Dayong Shen

TL;DR: This paper overviews data sources, analytical approaches, and application systems for social transportation, and suggests a few future research directions for this new social transportation field.

TL;DR: A self-adaptive parameter selection algorithm called HMTP * is proposed, which captures the parameters necessary for real-world scenarios in terms of objects with dynamically changing speed and has higher positioning precision than HMTP due to its capability of self-adjustment.

TL;DR: This work analyzes the existing challenges in video-based surveillance systems for the vehicle and presents a general architecture for video surveillance systems, i.e., the hierarchical and networked vehicle surveillance, to survey the different existing and potential techniques.

TL;DR: The proposed DP-KELM traffic sign recognition approach is demonstrated to have higher precision than most of the state-of-the-art approaches and can achieve a comparable recognition rate with significantly fewer computational costs.

TL;DR: A probabilistic model is developed that can estimate from empirical analysis how the passenger flows are dispatched to different routes and trains and is validated using a large-scale data set collected from the Shenzhen Metro system.