Transportation Mode

Transportation mode recognition (TMR) aims to automatically identify how people travel (e.g., walking, driving, cycling) using data from sources like smartphones. Current research focuses on improving accuracy and efficiency using various machine learning approaches, including convolutional neural networks (CNNs), recurrent neural networks (RNNs, particularly biLSTMs), and transformer models, often incorporating techniques like attention mechanisms and feature pyramids to process diverse data streams (e.g., acceleration, GPS location). These advancements are crucial for applications such as urban planning, traffic management, and personalized location-based services, enabling a more comprehensive understanding of human mobility patterns.