Grab is planning to build a hybrid ecosystem that integrates human driving, autonomous driving, and remote driving. Grab CEO Anthony Tan noted that the future of transportation in Southeast Asia will no longer rely on a single mode but instead on the collaboration of multiple technologies. Vay’s model combines remote driving with a shared electric-vehicle fleet. After a user requests a vehicle via the app, a remote driver pilots the vehicle to the user’s location. The user then completes the trip by driving themselves. When the trip ends, the remote driver takes over again and parks the vehicle at an appropriate location. This approach saves users the time needed to search for parking, allows remote drivers to support more trips with limited manpower, and, with the use of cameras and lightweight hardware, reduces costs. As a result, the operational efficiency surpasses that of traditional ride-hailing services and is particularly well-suited for multi-segment or short-distance travel needs.
Vay’s technology has already been deployed in the United States, with its remote-driving fleet launched in Las Vegas in 2024. Its automotive-grade safety standards have been certified by German regulators, demonstrating a high level of safety and reliability. Moving forward, Vay plans to gradually introduce more autonomous-driving functions based on the extensive real-world driving data collected through remote operations. This human–machine collaboration approach shortens the commercialization timeline, positioning Vay as one of the few companies in the autonomous-driving field with the capability for large-scale commercial deployment.
For Grab, this investment carries multiple layers of significance. Grab operates mobility services across eight countries and more than 800 cities, with strong capabilities in marketing, product development, and fleet management. These strengths can help Vay accelerate its penetration into the U.S. market while enabling Grab to explore integration opportunities between remote driving and its existing service ecosystem. Moreover, the large amount of driving data collected by Vay may enhance Grab’s autonomous-driving AI model training, strengthening its competitive position in the future automated mobility market in Southeast Asia. It is also notable that Grab has invested in WeRide and May Mobility in recent years, highlighting its aggressive deployment in autonomous driving and next-generation mobility services.
According to the investment agreement, after the initial USD 60 million injection, Grab may invest an additional USD 350 million within one year after the transaction is completed, provided that Vay meets several milestones, including revenue performance, number of operating cities, safety-technology certifications, and regulatory approvals. If these conditions are met within a year, Grab could gradually acquire a majority stake in Vay. This structure allows Grab to reduce early-stage risk and expand investment only after confirming the technology’s feasibility and market traction. Should Vay’s growth and expansion progress as expected, Grab may become its largest shareholder within three years and secure a more influential position in the future mobility-technology landscape.
Overall, Grab’s core objective in investing in Vay is not short-term financial returns but control over the future of urban mobility. The combination of remote driving and shared fleets allows Grab to create an intermediary solution that commercializes faster than full autonomous driving and is more cost-effective than models relying purely on human labor. This human–machine collaboration model may prove to be the most pragmatic and competitive mobility solution for Southeast Asia’s complex transportation conditions.
For Taiwan, the remote-driving model that Grab is introducing offers an opportunity to improve operational efficiency by reducing the need for large-scale on-site manpower for fleet repositioning, collection, and redistribution. It may also help address mobility shortages in rural areas. If Taiwan aims to reduce reliance on private cars and enhance transportation efficiency in the future, the introduction of remote-driving technology would be a direction worth evaluating jointly by the government and the industry.
Furthermore, Vay’s model shows that full autonomous driving is not the only path forward. Instead, remote driving accumulates large volumes of real-world data, which can then be used to gradually integrate more automated features, accelerating the practical adoption of autonomous technologies. In our view, for Taiwan’s autonomous-driving industry, adopting a “remote-first, autonomous-second” strategy to build technological and data advantages could help companies establish a stronger foothold in future global competition.
Taiwan possesses a robust supply chain in automotive electronics, camera modules, communication modules, and networking equipment. Vay’s camera-centric hardware architecture aligns well with the strengths of Taiwan’s ICT sector, manufacturing capabilities, and vehicle-networking ecosystem. As remote-driving technology expands across the United States and Southeast Asia, Taiwanese companies may become core suppliers within this emerging value chain.
From an urban-governance perspective, Taiwan’s dense population and limited parking capacity could significantly benefit from a remote-driving car-sharing model in which users do not need to search for parking spaces. This would substantially reduce parking pressure and urban space waste. If such a model can be tested through partnerships with local electric-car-sharing providers, it could introduce a completely new urban mobility experience. Taken together, the collaboration between Grab and Vay represents not merely a technological innovation but a design proposal for redefining how cities operate—an opportunity that Taiwan should examine carefully.