Public Transportation Management

A robust public transit network is an integral part of an urban transportation system. Together with the MIT Transit Lab, we merge behavioral science and systems engineering to determine how to improve the flow of passengers on mass transit, better understand demand, and offer policy solutions to transit agencies to help them respond to emerging challenges in this space.

Please click on the following links to learn more about our specific transit agency partnerships: Transport for London, Chicago Transit Authority, Hong Kong MTA

Discovering Latent Activity Patterns from Transit Smart Card Data: A Spatiotemporal Topic Model, Zhan Zhao, Haris N. Koutsopoulos, and Jinhua Zhao , Transportation Research Part C, (2020)

Although automatically collected human travel records can accurately capture the time and location of human
movements, they do not directly explain the hidden semantic structures behind the data, e.g., activity types. This work
proposes a probabilistic topic model, adapted from Latent Dirichlet Allocation (LDA), to discover representative and
interpretable activity categorization from individual-level spatiotemporal data in an unsupervised manner. Specifically,

Capacity-Constrained Network Performance Model for Urban Rail Systems, Baichuan Mo, Zhenliang Ma, Haris N. Koutsopoulos, and Jinhua Zhao , Transportation Research Record, (2020)

This paper proposes a general Network Performance Model (NPM) for urban rail systems performance monitoring using smart card data. NPM is a schedule-based network loading model with strict capacity constraints and boarding priorities. It distributes passengers over the network given origin-destination (OD) demand, operations, route choice, and effective train capacity. A Bayesian simulation-based optimization method for calibrating the effective train capacity is introduced, which explicitly...

How does Ridesourcing Substitute for Public Transit? A geospatial perspective in Chengdu, China, Kong, Hui, Xiaohu Zhang, and Jinhua Zhao , Journal of Transport Geography, (2020)

The explosive growth of ridesourcing services has stimulated a debate on whether they represent a net substitute for or a complement to public transit. Among the empirical evidence that supports discussion of the net effect at the city level, analysis at the disaggregated level from a geospatial perspective is lacking. It remains unexplored the spatiotemporal pattern of ridesourcing’s effect on public transit, and the factors that impact the effect. Using DiDi Chuxing data in Chengdu, China...

Demand Management of Congested Public Transport Systems: A Conceptual Framework and Application Using Smart Card Data, Anne Halvorsen, Haris N. Koutsopoulos, Zhenliang Ma, and Jinhua Zhao , Transportation, (2019)

Transportation Demand Management (TDM), long used to reduce car traffic, is receiving attention among public transport operators as a means to reduce congestion in crowded public transportation systems. Though far less studied, a more structured approach to Public Transport Demand Management (PTDM) can help agencies make informed decisions on the combination of PTDM and infrastructure investments that best manage crowding. Automated fare collection (AFC) data, readily available in many...

Bayesian Inference of Passenger Boarding Strategies at Express Stops with Real-Time Bus Arrival Information, Neema Nassir, Jinhua Zhao, Frederick P. Salvucci, John Attanucci, and Nigel Wilson , Transportation Research Board 97th Annual Meeting, Washington, DC, (2018)

Efficient design of express and local bus services in urban corridors requires accurate understanding of the travel demand and heterogeneities in passengers’ preferences and needs. Public transit Automated Fare Collection (AFC) systems provide a high-coverage source of data that facilitates an unprecedented opportunity for understanding the demand patterns and passenger preferences for more efficient service designs.In this paper, a Bayesian inference method is proposed to analyze the AFC...

Individual mobility prediction using transit smart card data, Zhan Zhao, Haris N. Koutsopoulos, and Jinhua Zhao , Transportation Research Part C, Volume 89, p.19-34, (2018)

For intelligent urban transportation systems, the ability to predict individual mobility is crucial for personalized traveler information, targeted demand management, and dynamic system operations. Whereas existing methods focus on predicting the next location of users, little is known regarding the prediction of the next trip. The paper develops a methodology for predicting daily individual mobility represented as a chain of trips (including the null set, no travel), each defined as a...

