China a Global Pacesetter in AI Simulation

"The integration of AI and simulation is one of the most powerful trends of our time — it's transforming how we design, manage and live in cities," said Professor Mohammed S. Obaidat, a computer scientist and past president and chair of board of directors of the Society for Modeling and Simulation International (SCS).

As a prominent expert in modeling and simulation since the 1980s, Obaidat has witnessed this field evolve from academic curiosity to urban necessity. In a recent interview, he noted that the convergence of AI, high-fidelity simulation, and digital twin technology is now reshaping megacities worldwide, with China emerging not just as a participant but as a global pacesetter.

Real-time intelligence for cities

In the past, simulation models were used to test scenarios pending decision making. Urban planners might simulate traffic flow using different road layouts, or energy engineers might model grid pressure during peak demand. But as Obaidat explained, AI has turned simulation into a living, responsive system.

Traditional simulation helped people make predictions. However, "AI-enhanced simulation helps us act. It creates dynamic, data-driven models that learn from real-time inputs — traffic cameras, IoT sensors, weather forecasts and continuously optimize outcomes," he said.

This shift is particularly vital in transportation. In a megacity like Beijing, where over 20 million people generate billions of mobility events daily, and static models quickly become obsolete. AI-simulation systems can now detect problems, such as a multi-vehicle collision on a ring road, and within seconds traffic can be rerouted, emergency services alerted and adjustments of signal timings made across adjacent districts.

The same logic applies to energy. As cities integrate solar, wind and battery storage into their grids, variability becomes a major challenge. AI-simulation platforms can forecast renewable output, anticipate spikes in demand, and simulate thousands of control strategies in milliseconds to maintain stability.

China's urban development, a global benchmark

Few places illustrate this transformation as dramatically as China. Obaidat credited China's success to a rare combination of top-down policy coherence, massive infrastructure investment, and bottom-up technological adoption.

But perhaps the most striking example is urban mobility. "Today, Beijing operates over 800 kilometers of metro, the longest network in the world, and integrates buses, ride hailing, bike sharing and high-speed rail into a single digital ecosystem," he said. This integrated transport layer provides the perfect data foundation for AI-simulation platforms to optimize everything from bus frequencies to last-mile delivery routes.

What makes China's approach globally relevant, he argues, is its scalability. "Cities like Jakarta and Lagos face similar pressures, rapid urbanization, limited public transit, and aging infrastructure. They don't need theory, [but] proven solutions. And China has them, and its experience is transferable."

Obaidat has another vision. "A smart city isn't just one with sensors and algorithms," he said. "It's one that learns from its citizens, adapts to crises, and distributes benefits equitably." In this vision, China's role is pivotal. Its ability to deploy technologies at scale, iterate rapidly, and align public and private sectors offers a template the world can study and adapt. "The future of urban life will be shaped by those who can turn data into dignity, efficiency into equity, and simulation into sustainability," he said. "And right now, China is writing some of the most important chapters of that future."

Shifting to a global ecosystem

As international scientific organizations increasingly establish offices in China, Obaidat sees both opportunity and responsibility.

"The geographic center of science is shifting toward Asia," he said. "With 1.4 billion people, world-class universities, and leadership in 5G, electric vehicles and fintech, China is a natural hub for international sci-tech cooperation."

In terms of the rapid development of AI, he cautioned that technical excellence must be matched by ethical discipline.

"One of my biggest concerns is data bias," he explained. "If an AI traffic model is trained only on data from wealthy districts, it may ignore congestion in informal settlements. If facial recognition systems lack diversity in their training data, they fail to serve marginalized groups. We need inclusive, transparent datasets and global standards to ensure them."

He therefore called for deeper institutional collaboration, praising China's growing participation in international bodies but urged reciprocal openness.

Obaidat's own collaborations reflect this vision. Over the past two decades, he has collaborated with researchers at Beihang University, Beijing University of Posts and Telecommunications, Chongqing University of Posts and Telecommunications, and other Chinese universities, publishing papers in top journals such as IEEE Transactions, co-editing books, and organizing joint workshops on cybersecurity, smart grids and digital twins.

Source: Science and Technology Daily