87 citations · 255 across the 21 of their papers we have counts for
5 papers · 1 filter
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…
Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks
Shenhao Wang, Baichuan Mo, Jinhua Zhao
Researchers often treat data-driven and theory-driven models as two disparate or even conflicting methods in travel behavior analysis. However, the two methods are highly complemen…
Modeling Epidemic Spreading through Public Transit using Time-Varying Encounter Network
Baichuan Mo, Kairui Feng, Yu Shen +4
Passenger contact in public transit (PT) networks can be a key mediate in the spreading of infectious diseases. This paper proposes a time-varying weighted PT encounter network to…
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…
Competition between shared autonomous vehicles and public transit: A case study in Singapore
Baichuan Mo, Zhejing Cao, Hongmou Zhang +2
Emerging autonomous vehicles (AV) can either supplement the public transportation (PT) system or compete with it. This study examines the competitive perspective where both AV and…