Detecting Pattern Changes in Individual Travel Behavior: A Bayesian Approach, Zhan Zhao, Haris N. Koutsopoulos, and Jinhua Zhao , Transportation Research Part B, (2018)

Although stable in the short term, individual travel patterns are subject to changes in the long term. The ability to detect such changes is critical for developing behavior models that are adaptive over time. We define travel pattern change as "abrupt, substantial, and persistent changes in the underlying pattern of travel behavior" and develop a methodology to detect such changes in individual travel patterns. We specify one distribution for each of the three dimensions of travel behavior...

Integrating Shared Autonomous Vehicle in Public Transportation System: A Supply-Side Simulation of the First-Mile Service in Singapore, Yu Shen, Hongmou Zhang, and Jinhua Zhao , Transportation Research Part A, (2018)

This paper proposes and simulates an integrated autonomous vehicle (AV) and public transportation (PT) system. After discussing the attributes of and the interaction among the prospective stakeholders in the system, we identify opportunities for synergy between AVs and the PT system based on Singapore’s organizational structure and demand characteristics. Envisioning an integrated system in the context of the first-mile problem during morning peak hours, we propose to preserve high demand...

Real time transit demand prediction capturing station interactions and impact of special events, Peyman Noursalehi, Haris N. Koutsopoulos, and Jinhua Zhao , Transportation Research Part C, (2018)

Demand for public transportation is highly affected by passengers’ experience and the level of service provided. Thus, it is vital for transit agencies to deploy adaptive strategies to respond to changes in demand or supply in a timely manner, and prevent unwanted deterioration in service quality. In this paper, a real time prediction methodology, based on univariate and multivariate state-space models, is developed to predict the short-term passenger arrivals at transit stations. A...

Demand Management in Public Transportation: A Framework and Application, Anne Halvorsen, Koutsopoulos Haris, Zhenliang Ma, and Jinhua Zhao , Working paper, (2018)

Transportation demand management (TDM), long used to reduce car traffic, receives increasing attention as means to ease congestion in overcrowded public transit systems. A more structured approach to transit-specific TDM can help agencies find better combinations of demand management and infrastructure investments to satisfy customer need. This paper develops a framework for public transportation demand management (PTDM) including problem identification and formulating program goals, program...

Mobility as A Language: Predicting Individual Mobility In Public Transportation Using N-Gram Models, Zhan Zhao, Koutsopoulos Haris, and Jinhua Zhao , Transportation Research Board 96th Annual Meeting, (2017)

For public transportation agencies, the ability to provide personalized and dynamic passenger information is crucial for improving the efficiency of demand management and enhancing customer experience. This requires understanding and especially predicting individual travel behavior in the public transportation system, which is challenging because of the heterogeneity among passengers and the variability of their behaviors. This paper presents, to the best of our knowledge, the first attempt...

Simulating the First Mile Service to Access Train Stations by Shared Autonomous Vehicle, Yu Shen, Hongmou Zhang, and Jinhua Zhao , Transportation Research Board 96th Annual Meeting, (2017)

This paper studies the potential impacts of autonomous vehicle (AV) sharing with mobility-on demand service on the public transit system. We analyze the current travel demand in the public transit system in Singapore with a special focus on the first-/last-mile problem during morning peak hours. The first-/last-mile in this paper is defined as the gap between origin/destination and the heavy rail stations. A feasible method to integrate AV sharing in current transit system is proposed, which...

Incorporating Mobile Activity Tracking Data In A Transit Agency: Collecting, Comparing, And Trip Mode Inference, Tim Scully, John Attanucci, and Jinhua Zhao , Transportation Research Board 96th Annual Meeting, (2017)

The near ubiquity of smartphones has the potential to transform how researchers, companies, and public transit agencies understand travel behavior. This research analyzes how an emerging class of automatically-collected data based on smartphone GPS and sensor information – referred to here as mobile activity-tracking data – can be used in a transit agency to better understand travel behavior. Through a collaboration with Transport for London, multiple weeks of mobile activity-tracking data...

Worse than Baumol's disease: The implications of labor productivity, contracting out, and unionization on transit operation costs, Javier Morales-Sarriera, Frederick Salvucci, and Jinhua Zhao , Transport Policy, 10/2017, Volume 61, p.10-16, (2017)

Unit costs measured as bus operating costs per vehicle mile have increased considerably above the inflation rate in recent decades in most transit agencies in the United States. This paper examines the impact of (lack of) productivity growth, union bargaining power, and contracting out on cost escalation. We draw from a 17-year (1997–2014) and a 415-bus transit agency panel with 5780 observations by type of operation (directly operated by the agency or contracted out). We have three main...

