Autonomous buses, also known as Robobuses, are emerging as a pivotal breakthrough in the commercialization of L4 autonomous driving technology. In the realm of public transportation, the combination of high-frequency demand, essential services (the term "rigid demand" is used here to convey the idea of consistent and indispensable transportation needs), and governmental support has propelled this sector to unprecedented heights.

In recent years, several Chinese autonomous driving firms have made significant strides in the bus industry, even triggering a wave of concentrated initial public offerings (IPOs). WeRide and Pony.ai, among others, have successfully gone public, while Shenzhen-based Minieye has cleared the Hong Kong Stock Exchange's listing hearing, signaling strong investor interest in this field.

Drawing on existing research reports, this article provides a professional comparative analysis of five leading companies—WeRide, MOGOX, UISEE, QCraft, and Minieye—across four dimensions: market positioning, deployment cities, core capabilities, and strategic pathways.

1

The Competitive Landscape of the Five Major Players: Differentiated Pathways and Core Competencies

WeRide

Market Positioning: A globally recognized leader in L4 autonomous driving technology.

Deployment Cities: By 2025, WeRide's autonomous minibusses will have conducted tests or operational services in nearly 30 cities worldwide, including major Chinese cities like Guangzhou, Shenzhen, and Beijing, as well as international hubs such as Singapore, Abu Dhabi, Riyadh, Paris, and Zurich.

Core Capabilities: Technologically, WeRide boasts fully autonomous and controllable full-stack L4 capabilities, supported by extensive real-world data and robust safety design redundancies. Its "WeRide One" platform integrates various levels from L2 to L4, with core sensors, algorithms, computing units, and wire-controlled chassis all adopting redundant architectures. The minibus body is equipped with over 20 LiDAR sensors and cameras, enabling 360-degree perception within a 200-meter range and accurately identifying critical traffic elements such as lane markings and traffic lights.

Strategic Pathway: WeRide adopts a dual strategy of technological research and development alongside commercial operations. On one hand, it continues to invest heavily in R&D for core L4 autonomous driving technologies, developing universal platforms and diverse products (such as RoboTaxi, RoboBus, RoboVan, and autonomous sanitation vehicles). On the other hand, the company actively collaborates with industry chain partners to achieve commercialized services in key cities.

MOGOX

Market Positioning: A globally leading provider of autonomous buses.

Deployment Cities: By 2025, MOGOX's Robobus projects will have spread across more than ten provinces and municipalities in China, serving large-scale event scenarios multiple times. Its autonomous buses have demonstration deployments in cities like Beijing, Shanghai, Chengdu, and Dali, Yunnan, with over 500 Robobus vehicles deployed and cumulative operational mileage exceeding 10 million kilometers. It has also begun its overseas market expansion by signing an autonomous bus project in Singapore.

Core Capabilities: MOGOX's autonomous bus, MOGOBUS, adopts a "vision-primary + solid-state LiDAR" solution, boasting the world's largest bus dataset and a unique roadside dataset. It has also independently developed an end-to-end autonomous driving system, MOGO AutoPilot, achieving technological generational leadership. MOGOX is also the only Robobus enterprise that simultaneously possesses "L4 full-stack technology + city-level AI scheduling platform + commercialization on main roads in developed countries" capabilities.

Strategic Pathway: MOGOX actively assumes the role of a smart urban transportation partner, providing autonomous shuttle services in cities like Beijing, Jiading in Shanghai, and the Xiong'an New Area. It has served as the designated supplier for autonomous bus shuttles at major events such as the Chengdu Universiade and the World Internet Conference. Meanwhile, the company emphasizes collaboration with OEMs and operators to develop factory-installed mass-produced buses and has formed consortia to win bids in Singapore and other regions. This model not only exports technology but also binds local operational resources, accelerating the localization and adaptation process. MOGOX has forged a path of "deep domestic demonstration - creating benchmark projects - expanding into overseas markets," building competitive barriers through differentiated advantages.

UISEE

Market Positioning: To be the world's AI driver.

Deployment Cities: As of mid-2025, UISEE has collaborated with over 30 leading enterprises globally, deploying commercial projects in multiple scenarios such as airports, factory districts, and public transportation. Its business covers six countries and regions, including Qatar, Saudi Arabia, and the United Arab Emirates.

Core Capabilities: Its technological strength lies in its multi-scenario, high-safety L4 system and massive real-world unmanned operational data. In terms of sensing and computing, UISEE introduced the industry's first full-solid-state LiDAR solution for minibusses, equipped with eight domestic LiDAR sensors and 15 cameras on the entire vehicle, providing omnidirectional environmental perception from 0 to 200 meters through multi-source sensing fusion. It also possesses a powerful cloud-based operation and management platform for remote vehicle monitoring and scheduling.

Strategic Pathway: UISEE adopts a B2B-first, gradual expansion strategy. It starts with closed scenarios, achieving unmanned driving operations in commercial environments like factories and airports to validate technologies and accumulate revenue before gradually expanding to open road scenarios. Its "Beijing-Hong Kong hybrid" model exemplifies this approach: developing technologies in Beijing and applying them on a large scale at Hong Kong International Airport, thus rapidly overcoming the technology validation stage.

QCraft

Market Positioning: A pioneer in Robobus technology.

Deployment Cities: It has deployed trial operational routes for autonomous minibusses in multiple cities, including Suzhou, Shenzhen, Wuhan, Beijing, Wuxi, and Jiaxing, to validate technologies and serve public transportation needs. Overall, QCraft's city deployments primarily focus on second-tier cities and demonstration zones, with relatively small-scale operations but accumulating operational experience across multiple regions to lay the foundation for future expansion.

