The mass production of autonomous vehicle is coming, thanks to the rapid progress of autonomous driving technology, especially the recent breakthroughs in LiDAR sensors, GPUs, and deep learning. Many automotive and IT companies represented by Waymo and GM are constantly promoting their advanced autonomous vehicles to hit public roads as early as possible. This paper systematically reviews the latest development and future trend of the autonomous vehicle technologies, discusses the extensive application of AI in ICV, and identifies the key problems and core challenges facing the commercialization of autonomous vehicle. Based on the review, it forecasts the prospects and conditions of autonomous vehicle’s mass production and points out the arduous, long-term and systematic nature of its development.

The automatic emergency braking (AEB) system is an effective intelligent vehicle active safety system for avoiding certain types of collisions. This study develops a national-level safety impact evaluation model for this intelligent vehicle function, including the potential maximum impact and realistic impact. The evaluation model was firstly applied in China to provide insights into Chinese policymaking. Road traffic fatality and severe injury trends, the proportion of different collision types, the effectiveness of collision avoidance, and the AEB market penetration rates are considered in the potential maximum impact scenario. Furthermore, the AEB activation rate and the technology’s technical limitations, including its effectiveness in different weather, light, and speed conditions, are discussed in the realistic scenario. With a 100% market penetration rate, fatalities could be reduced by 13.2%, and injuries could be reduced by 9.1%. Based on China’s policy, the market penetration rate of intelligent vehicles with AEB is predicted to be 34.0% in 2025 and 60.3% in 2030. With this large market penetration rate increase of AEB, the reductions in fatalities and severe injuries are 903–2309 and 2025–5055 in 2025; and 1483–3789 and 3895–7835 in 2030, respectively. Considering AEB’s activation rate and its three main limitations, the adjusted realistic result is approximately 2/5 of the potential maximum result.

Intelligent connected vehicles (ICV) are recognized as a great opportunity with huge social benefits by the global auto industry. Governments of various countries attach great importance to them, and traditional Original Equipment Manufacturer (OEM) and technology companies are also introducing them into consumers’ lives by virtue of various business models, thereby generating practical value. The business model plays a decisive role in determining whether a company can share the ICV market cake and its future position in the industry. More importantly, it will also determine how fast the ICVs can become reality from imagination. In this paper, the ICV industry ecosystem was sorted out, the business models of ICVs adopted by mainstream OEMs were analyzed, and five typical business models were summarized, i.e. platform model, self-transformation model, traditional Tier1 dependence model, alliance model, and outsourcing model. On this basis, the SWOT analysis method was adopted to systematically analyze the internal and external advantages and disadvantages of the five business models, and forward insights on enterprises’ developing and maintaining the competitive advantages in the ICV industry were proposed from five perspectives of technology, market timing, customer experience, brand, and data.

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