(From right to left) Dr Ryan WONG, Lecturer, Department of Civil Engineering, Faculty of Engineering, HKU; Professor Jintao KE, Director of Smart Mobility Lab and Assistant Professor, Department of Civil Engineering, Faculty of Engineering, HKU; Ms. Sonia Cheng, Executive Director of Chung Shing Taxi Limited and Founder of SynCab
The Smart Mobility Lab under the Faculty of Engineering at The University of Hong Kong (HKU) and SynCab, a taxi fleet under Chung Shing Taxi Ltd., have jointly developed and launched an AI-powered Smart Dispatch Decision System, offering a faster and more intelligent ride-matching experience for both taxi drivers and passengers.
This Smart Dispatch System integrates key operational inputs including supply, demand, and contextual data. By processing large volumes of dynamic platform information—such as ride-hailing requests, vehicle locations, and road traffic status—the system can accurately assess the current operational environment and provide data-driven support for every dispatch decision, thereby avoiding allocation mismatches. The system also features continuous learning and real-time model updates based on daily operational data.
Professor Jin-tao Ke, Director of the Smart Mobility Lab at the Department of Civil Engineering at HKU, explained, "This system, co-developed by HKU and SynCab, a taxi fleet under Chung Shing Taxi, uses advanced AI analytics to process complex data from multiple sources. It identifies the key factors affecting matching efficiency and dynamically adjusts the weight of various inputs depending on real-time conditions—for instance, prioritizing traffic forecasts during congestion or adapting dispatch based on driver distribution during high-demand periods. Such adaptability allows the system to make reliable, context-aware decisions even under highly dynamic urban environments."
To enhance the quality and precision of dispatch suggestions, the system uses a multi-objective optimisation model during the prediction stage. It simultaneously evaluates key performance indicators including passenger waiting time, driver acceptance probability, estimated driving time, and travel distance. Based on this analysis, the system generates multiple matching scenarios between drivers and ride requests and applies optimization algorithms to select the most effective combination, balancing platform efficiency, passenger satisfaction, and driver income.
Ms. Sonia Cheng, Executive Director of Chung Shing Taxi Limited and Founder of SynCab, remarked, "At present, more than 160 taxis in the SynCab fleet have been equipped with this advanced system. During operational deployment, we have observed a notable improvement in efficiency. With the phased introduction of up to 425 taxis into SynCab fleet, this initiative is expected to significantly enhance fleet capacity utilization, reduce passenger waiting times, and improve the order-taking experience for drivers. This development not only represents a pivotal transformation and innovation for the taxi industry but also serves as a critical step toward the long-term advancement of smart transportation services."
Professor Ke concluded, "This collaboration between HKU and SynCab not only marks a technological breakthrough in AI-powered dispatch decision-making, but also signals a meaningful step toward innovation for the local taxi industry."
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About the Smart Mobility Lab at HKU
The Smart Mobility Lab was founded by Professor Jin-tao Ke at the University of Hong Kong. Professor Ke has published over 60 SCI/SSCI-indexed papers in leading journals on transportation and data analytics. Since 2023, he has been ranked among the world's top 2% most-cited scientists by Stanford University and received the Outstanding Paper Award from the Hong Kong Society for Transportation Studies in 2020.
The lab's research areas include on-demand mobility services, traffic big data analytics, multimodal transport optimization, congestion pricing, and spatiotemporal traffic forecasting. It aims to develop new models and algorithms for data-driven decision-making to better manage and regulate emerging mobility systems. The lab has developed various software tools and applications to enhance the efficiency and sustainability of smart mobility systems, including ride-hailing services, EV networks, and e-taxi markets.
