
Zhejiang Merchants Securities: Tesla Robotaxi pilot finally lands, expected to accelerate domestic L4

ZheShang Securities released a research report stating that Tesla has launched a Robotaxi pilot operation in Austin, Texas, using Model Y and FSD autonomous driving software, with positive feedback from the first batch of passengers. This move validates the feasibility of Tesla's pure vision + end-to-end solution, and it is expected that domestic L4 autonomous driving will accelerate development. In the future, L4 and L5 autonomous driving will follow a gradual path of "closed scenarios → high-speed trunk roads → urban roads." Tesla plans to rapidly expand the Robotaxi fleet to 1,000 vehicles in the coming months, and it is expected that by the end of 2026, there will be more than 1 million autonomous Teslas operating in the United States
According to Zhitong Finance APP, Zhejiang Merchants Securities released a research report stating that recently, Tesla (TSLA.US) launched a Robotaxi pilot operation service in Austin, Texas, USA, using the mass-produced Model Y and FSD autonomous driving software. The initial feedback from the first batch of passengers in this pilot program has been positive. The operation of Robotaxi is a strong validation of Tesla's pure vision + end-to-end solution, proving the feasibility of the route that enhances the intelligence of autonomous driving through large-scale computing power + data-driven approaches. Against the backdrop of Tesla's accelerated entry into the Robotaxi and L4 autonomous driving competition, it is expected that domestic L4 will likely speed up. The future development path of L4 and L5 autonomous driving will follow a gradual path from "closed scenarios → high-speed trunk roads → urban roads," transitioning from commercial scenarios to passenger scenarios.
The main points of Zhejiang Merchants Securities are as follows:
Tesla Robotaxi Pilot Finally Launched
On June 22, Tesla launched the Robotaxi pilot operation service in Austin, Texas, using the mass-produced Model Y and FSD autonomous driving software, allowing users to call for vehicles via an app. This pilot program is invitation-only, with invitees including investors and tech bloggers, and the initial feedback from passengers has been positive. The operation of Robotaxi is a strong validation of Tesla's pure vision + end-to-end solution, proving the feasibility of the route that enhances the intelligence of autonomous driving through large-scale computing power + data-driven approaches. This year, Tesla is expected to launch a new generation model with parameters 4.5 times that of the existing model. Musk plans to rapidly expand the Robotaxi fleet to 1,000 vehicles in the coming months, and by the end of 2026, there will be over 1 million autonomous Teslas operating in the United States.
High-Level Autonomous Driving Competition Begins, Smart Car Companies' Advantages Highlighted
As an L4 (and above) level autonomous driving application, Robotaxi's development may complement the L4 of passenger vehicles. Tesla, as one of the largest smart electric vehicle companies by ownership, can quickly expand the Robotaxi capacity network by incorporating idle cars from owners. Combined with Musk's plans, Tesla's Robotaxi is expected to be widely deployed in the future. With L4 Robotaxi on the road, passenger vehicle drivers will gradually adapt to the road environment of Robotaxi operations, thereby increasing psychological acceptance and recognition of autonomous driving, which will likely open up the L4 passenger vehicle market. Smart car companies have advantages in driving data, and the operation of Robotaxi will serve as a strong promotional proof of the vehicle's autonomous driving capabilities, making Robotaxi applications a key focus of competition for smart cars in the future.
L4 Expected to Accelerate, Commercial Scenarios to Land First
Against the backdrop of Tesla's accelerated entry into the Robotaxi and L4 autonomous driving competition, it is expected that domestic L4 will likely speed up. The future development path of L4 and L5 autonomous driving will follow a gradual path from "closed scenarios → high-speed trunk roads → urban roads," transitioning from commercial scenarios to passenger scenarios. The Ministry of Transport has announced two batches of pilot projects for intelligent transportation leading applications, with the first batch of autonomous driving projects reaching 14, planning to deploy 1,500 autonomous vehicles; the second batch of autonomous driving projects reaching 18, planning to deploy over 2,300 autonomous vehicles In the Mianyang Science and Technology City New District project, Shengtong Technology has launched a dedicated unmanned delivery line, ushering in a new era of intelligent logistics with L4 level unmanned delivery vehicles. The first route has a round trip distance of approximately 17 km, with the unmanned vehicle having a maximum range of 180 km and a load capacity of 800 kg. This L4 level unmanned delivery vehicle can be used in various urban B2B delivery scenarios such as fresh produce, pharmaceuticals, and convenience stores, and can also be applied in closed parks, platform connections, forklift loading and unloading, industrial logistics, and mining transportation.
Recommended Focus
Intelligent Vehicle Companies: Jianghuai Automobile (600418.SH), Seres (601127.SH), BAIC BluePark (600733.SH), Changan Automobile (000625.SZ), GAC Group (601238.SH), SAIC Group (600104.SH), Yutong Bus (600066.SH); Operators: Public Transport (600611.SH), Jinjiang Online (600650.SH).
Hardware and Software Service Providers: Lianchuang Electronics (002036.SZ), Meilixin (301307.SZ), Wanjie Technology (300552.SZ), Jingwei Hirain (688326.SH), Desay SV (002920.SZ), Four-Dimensional Map (002405.SZ), Zhongke Chuangda (300496.SZ), Qianfang Technology (002373.SZ), Qiming Information (002232.SZ), StarNet YuDa (002829.SZ); Unmanned Logistics Vehicles: China Post Technology (688648.SH), Zhilai Technology (300771.SZ), SF City (09699), Shengtong Technology (02495).
Risk Warning
Technology may not meet expectations, commercial implementation may not meet expectations, and policy implementation may not meet expectations