自动驾驶汽车的商业化及相关问题

自动驾驶汽车透过感测器和摄影机配备感知功能。总的来说，光达和摄影机是实现感知能力的两大类技术解决方案。美国汽车工程师学会（SAE）提出了自动驾驶的分类体系，共分为L0至L5共6个等级。尤其是L3是一个重要的门槛。在某些条件下，配备L3-L5解决方案的车辆的一个驾驶因素是能够在自动驾驶系统（ADS）的支援下暂时将手从方向盘上移开。

驾驶座上必须有人准备好接手驾驶任务，因为 L3 功能允许紧急控制在需要时快速返回到突发因素。儘管如此，L3 级仍然是全自动驾驶的一个重要里程碑。引进自动驾驶技术的主要目的不仅是提高交通效率、减少二氧化碳排放，也是为了减少人为失误造成的交通事故，并提高安全性。自动驾驶技术也有助于优化智慧城市的交通流量。此外，随着自动驾驶从状况3进展到情况4，交通产业的面貌将逐渐发生变化，交通业者的商业模式也将逐渐改变。

该报告调查了自动驾驶汽车市场，并提供了有关自动驾驶实际应用现状、商业模式和未来挑战的资讯。

目录

第一章 自动驾驶实际应用－现状

• 自动驾驶汽车的实际应用可望优化交通流量，实现智慧城市。
• 自动驾驶汽车的开发进度因地区市场而异，法规对大规模商业化有重大影响。

第二章 自动驾驶汽车商业模式及相关问题

• 自动驾驶汽车有潜力解决劳动力短缺和降低成本。
• 机器人轴实际应用面临的挑战

第三章 TRI的观点

• 支持从 L3 到 L4 过渡的法规和技术不断发展，使自动驾驶汽车能够帮助优化智慧城市的交通流量
• 大型车辆生产和技术成本降低是获利的关键；自动驾驶汽车还有很长的路要走

Autonomous or self-driving vehicles are endowed with perception capabilities through sensors and cameras. In general, LiDAR and cameras are the two main categories of technological solutions for enabling perception capabilities. The Society of Automotive Engineers (SAE) in the United States has proposed a classification system for automated driving, comprising a total of six levels from L0 to L5. In particular, L3 marks a significant threshold. Under specific conditions, drivers of vehicles equipped with L3~L5 solutions can temporarily keep their hands away from the steering wheel due to the support from the automated driving system (ADS).

L3 functionality allows for emergency control to be quickly handed back to the driver when needed, so there still must be a person ready to take over the driving task in the driver's seat. Nevertheless, L3 remains an important milestone in the progress towards fully automated driving. The adoption of automated driving technologies extends beyond improving traffic efficiency and reducing carbon emissions; the core purpose of adopting these technologies is to reduce traffic accidents caused by human errors, thereby improving safety. Automated driving technologies can contribute to the optimization of traffic flows in smart cities. Furthermore, as automated driving advances from L3 to L4, the landscape of the transportation sector, along with the business models of transport operators, will gradually change.

Table of Contents

1. Commercialization of Automated Driving - Current Status

• (1) Commercialization of Autonomous Vehicles Is Expected to Lead to Optimization of Traffic Flows and Realization of Smart Cities

• (2) Progress in Development of Autonomous Vehicles Varies Depending on Regional Market, and Regulations Have Significant Influence on Large-Scale Commercialization<

2. Business Models for Operating Autonomous Vehicles and Related Challenges

• (1) Autonomous Vehicles Have Potential to Alleviate Labor Shortages and Cut Costs

• (2) Challenges in Commercialization of Robotaxi

3. TRI's View

• (1) Regulations and Technologies Are Evolving to Support Transition from L3 to L4, and Autonomous Vehicles Will Contribute to Optimization of Traffic Flows in Smart Cities

• (2) Large-Scale Vehicle Production and Lowering Costs of Technologies Are Key to Profitability, so There Is Still Long Road Ahead Before Commercialization of Autonomous Vehicles