50 citations · 140 across the 20 of their papers we have counts for
20 papers
Reconstructing Transit Vehicle Trajectory Using High-Resolution GPS Data
Yuzhu Huang, Awad Abdelhalim, Anson Stewart +2
High-resolution location ("heartbeat") data of transit fleet vehicles is a relatively new data source for many transit agencies. On its surface, the heartbeat data can provide a we…
Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks
Qingyi Wang, Shenhao Wang, Dingyi Zhuang +2
Recent studies have significantly improved the prediction accuracy of travel demand using graph neural networks. However, these studies largely ignored uncertainty that inevitably…
Passenger Path Choice Estimation Using Smart Card Data: A Latent Class Approach with Panel Effects Across Days
Baichuan Mo, ZhenLiang Ma, Haris N. Koutsopoulos +1
Understanding passengers' path choice behavior in urban rail systems is a prerequisite for effective operations and planning. This paper attempts bridging the gap by proposing a pr…
Modeling Virus Transmission Risks in Commuting with Emerging Mobility Services: A Case Study of COVID-19
Baichuan Mo, Peyman Noursalehi, Haris N. Koutsopoulos +1
Commuting is an important part of daily life. With the gradual recovery from COVID-19 and more people returning to work from the office, the transmission of COVID-19 during commuti…
Bulk Service Queueing for Transit Resilience under Short Random Service Suspensions
Baichuan Mo, Li Jin, Zhengzhong Ricky You +3
Short service suspensions are common in public transit systems, but their operational impacts remain difficult to quantify. We develop an analytical framework for measuring the res…
Individual Path Recommendation Under Public Transit Service Disruptions Considering Behavior Uncertainty
Baichuan Mo, Haris N. Koutsopoulos, Zuo-Jun Max Shen +1
Public transit passengers need guidance during service disruptions. This study proposes an individual-based path (IPR) recommendation model. The model decides which paths to recomm…
An Integrated Ride-Matching Model for Shared Mobility on Demand Services
Kerem Tuncel, Haris N. Koutsopoulos, Zhenliang Ma
Shared mobility on demand (MoD) services are receiving increased attention as many high volume ride-hailing companies are offering shared services (e.g. UberPool, LyftLine) at an i…
Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks
Dingyi Zhuang, Shenhao Wang, Haris N. Koutsopoulos +1
Origin-Destination (O-D) travel demand prediction is a fundamental challenge in transportation. Recently, spatial-temporal deep learning models demonstrate the tremendous potential…
Dynamic Interlining in Bus Operations
Seyedmostafa Zahedi, Haris N. Koutsopoulos, Zhenliang Ma
The paper introduces and evaluates the concept of the dynamic interlining of buses. Dynamic interlining is an operational strategy for routes that have a terminal station at a comm…
Transit Frequency Setting Problem with Demand Uncertainty
Xiaotong Guo, Baichuan Mo, Haris N. Koutsopoulos +2
Public transit systems are the backbone of urban mobility systems in the era of urbanization. The design of transit schedules is important for the efficient and sustainable operati…
Schedule-based Analysis of Transmission Risk in Public Transportation Systems
Jiali Zhou, Haris N. Koutsopoulos
Airborne diseases, including COVID-19, raise the question of transmission risk in public transportation systems. However, quantitative analysis of the effectiveness of transmission…
Robust Path Recommendations During Public Transit Disruptions Under Demand Uncertainty
Baichuan Mo, Haris N. Koutsopoulos, Max Zuo-Jun Shen +1
When there are significant service disruptions in public transit systems, passengers usually need guidance to find alternative paths. This paper proposes a path recommendation mode…
Identifying Hidden Visits from Sparse Call Detail Record Data
Zhan Zhao, Haris N. Koutsopoulos, Jinhua Zhao
Despite a large body of literature on trip inference using call detail record (CDR) data, a fundamental understanding of their limitations is lacking. In particular, because of the…
Individual Mobility Prediction: An Interpretable Activity-based Hidden Markov Approach
Baichuan Mo, Zhan Zhao, Haris N. Koutsopoulos +1
Individual mobility is driven by demand for activities with diverse spatiotemporal patterns, but existing methods for mobility prediction often overlook the underlying activity pat…
Calibrating Path Choices and Train Capacities for Urban Rail Transit Simulation Models Using Smart Card and Train Movement Data
Baichuan Mo, Zhenliang Ma, Haris N. Koutsopoulos +1
Transit network simulation models are often used for performance and retrospective analysis of urban rail systems, taking advantage of the availability of extensive automated fare…
Near-on-Demand Mobility. The Benefits of User Flexibility for Ride-Pooling Services
Zhenliang Ma, Haris N. Koutsopoulos
Mobility-On-Demand (MoD) services have been transforming the urban mobility ecosystem. However, they raise a lot of concerns for their impact on congestion, Vehicle Miles Travelled…
Virus Transmission Risk in Urban Rail Systems: A Microscopic Simulation-based Analysis of Spatio-temporal Characteristics
Jiali Zhou, Haris N. Koutsopoulos
Transmission risk of air-borne diseases in public transportation systems is a concern. The paper proposes a modified Wells-Riley model for risk analysis in public transportation sy…
Assignment-based Path Choice Estimation for Metro Systems Using Smart Card Data
Baichuan Mo, Zhenliang Ma, Haris N. Koutsopoulos +1
Urban rail services are the principal means of public transportation in many cities. To understand the crowding patterns and develop efficient operation strategies in the system, o…
Profiling presence patterns and segmenting user locations from cell phone data
Yan Leng, Haris Koutsopoulos, Jinhua Zhao
The dynamic monitoring of commuting flows is crucial for improving transit systems in fast-developing cities around the world. However, existing methodology to infer commuting orig…
Real-time Predictive Analytics for Improving Public Transportation Systems' Resilience
Peyman Noursalehi, Haris N. Koutsopoulos
Public transit systems are a critical component of major metropolitan areas. However, in the face of increasing demand, most of these systems are operating close to capacity. Under…