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Yanshuo Sun
Researcher at Florida A&M University – Florida State University College of Engineering
Publications - 33
Citations - 515
Yanshuo Sun is an academic researcher from Florida A&M University – Florida State University College of Engineering. The author has contributed to research in topics: Computer science & Public transport. The author has an hindex of 10, co-authored 30 publications receiving 355 citations. Previous affiliations of Yanshuo Sun include Tongji University & University of Maryland, College Park.
Papers
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Rail Transit Travel Time Reliability and Estimation of Passenger Route Choice Behavior: Analysis Using Automatic Fare Collection Data
Yanshuo Sun,Ruihua Xu +1 more
TL;DR: Applications of automatic fare collection data were investigated, with a focus on analysis of travel time reliability and estimation of passenger route choice behavior, and could facilitate analysis of transit service reliability and passenger flow assignment in daily operations.
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Identifying passenger flow characteristics and evaluating travel time reliability by visualizing AFC data: a case study of Shanghai Metro
TL;DR: This paper’s main objectives are to analyze passenger flow characteristics and evaluate travel time reliability for the Shanghai Metro network by visualizing the automatic fare collection (AFC) data.
Journal ArticleDOI
Schedule-Based Rail Transit Path-Choice Estimation using Automatic Fare Collection Data
Yanshuo Sun,Paul Schonfeld +1 more
TL;DR: In this paper, a schedule-based passenger's path-choice estimation model for a multioperator rail transit network, using automatic fare collection (AFC) data from both entry and exit stations, is presented.
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Joint optimization of tram timetables and signal timing adjustments at intersections
TL;DR: A real-world case study of Line 5 of the Shenyang Hunnan Modern Tramway shows that by extending the dwell time or link travel time, the authors can significantly reduce the TSP’s negative impacts on the auto traffic while only slightly increasing tram travel times.
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Analyzing high speed rail passengers’ train choices based on new online booking data in China
TL;DR: Two nonparametric machine learning methods, namely support vector regression (SVR) and artificial neural networks (ANN), are explored for understanding and predicting high-speed rail travelers’ choices of ticket purchase timings, train types, and travel classes, using ticket sales data.