Papers by Author: Chao Yang

Abstract: The development of information technology gives rise to explosive growth of the amount of data. As a result, a more effective data mining method in pattern recognition is called into existence, which can properly reflect the inherent daily activity structure of metro travelers. This study is aimed to enrich the traditional clustering methods and provide practical information in dealing with traffic volume variation to the metro system operations. In this study, daily metro origin-destination (OD) data come from smart card records of Shenzhen, China, which cover 290 days and 118 stations. Principal component analysis (PCA) and singular value decomposition (SVD) are applied to conduct dimensionality reduction. Affinity propagation is then chosen to cluster the dimensionality reduced matrix to identify demand patterns of the metro OD matrix. Eleven representative categories are clustered and shown.

Abstract: This paper presents a new method to calculate control delay at signalized intersection or other types using speed-time data. For the control delay which composed of deceleration delay, stopped delay, and acceleration delay, it is important to determine the critical points of each delay. This paper uses speed as well as acceleration to determine the critical points and get an accurate result. Different with other researches, it uses the area that composed of real time speed curve and desired speed curve, divided by the downstream speed, to get the control delay precisely. This method needs less data than other methods and can be applied to any traffic condition including variant desired speed or volume. This paper also provides a rapid method, which doesn’t need to determine the critical points, to estimate control delay, and the precision is acceptable.