自動駕駛汽車的商業化及相關問題

自動駕駛汽車透過感測器和攝影機配備感知功能。總的來說，光達和攝影機是實現感知能力的兩大類技術解決方案。美國汽車工程師學會（SAE）提出了自動駕駛的分類體系，共分為L0至L5共6個等級。尤其是L3是一個重要的門檻。在某些條件下，配備L3-L5解決方案的車輛的一個駕駛因素是能夠在自動駕駛系統（ADS）的支援下暫時將手從方向盤上移開。

駕駛座上必須有人準備好接手駕駛任務，因為 L3 功能允許緊急控制在需要時快速返回到突發因素。儘管如此，L3 級仍然是全自動駕駛的一個重要裡程碑。引進自動駕駛技術的主要目的不僅是提高交通效率、減少二氧化碳排放，也是為了減少人為失誤造成的交通事故，並提高安全性。自動駕駛技術也有助於優化智慧城市的交通流量。此外，隨著自動駕駛從狀況3進展到情況4，交通產業的面貌將逐漸發生變化，交通業者的商業模式也將逐漸改變。

該報告調查了自動駕駛汽車市場，並提供了有關自動駕駛實際應用現狀、商業模式和未來挑戰的資訊。

目錄

第一章 自動駕駛實際應用－現狀

• 自動駕駛汽車的實際應用可望優化交通流量，實現智慧城市。
• 自動駕駛汽車的開發進度因地區市場而異，法規對大規模商業化有重大影響。

第二章 自動駕駛汽車商業模式及相關問題

• 自動駕駛汽車有潛力解決勞動力短缺和降低成本。
• 機器人軸實際應用面臨的挑戰

第三章 TRI的觀點

• 支持從 L3 到 L4 過渡的法規和技術不斷發展，使自動駕駛汽車能夠幫助優化智慧城市的交通流量
• 大型車輛生產和技術成本降低是獲利的關鍵；自動駕駛汽車還有很長的路要走

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