Core Capabilities: Its core competitiveness stems from the combination of a top-tier algorithm team and efficient engineering implementation. QCraft's autonomous driving system comprehensively covers complex urban traffic environments, achieving reliable driving control on open roads through multi-sensor fusion and self-developed decision-making and planning. The substantial real-world data accumulated during long-term Robobus operations further feeds back into rapid algorithm evolution. This "algorithm + data" loop enables QCraft's minibusses to perform reliably (this Chinese adjective means "stable" or "robust" and is used here to convey consistent performance) in microcirculation bus scenarios.

Strategic Pathway: QCraft follows a pathway of first seizing commanding heights in niche scenarios before horizontally expanding its business. Initially focusing on Robobus as its main direction, after accumulating over three years of minibus operational data, QCraft proposed the "Dual-Engine Strategy" in 2022. While continuing to deepen L4 technologies, it added an L2+ product line for factory-installed mass production. Specifically, one "power engine" focuses on enhancing longitudinal autonomous driving technological capabilities to approach full autonomy in more scenarios, while the other "innovation engine" introduces the "Chengfeng" urban NOA (Navigate on Autopilot) advanced driver-assistance system to enter the mass production market for passenger vehicles. This strategy achieves parallel development of L4 and L2+ lines.

MINIEYE

Market Positioning: A provider of "progressive" full-stack solutions.

Deployment Cities: From 2023 to 2025, the company successively deployed L4 autonomous minibusses for shuttle and sightseeing purposes in the Suzhou Industrial Park, Harbin in Heilongjiang, the Lingang New Area in Shanghai, and the Hangzhou Asian Games Village. In the first half of 2025, Minieye secured the "Vehicle-Road-Cloud Integration" autonomous bus project in Tongxiang City through competitive bidding, with a contract value of 11.85 million yuan. It will deliver multiple autonomous buses for urban open road public transportation services in the city.

Core Capabilities: Minieye's core strength lies in the integration of full-stack self-research and extreme cost control. For L4 minibusses, Minieye adheres to automotive-grade reliability standards, employing a dual-Orin domain control platform providing 500 TOPS of computing power, paired with a sensor suite of semi-solid-state LiDAR, long-range millimeter-wave radar, and multi-lens cameras to achieve 360° blind-spot-free perception. Through end-to-end large model technology, the vehicle's adaptive perception and decision-making capabilities in complex scenarios such as unprotected left turns, pedestrian mixed-traffic avoidance, and signal recognition have been significantly enhanced, approaching the flexibility of human drivers.

Strategic Pathway: Its strategy can be summarized as a "progressive route" of "ADAS for revenue generation, L4 for breakthroughs." As a leader in cost-effective ADAS solutions, Minieye has achieved stable revenue and technological accumulation by serving numerous OEMs, laying the foundation for its foray into L4. In the L4 direction, the company has focused on two clear scenarios: Robobus autonomous minibusses and Robovan autonomous logistics vehicles.

2

How Far Are Autonomous Buses from Profitability?

After several years of trial operations and explorations, the mainstream business models and profitability prospects for autonomous buses are becoming increasingly clear. They are gradually moving beyond the stage of "burning money on R&D" and beginning to validate feasible revenue models.

The dual-wheel drive of "government cooperation (ToG)" and "enterprise customization (ToB)" represents the primary commercial pathways currently. In the ToG model, autonomous buses integrate into public transportation networks, achieving break-even through ticket revenues and government support. For instance, the Singaporean government is considering L4 autonomous buses. Once validated, the subsequent replacement and expansion of over 300 existing bus routes will open up a vast market space for relevant enterprises. Domestically, cities like Guangzhou and Shenzhen have incorporated Robobuses into their urban intelligent transportation plans, reducing trial operational costs for enterprises through fiscal policies and taxes. Government involvement not only provides financial support but also offers conveniences in route resources and hub access, enabling autonomous buses to integrate more swiftly into local transportation systems.

In the ToB model, autonomous buses provide unmanned shuttle services tailored to specific scenarios such as industrial parks, airports, and other designated areas, delivering direct value to clients through cost reduction, efficiency enhancement, and technological empowerment.

From a scenario-based perspective, tourism parks and industrial zones often serve as the vanguards of commercialization. In closed or semi-closed environments like parks, airports, and ports, the simple and controllable surroundings, stable passenger flows, and relatively high ticket prices make it easy for autonomous minibusses to operate and achieve profitability. According to estimates, if a scenic area receives 100,000 annual visitors taking the bus, at a fare of 10-20 yuan per person, a single autonomous bus can generate annual revenues of 1-2 million yuan. Additionally, tourists' willingness to pay for novel technological experiences ensures a controllable investment recovery period for such projects.

The urban public transportation scenario represents the primary battleground for future large-scale applications. Urban routes boast high passenger volumes and substantial transportation demands, enabling steady revenue generation through long-term operations. Compared to traditional buses, autonomous systems demonstrate superior cost control and profit potential over extended operational periods. Although initial investments are relatively high, once a certain operational scale is reached, the diminishing marginal cost effect becomes pronounced. Research by Yiou Intelligence also indicates that the gross profit margin for Robobus services can reach 25%, with profitability becoming inevitable once fleet sizes surpass a critical threshold.

In summary, autonomous buses are gradually moving towards a virtuous commercial cycle: technological maturity → cost reduction → operational validation → scale expansion, further diluting costs and enhancing profitability.

The profit model for autonomous buses is not built on thin air; rather, it can be established and replicated in high-frequency, essential service (again, "rigid demand") scenarios. With the scaling up of more fleets and reductions in per-unit costs, the overall profitability of the industry is expected to rise in the future.