Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank

Understand

Traffic forecasting is a critical service in Intelligent Transportation Systems (ITS).

• Utilizing deep models to tackle this task relies heavily on data from traffic sensors or vehicle devices, while some cities might lack device support and thus have few available data.
• So, it is necessary to learn from data-rich cities and transfer the knowledge to data-scarce cities in order to improve the performance of traffic forecasting.
• To address this problem, we propose a cross-city few-shot traffic forecasting framework via Traffic Pattern Bank (TPB) due to that the traffic patterns are similar across cities.