Redesigning Subway Map to Mitigate Bottleneck Congestion: An Experiment in Washington DC Using Mechanical Turk, Zhan Guo, Jinhua Zhao, Chris Whong, Prachee Mishra, and Lance Wyman , Transportation Research Part A, Volume 106, p.158–169, (2017)

This paper explores the possibility of using subway maps as a planning tool to influence passenger route choice to mitigate congestion. Specifically, it tests whether extending the appearance of an overcrowded subway line on the Washington DC subway map would encourage passengers to use other underutilized lines. The experiment was conducted through the Mechanical Turk, a crowdsourcing platform, with 3056 participants, producing 21,240 route choice decisions on the official and six...

Measuring Regularity of Individual Travel Patterns, Gabriel Goulet-Langlois, Haris N. Koutsopoulos, Zhan Zhao, and Jinhua Zhao , IEEE Transactions on Intelligent Transportation Systems, (2017)

Regularity is an important property of individual travel behavior, and the ability to measure it enables advances in behavior modeling, mobility prediction, and customer analytics. In this paper, we propose a methodology to measure travel behavior regularity based on the order in which trips or activities are organized. We represent individuals’ travel over multiple days as sequences of “travel events”—discrete and repeatable behavior units explicitly defined based on the research question...

Measuring Explicit and Implicit Social Status Bias in Car vs. Bus Mode Choice, Joanna Moody, Gabriel Goulet Langlois, Lauren Alexander, Jonathan Campbell, and Jinhua Zhao , 95th Transportation Research Board Annual Meeting, 08/2015, Washington, D.C., (2016)

With results from an Implicit Association Test (IAT) and sociodemographic, travel behavior, and Likert-scale survey questions, we investigate implicit and explicit social status biases in the context of mode choice between car and bus. Using a novel two-part experimental design, the differences between implicit and explicit measures of bias are examined to understand how the IAT may complement or improve upon traditional survey methods to capture attitudinal biases. We find that explicit...

FMS-TQ: Combining Smartphone and iBeacon 4 Technologies in A Transit Quality Survey, Corinna Li, Christopher Zegras, Fang Zhao, Francisco Pereira, Kalan Vishwanath Nawarathne, Zhengquan Qin, Moshe Ben-Akiva, and Jinhua Zhao , 95th Transportation Research Board Annual Meeting, Washington, D.C., (2016)

The Internet of Things (IoT) will offer transit agencies an opportunity to transform ways to measure, monitor, and manage performance. We demonstrate the potential value of two combined technologies, smartphones and iBeacons, for actively engaging customers in measuring satisfaction and co-monitoring bus service quality. Specifically, we adapt our smartphone-based survey system, Future Mobility Sensing (FMS), to connect with iBeacons for an event-driven approach to measure user-reported...

A Ride to Remember: Experienced vs. Remembered Emotion on Public Transit, Nate Bailey, Timothy Patton Doyle, Tolulope Ogunbekun, and Jinhua Zhao , 95th Transportation Research Board Annual Meeting, 08/2015, Washington, D.C., (2016)

Prior research has shown disconnects between the subjective well-being a person experiences during an event and the subjective well-being the same individual remembers once the event has passed. Despite the differences that exist between experience and memory, memory is often used as a basis for making decisions about the future. Measures of utility in transportation decision models have begun to incorporate concepts of subjective well-being. A better understanding of the differences between...

Uncertainty in Bus Arrival Time Predictions: Treating Heteroscedasticity With a Metamodel Approach, Aidan O'Sullivan, Francisco Pereira, Jinhua Zhao, and Harilaos Koutsopoulos , IEEE Transactions on Intelligent Transportation Systems, Issue 99, p.1–11, (2016)

Arrival time predictions for the next available bus or train are a key component of modern Traveller Information Systems (TIS). A great deal of research has been conducted within the ITS community developing an assortment of different algorithms that seek to increase the accuracy of these predictions. However, the inherent stochastic and non-linear nature of these systems, particularly in the case of bus transport, means that these predictions suffer from variable sources of error, stemming...

