Mobility Sensing & Prediction

For a century, transportation agencies have relied on costly and unreliable manual data collection systems. These approaches have hampered the effective planning, management, and evaluation of mobility services, ultimately reducing efficiency and threatening quality customer service.

The development of Information and Communication Technology (ICT), however, has transformed what was once a data-starved arena into a data-rich environment for planners and managers.

At JTL, we utilize automatic data sources, such as smart-card transactions, GPS-based vehicle locations, cell phone records, and mobility apps to estimate and predict travel demand, explore behavioral patterns, quantify service reliability and evaluate transportation system performance as a whole.

Analyzing Passenger Incidence Behavior in Heterogeneous Transit Services Using Smartcard Data and Schedule-Based Assignment, Michael Frumin, and Jinhua Zhao , Journal of the Transportation Research Board, Volume 2274, p.52–60, (2012)

Passenger incidence (station arrival) behavior has been studied primarily to understand how changes to a transit service will affect passenger waiting times. The impact of one intervention (e.g., increasing frequency) could be overestimated when compared with another (e.g., improving reliability), depending on the assumption of incidence behavior. Understanding passenger incidence allows management decisions to be based on realistic behavioral assumptions. Earlier studies on passenger...

Estimating a Rail Passenger Trip Origin-Destination Matrix Using Automatic Data Collection Systems, Jinhua Zhao, Adam Rahbee, and Nigel Wilson , Computer-Aided Civil and Infrastructure Engineering, Volume 22, Issue 5, p.376–387, (2007)

Automatic data collection (ADC) systems are becoming increasingly common in transit systems throughout the world. Although these ADC systems are often designed to support specific fairly narrow functions, the resulting data can have wide-ranging application, well beyond their design purpose. This article illustrates the potential that ADC systems can provide transit agencies with new rich data sources at low marginal cost, as well as the critical gap between what ADC systems directly offer...



Abhishek Basu's picture
MST Student
Shan Jiang's picture
Postdoctoral Associate
Zelin Li's picture
MST/MCP Student
Corinna Li's picture
MCP-MST Student
Neema Nassir's picture
Assistant Professor at University of Melbourne
Tim Scully's picture
MST-ORC Student
Zhan Zhao's picture
PhD Candidate
Zhenliang Ma's picture
Postdoctoral Associate
Peyman Noursalehi's picture
Post-Doctoral Associate
Saeid Saidi's picture
Postdoctoral Fellow
Gabriel Wolofsky's picture
Master of Science in Transportation '19
Jinhua Zhao's picture
Edward H. and Joyce Linde Associate Professor