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2024年中国Robotaxi商业化趋势研究报告
每年都有人说是自动驾驶的元年，Robotaxi究竟如何？
在⾃动驾驶仿真领域，场景⼀直是⼤家关注的重中之重。因为⾃动驾驶仿真与传统的仿真的最⼤区别就是缺少了⼈。⾯对复杂的交通状况做出灵活应对，在⾃动驾驶之前⼀直是⼈类驾驶员的责任，⽽在⾃动驾驶⾯世之后，车辆本⾝需要对⾃⼰负责、对乘坐在其上的乘客负责。因此，需要在⾃动驾驶车辆上路之前，尽可能多的经历不同场景的测试和考验，才能让消费者放⼼，让⼚商⾃⼰安⼼。
With the new industrial revolution of digital trans-formation, more intelligence and autonomous systems can be adopted in the manufacturing transportation processes. Safety and security of autonomous vehicles (AV) have obvious advan-tages of reducing accidents and maintaining a cautious environ-ment to drivers and pedestrians. Therefore, the transformation to data-driven vehicles is associated with the concept of digital twin, especially within the context of autonomous vehicle design. This also raises the need to adopt new safety designs to increase the resiliency and security of the whole autonomous vehicle system. To enable secure autonomous systems for smart manufacturing transportation in an end-to-end fashion, this article presents the main challenges and solutions considering safety and security functions. This article aims to identify a standard framework for vehicular digital twins that facilitate data collection, data processing, and analytics phases. To demonstrate the effectiveness of the proposed approach, a case study for vehicle follower model is analyzed when radar sensor measurements are manipulated in an attempt to cause a collision. Perceptive findings of this article can pave the way for future research aspects related to employing digital twins in the autonomous vehicle industry.
Digital twin, an emerging representation of cyber-physical systems, has attracted increasing attentions very recently. It opens the way to real-time monitoring and synchronization of real-world activities with the virtual counterparts. In this study, we develop a digital twin paradigm using an advanced driver assistance system (ADAS) for connected vehicles. By leveraging vehicle-to-cloud (V2C) communication, on-board devices can up-load the data to the server through cellular network. The server creates a virtual world based on the received data, processes them with the proposed models, and sends them back to the connected vehicles. Drivers can benefit from this V2C based ADAS, even if all computations are conducted on the cloud. The cooperative ramp merging case study is conducted, and the field implementation results show the proposed digital twin framework can benefit the transportation systems regarding mobility and environmental sustainability with acceptable communication delays and packet losses.
In the nearby future, testing advanced driver assistance systems (ADAS) solely on a proving ground is no longer sufficient. With the increasing level of automation, the number of scenarios vehicles need to react to in a safe and repeatable manner is rapidly growing. Virtual validation and verifica-tion is about to become common practice for all original equipment manu-facturers (OEMs) that are integrating systems like autonomous emergency braking, lane keeping assist, speed and parking assist. However, virtual results can only be trustworthy if they are confirmed by physical testing. Having consistency in test scenarios, the virtual representation of the envi-ronment, the car and sensors is the key to successfully validating and veri-fying automated driving functions.
本白皮书介绍数据中心自动驾驶网络的内涵、分级标准、网络架构、尤其是关键技术，包括数字孪生网络、网络引入的 AI 技术、网络仿真与推演、意图管理和回滚、智能搜索技术，并通过测试用例介绍数据中心自动驾驶网络的关键能力。
在国内发展智能网联汽车产业具有充足的必要性：汽车作为国内第二大产业对经济发展至关重要，通过发展智能网联汽车产业除了可以实现对海外传统汽车工业强国的弯道超车，同时可培养一批具有高端技术实力的产业链上游厂商。此外，智能网联汽车将会显著改善城市交通环境，提升人们的出行效率；
汽车产业经过百年发展，产业链固化并形成了较高的市场壁垒，但传统的产业格局难以适应新时代智能网联汽车的技术发展需求。智能网联汽车需要对于汽车底层电子电气系统重新整合设计，传统汽车电子供应链存在着破坏式的创新发展机会；
智能网联汽车产业发展包括单车自动化和车联网两大发展领域。其中单车自动化预计在未来两年将会迎来L3级产品的量产落地，L4级将会在未来5-10年实现落地。L3级及以上产品的落地这将会相继带动包括：毫米波雷达、激光雷达、智能芯片等产业链上游环节的发展机会；
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