Reducing Subway Crowding: Analysis of an Off-peak Discount Experiment in Hong Kong, Anne Halvorsen, Koutsopoulos Haris, and Jinhua Zhao , Transportation Research Record: Journal of the Transportation Research Board, Washington, D.C., (2016)

Increases in ridership are outpacing capacity expansions in a number of transit systems. By shifting their focus to demand management, agencies can instead influence how customers use the system, getting more out of the capacity they already have. This paper uses Hong Kong's MTR system as a case study to explore the effects of crowding-reduction strategies as well as methods to use automatically collected fare data to support these measures. MTR introduced a pre-peak discount in September...

Inferring patterns in the multi-week activity sequences of public transport users, Gabriel Goulet Langlois , Transportation Research Part C: Emerging Technologies, Volume 64, p.1-16, (2016)

The public transport networks of dense cities such as London serve passengers with widely different travel patterns. In line with the diverse lives of urban dwellers, activities and journeys are combined within days and across days in diverse sequences. From personalized customer information, to improved travel demand models, understanding this type of heterogeneity among transit users is relevant to a number of applications core to public transport agencies’ function. In this study,...

Agglomeration and Diversification: Bi-Level Analysis of 15-Years' Impacts of Madrid-Seville High-Speed Rail, Yu Shen, João de Abreu e Silva, Jinhua Zhao, and Luis Miguel Martínez , Transportation Research Board 94th Annual Meeting, Washington, D.C., (2015)

This paper studies the impacts of Madrid-Seville High-Speed Rail (HSR) on population growth and land cover change in the five HSR connected cities - Madrid, Ciudad Real, Puertollano, Cordoba, and Seville - at both regional and local level. The analysis period ranges from 1991 to 2006. The study finds that, at regional level, the population growth and land development process concentrate mostly towards the two largest cities, Madrid and Seville, while other smaller HSR served cities are also...

Capacity Constrained Accessibility of High-Speed Rail, Yu Shen, and Jinhua Zhao , Transportation, p.1–28, (2015)

This paper proposes an enhanced measure of accessibility that explicitly considers circumstances in which the capacity of the transport infrastructure is limited. Under these circumstances, passengers may suffer longer waiting times, resulting in the delay or cancellation of trips. Without considering capacity constraints, the standard measure overestimates the accessibility contribution of transport infrastructure. We estimate the expected waiting time and the probability of forgoing trips...

Smart Devices and Travel Time Use by Bus Passengers in Vancouver, Canada, Zhan Guo, Alexandra Derian, and Jinhua Zhao , International Journal of Sustainable Transportation, Volume 9, Issue 5, p.335–347, (2015)

This research investigates the usage of smart devices and time at bus stops and on buses in Vancouver, Canada. Using passive observations and self-reported surveys mainly from college students, the majority of passengers were found to use their travel time actively. Most of the observed active activities are associated with the usage of smart devices. However, while the possession of smart devices is prevalent, less than one third of passengers used them during travel. A variety of...

Hysteresis and Urban Rail: The Effects of Past Urban Rail on Current Residential and Travel Choices, David Block-Schachter, and Jinhua Zhao , European Journal of Transport and Infrastructure Research, Volume 15, Issue 1, p.78–91, (2015)

Cities are endowed with and accumulate natural and constructed assets based on their unique histories, which in turn define the choice set of the present. But, common practice is that current behaviour can be described without reference to past circumstances. This work departs from that practice by examining the effects of historical urban rail on current residential location and travel behaviour, from the era of horsecars (1865) and streetcars (1925) to the present in Boston. It uses tract...

Customer Loyalty Differences Between Captive and Choice Transit Riders, Jinhua Zhao, Valerie Webb, and Punit Shah , Journal of the Transportation Research Board, Volume 2415, p.80–88, (2014)

Traditionally, efforts to increase the customer base of public transportation agencies have focused primarily on attracting first-time users. Customer retention, however, has many benefits not often realized. Loyal customers provide recommendations to others, increase and diversify their use of the service, and do not require acquisition costs associated with new customers. An earlier study identified key drivers of customer loyalty, with the Chicago Transit Authority (CTA) in Illinois as a...

