Measuring Regularity of Individual Travel Patterns Gabriel Goulet-Langlois, Haris Koutsopoulos, Zhan Zhao, Jinhua Zhao. Measuring Regularity of Individual Travel Patterns. IEEE Transactions on Intelligent Transportation Systems. 2017. Read more about Measuring Regularity of Individual Travel PatternsDOI
Real time transit demand prediction capturing station interactions and impact of special events Peyman Noursalehi, Haris Koutsopoulos, Jinhua Zhao. Real time transit demand prediction capturing station interactions and impact of special events. Transportation Research Part C. 2018. Read more about Real time transit demand prediction capturing station interactions and impact of special eventsDOI
Uncertainty in Bus Arrival Time Predictions: Treating Heteroscedasticity With a Metamodel Approach Aidan O'Sullivan, Francisco Pereira, Jinhua Zhao, Harilaos Koutsopoulos. Uncertainty in Bus Arrival Time Predictions: Treating Heteroscedasticity With a Metamodel Approach. IEEE Transactions on Intelligent Transportation Systems. 2016;(99):1-11. Read more about Uncertainty in Bus Arrival Time Predictions: Treating Heteroscedasticity With a Metamodel ApproachDOI
Individual-Level Trip Detection using Sparse Call Detail Record Data based on Supervised Statistical Learning Zhan Zhao, Jinhua Zhao, Haris Koutsopoulos. Individual-Level Trip Detection using Sparse Call Detail Record Data based on Supervised Statistical Learning. In: Transportation Research Board 95th Annual Meeting.; 2016. Read more about Individual-Level Trip Detection using Sparse Call Detail Record Data based on Supervised Statistical Learning
Mobility as A Language: Predicting Individual Mobility In Public Transportation Using N-Gram Models Zhan Zhao, Haris Koutsopoulos, Jinhua Zhao. Mobility as A Language: Predicting Individual Mobility In Public Transportation Using N-Gram Models. In: Transportation Research Board 96th Annual Meeting.; 2017. Read more about Mobility as A Language: Predicting Individual Mobility In Public Transportation Using N-Gram Models
Incorporating Mobile Activity Tracking Data In A Transit Agency: Collecting, Comparing, And Trip Mode Inference Tim Scully, John Attanucci, Jinhua Zhao. Incorporating Mobile Activity Tracking Data In A Transit Agency: Collecting, Comparing, And Trip Mode Inference. In: Transportation Research Board 96th Annual Meeting.; 2017. Read more about Incorporating Mobile Activity Tracking Data In A Transit Agency: Collecting, Comparing, And Trip Mode Inference
Enabling Transit Service Quality Co-monitoring Through a Smartphone-Based Platform Corinna Li, Christopher Zegras, Fang Zhao, Zhengquan Qin, Ayesha Shahid, Moshe Ben-Akiva, et al. Enabling Transit Service Quality Co-monitoring Through a Smartphone-Based Platform. In: Transportation Research Record: Journal of the Transportation Research Board.; 2017. Read more about Enabling Transit Service Quality Co-monitoring Through a Smartphone-Based Platform
Smartphone-based Mobility Mapping and Perceived Air Quality Evaluation in Beijing Zelin Li. Smartphone-based Mobility Mapping and Perceived Air Quality Evaluation in Beijing. Vol Master of City Planning, Master of Science in Transportation. Cambridge, MA: Massachusetts Institute of Technology; 2016. Read more about Smartphone-based Mobility Mapping and Perceived Air Quality Evaluation in Beijing
Supervised Statistical Learning for Individual Level Trip Detection using Sparse Call Detail Record Data Zhan Zhao, Haris Koutsopoulos, Jinhua Zhao. Supervised Statistical Learning for Individual Level Trip Detection using Sparse Call Detail Record Data. In: 95th Transportation Research Board Annual Meeting. Washington, D.C.: Transportation Research Board; 2016. Read more about Supervised Statistical Learning for Individual Level Trip Detection using Sparse Call Detail Record Data
Clustering the Multi-week Activity Sequences of Public Transport Users Gabriel Goulet Langlois, Haris Koutsopoulos, Jinhua Zhao. Clustering the Multi-week Activity Sequences of Public Transport Users. In: 95th Transportation Research Board Annual Meeting. Washington, D.C.: Transportation Research Board; 2016. Read more about Clustering the Multi-week Activity Sequences of Public Transport Users