of system failure, cybersecurity vulnerabilities, and the ability to react to changing conditions such as construction zones are all significant technological challenges that must be addressed.
Public Acceptance and Workforce Displacement: The Autonomous trucks may result in job displacement for truck drivers, prompting opposition from labor unions and communities. Furthermore, obtaining public trust in terms of safety and dependability will necessitate substantial real-world testing and public awareness initiatives.
Key Trends:
Advancements in AI and Machine Learning: AI and machine learning are crucial to improving autonomous trucks' decision-making capabilities. These technologies enable vehicles to process massive volumes of data from sensors and cameras, allowing them to maneuver through difficult environments. AI algorithms are constantly improving in terms of object detection, route optimization, and obstacle avoidance, allowing autonomous trucks to operate more efficiently and safely, particularly for long-haul freight delivery.
Partnerships and Collaborations: Several automotive and technology businesses are creating strategic alliances to speed the development and commercialization of self-driving trucks. Waymo, Daimler, and Tesla are working with logistics firms to integrate self-driving trucks into the supply chain. These collaborations are accelerating the implementation of self-driving trucks by combining expertise in AI, sensors, and logistics.
Integration with Electric Vehicles (EVs): There is a growing trend of combining autonomous truck technology with electric vehicle (EV) platforms. Autonomous electric trucks provide a more environmentally friendly and efficient alternative to typical diesel-powered vehicles. Companies such as Tesla and Nikola are developing electric autonomous trucks that claim to cut emissions, slash fuel costs, and run more effectively, thereby harmonizing with global environmental goals.
Focus on Long-Haul and Freight Transport: Long-haul trucking is viewed as the most promising use due to regular routes and regulated surroundings such as highways, therefore autonomous truck development is largely focused there. Long-haul freight has the greatest potential for cost reductions due to reduced driver fatigue and improved fuel efficiency. Companies are pursuing this area because it is easier to automate than urban or last-mile deliveries, which require more dynamic conditions.
Here is a more detailed regional analysis of the global autonomous trucks market:
North America:
North America currently controls the autonomous trucks market and is growing at the fastest rate. This leadership position is fueled by considerable investments from major automotive and technology businesses, advanced infrastructure, and favorable regulatory regimes in the United States and Canada. In March 2024 TuSimple stated that it would expand its autonomous freight network in Texas, while Waymo Via collaborated with J.B. Hunt to launch autonomous truck deliveries in the Southwest United States.
In January 2024, the United States Department of Transportation issued updated standards for autonomous vehicle testing and deployment, giving a more defined regulatory framework for manufacturers and operators. In May 2024, the Ontario government adopted new legislation allowing autonomous truck testing on public highways, reinforcing North America's status as a hub for autonomous vehicle development and implementation.
Asia Pacific:
The Asia Pacific area is emerging as the fastest-growing autonomous truck industry, with a projected CAGR of 17.8% between 2024 and 2028. China is driving this expansion, accounting for over 45% of the regional market share. In March 2024, Chinese autonomous driving company Plus.ai announced a collaboration with FAW Jiefang, one of China's top truck manufacturers, to deploy 1,000 autonomous vehicles on major freight routes by 2025. Meanwhile, in Japan, WABCO Holdings and Mitsubishi Fuso Truck and Bus Corporation announced a collaboration in January 2024 to develop Level 4 autonomous trucking technology, with plans to conduct public road tests by late 2024.
In November 2024, Singapore's Land Transport Authority announced the expansion of its autonomous vehicle testbed, enabling for longer trials of autonomous trucks in urban situations. The Asia Pacific autonomous truck market was worth $1.2 billion in 2024 and is predicted to exceed $3.5 billion by 2028, owing to rising labor shortages in the logistics sector and the region's strong manufacturing and e-commerce boom.
The Global Autonomous Trucks Market is segmented on the basis of By Level of Autonomy, By Propulsion Type, By Truck Type, By End-User and By Geography.
Based on Level of Autonomy, the Global Autonomous Trucks Market is segmented into Level 1, Level 2, and Level 3. Level 2 autonomy is currently dominating, since semi-autonomous vehicles equipped with advanced driver assistance systems (ADAS) are commonly used for duties such as lane maintaining, adaptive cruise control, and emergency braking, particularly in logistics and freight. The fastest-growing area is Level 3 autonomy, which allows trucks to function without human assistance under specific conditions. Demand for this level is fast increasing as a result of technology breakthroughs in AI and sensor systems, as well as an increased interest in fully autonomous long-haul freight operations.
Based on Propulsion Type, the Global Autonomous Trucks Market is segmented into IC Engine, Electric. The IC Engine (Internal Combustion Engine) category is currently dominant, with diesel-powered trucks remaining popular due to their established infrastructure and greater range capabilities, particularly for heavy-duty, long-haul transportation. However, the Electric segment is expanding at the highest rate, thanks to increased environmental restrictions, developments in battery technology, and a quest for cleaner, more sustainable transportation choices. Companies such as Tesla and Nikola are speeding the deployment of electric self-driving trucks.
Based on Truck Type, the Global Autonomous Trucks Market is segmented into Light-Duty Trucks and Medium-Duty Trucks. The light-duty trucks segment is currently dominant because these trucks are commonly utilized in cities for short-distance deliveries and last-mile logistics, where autonomous features can increase efficiency. Medium-Duty Trucks are the fastest-growing market, owing to increased usage in logistics and freight operations for regional and mid-range deliveries, where autonomy can lower costs and optimize route planning over longer distances.
Based on End-User, the Global Autonomous Trucks Market is segmented into Manufacturing, Construction and Mining, Military. The Construction and Mining category is now dominant, as autonomous vehicles are widely utilized in these industries for repeated work in regulated conditions such as mine operations, where safety and efficiency are critical. The Military is the fastest-growing segment, because to increased investments in autonomous technologies for defense applications including moving supplies in dangerous locations and lowering dangers to soldiers during combat operations.
Based on the Geography, the Global Autonomous Trucks Market are classified into North America, Europe, Asia Pacific, and Rest of the World. North America is currently the dominant region, with to superior infrastructure, governmental support, and large expenditures in autonomous vehicle technology, particularly in the United States. Asia Pacific is the fastest-growing area, with countries such as China and Japan accelerating autonomous technology adoption because to government efforts, AI developments, and rising need for logistics and transportation automation.
The "Global Autonomous Trucks Market" study report will provide valuable insight with an emphasis on the global market. The major players in the market are AB Volvo, Uber Technologies, Inc., Daimler AG, Denso, Ford Motor Co., Tesla, Inc., Aptiv, BMW AG, Paccar, IVICO, Robert Bosch, MAN, DAF, Scania, Waymo.
Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with its product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.