Quantity and Quality of Productive Use of Transit Commuting Time: A Heckman Model, Jinhua Zhao, Alison Lung, and Zhan Guo , Transportation Research Board 92nd Annual Meeting, Washington, D.C., (2013)

In North America, the average individual taking public transportation spends about 45 minute commuting one way each day. This equates to about 398 hours per year and thus ways to reduce travel time are imperative. Rather than attempting to reduce travel time directly, changing the perspective of how commuting time is spent by improving the productive use of time provides a more cost effective solution. This paper explored and measured the extent that bus commuters are currently using their...

Unified Estimator for Excess Journey Time under Heterogenous Passenger Incidence Behavior using Smartcard Data, Jinhua Zhao, Michael Frumin, Nigel Wilson, and Zhan Zhao , Transportation Research Part C, Volume 34, p.70–88, (2013)

Excess journey time (EJT), the difference between actual passenger journey times and journey times implied by the published timetable, strikes a useful balance between the passenger’s and operator’s perspectives of public transport service quality. Using smartcard data, this paper tried to characterize transit service quality with EJT under heterogeneous incidence behavior (arrival at boarding stations). A rigorous framework was established for analyzing EJT, in particular for reasoning...

Automatic Data for Applied Railway Management: A Case Study on the London Overground, Michael Frumin, Jinhua Zhao, Nigel Wilson, and Zhan Zhao , Journal of the Transportation Research Board, Volume 2353, p.47–56, (2013)

In 2009, London Overground management implemented a new tactical plan for a.m. and p.m. peak service on the North London Line (NLL). This paper documents that tactical planning intervention and evaluates its outcomes in terms of certain aspects of service delivery (the operator's perspective on system performance) and service quality (the passenger's perspective). Analyses of service delivery and quality and of passenger demand contributed to the development, proposal, and implementation of...

Potential and Reality of Using High Speed Rail for Commuting in Yangtze River Delta, Cindy Tse, Jinhua Zhao, and Jessie Wang , IEEE/ASCE/ASME Joint Rail Conference, Philadelphia, (2012)

This paper focuses the current and potential impact of Huning High Speed Railway (H-N HSR) on commuting patterns in the Yangtze River Delta region. We will examine 1) to what extent commuting via HSR is occurring, since the HSR system is very new and is a substantial and long-term decision for people to move for a job or home across cities; 2) the future potential of commuting via the HSR perceived by current HSR passengers to relocate for a job or relocate their home and their preferences...

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...

The Potential Impact of Automated Data Collection Systems on Urban Public Transport Planning, Nigel Wilson, Jinhua Zhao, and Adam Rahbee , Schedule-Based Modeling of Transportation Networks: Theory and Applications, p.75–99, (2009)

Automated data collection systems are becoming increasingly common in urban public transport systems, both in the US and throughout the developed world. These systems, which include Automatic Vehicle Location (AVL), Automatic Passenger Counting (APC), and Automatic Fare Collection (AFC), are often designed to support specific and fairly narrow functions within the transport agency. However, it is clear that the data obtained from these systems can have wide-ranging applications within public...

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...

Public Transit Team Members

Abhishek Basu's picture
MST Student
Anne Halvorsen's picture
MST Student
Corinna Li's picture
MCP-MST Student
Javier Morales Sarriera's picture
Neema Nassir's picture
Assistant Professor at University of Melbourne
Adam Rosenfield's picture
MST/MCP Student
Jeffrey Rosenblum's picture
PhD Candidate
Jian Wen's picture
MST Student
Zhan Zhao's picture
PhD Candidate
Leo Chen's picture
MST Student
Mary Rose Fissinger's picture
PhD Candidate
Gabriel Goulet-Langlois's picture
MST 2015
Zhenliang Ma's picture
Postdoctoral Associate
Ru Mehendale's picture
Baichuan Mo's picture
PhD Candidate
Peyman Noursalehi's picture
Post-Doctoral Associate
Saeid Saidi's picture
Postdoctoral Fellow
Anson Stewart's picture
Research Scientist
Gabriel Wolofsky's picture
Master of Science in Transportation '19
Jinhua Zhao's picture
Edward H. and Joyce Linde Associate Professor