The concept of future transportation has always been a topic of continuous innovation and imagination. In the years to come, it may be as simple as pressing a button—driverless solar-powered public vehicles will transport people safely to their destinations. These cars will operate based on city-wide intelligent systems that plan routes efficiently, eliminating traffic jams and removing the hassle of parking. The vision for transportation is ever-evolving.
A few days ago, the China Highway Society and Gaode Map established the "Future Transport and Urban Computing Joint Lab," marking a significant step toward smarter cities. This initiative launched its first set of projects, aiming to provide practical solutions for urban mobility challenges. Five leading scientists and their teams will focus on innovative research in transportation and urban development, promoting the future of smart mobility and giving people a glimpse of what’s ahead.
According to Weng Mengyong, Chairman of the China Highway Society, “Future traffic must be multi-dimensional, constantly evolving to better address urban challenges.†The lab aims to leverage big data and cloud computing to revolutionize how we manage traffic.
Industry experts believe that future transportation should be digital, intelligent, automated, and fast. Flexible infrastructure will play a key role. For instance, Li Meng from Daimler’s Sustainable Transport Research Center at Tsinghua University emphasized that true autonomous driving requires integration into a broader transportation system. It’s not just about the vehicle but about the entire ecosystem, including roads and infrastructure.
“The future transportation infrastructure includes traffic detection, signal control, and data collection, enabling full perception of roads and intersections,†Li said. From a research perspective, it involves three levels: collecting massive data, building AI models, analyzing risks, and then transmitting insights to vehicles through AR/VR to enable smart driving.
To tackle urban congestion, Xu Li from the China Highway Society mentioned a five-year plan for the joint lab. The goal is to build a scientific foundation for a strong transportation nation, starting with solving congestion issues. By using data for “health checks†of urban transport, the lab aims to transition from individual optimization to system-level improvements, eventually creating an intelligent traffic management center.
An example is Hangzhou’s successful traffic brain system, which uses big data to detect and respond to traffic jams quickly. It sends real-time updates to traffic police, reducing congestion time by 20% and increasing average speeds by 35%.
Gao De Map’s vice president, Dong Zhenning, stated that the company will collaborate with researchers to explore future transportation technologies, aiming to transform the industry.
However, smart driving is only part of the picture. Yang Xiaoguang, a professor at Tongji University, noted that future transportation isn’t just about changing modes of transport—it’s about transforming the entire service model. Transportation systems are deeply connected to societal development and support smart cities.
Yang believes that a city’s transportation system can be simulated in a computer, demanding advanced computing and deep expertise. With big data, we can now achieve real-world sensing and predictive planning, integrating resources and actively managing urban mobility.
Despite progress, current transportation systems still face major challenges: time-varying, non-linear, discontinuous, unmeasurable, and uncontrollable. Professor Yu Zhi from Sun Yat-sen University proposed the IDPS framework (Infrastructure, Data, Platform, Service System) to address these issues. He emphasizes the need for robust infrastructure, comprehensive data collection, smart platforms, and flexible services.
Experts predict that in the future, roads will be networked and coordinated. Traditional traffic lights may disappear, replaced by intelligent systems where vehicles follow movement rules to optimize traffic flow. This transformation relies on powerful computing, AI, and vast data resources.
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