A mean-field Markov decision process model for spatial-temporal subsidies in ride-sourcing markets
Ride-sourcing services are increasingly popular because of their ability to accommodate on-
demand travel needs. A critical issue faced by ride-sourcing platforms is the supply-demand …
demand travel needs. A critical issue faced by ride-sourcing platforms is the supply-demand …
Traffic flow forecast through time series analysis based on deep learning
J Zheng, M Huang - IEEE Access, 2020 - ieeexplore.ieee.org
Traffic congestion is a thorny issue to many large and medium-sized cities, posing a serious
threat to sustainable urban development. Recently, intelligent traffic system (ITS) has …
threat to sustainable urban development. Recently, intelligent traffic system (ITS) has …
Competition between the transportation network company and the government with subsidies to public transit riders
The substitution and complement of ride-sourcing services and public transit services greatly
affect the mobility and accessibility of a multi-modal transportation system. Since the …
affect the mobility and accessibility of a multi-modal transportation system. Since the …
Analysis of multi-modal commute behavior with feeding and competing ridesplitting services
Public transit is an essential travel mode in many urban areas. Emerging dynamic
ridesplitting programs provided by transportation network companies (TNCs) can be a …
ridesplitting programs provided by transportation network companies (TNCs) can be a …
Modeling indoor-level non-pharmaceutical interventions during the COVID-19 pandemic: A pedestrian dynamics-based microscopic simulation approach
Mathematical modeling of epidemic spreading has been widely adopted to estimate the
threats of epidemic diseases (ie, the COVID-19 pandemic) as well as to evaluate epidemic …
threats of epidemic diseases (ie, the COVID-19 pandemic) as well as to evaluate epidemic …
Estimating the influence of disruption on highway networks using GPS data
Z Yang, F Liu, Z Gao, H Sun, J Zhao, D Janssens… - Expert Systems with …, 2022 - Elsevier
Incidents, such as natural disasters, public events, and holidays, often cause problems to
highways, even paralyze the operation of the whole networks, leading to a serious threat to …
highways, even paralyze the operation of the whole networks, leading to a serious threat to …
A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process
The disruption of critical components in a transportation network can bring about severe
network performance degradation and requires a relatively long period to recover, which …
network performance degradation and requires a relatively long period to recover, which …
Integrating probabilistic tensor factorization with Bayesian supervised learning for dynamic ridesharing pattern analysis
In the era of transportation big data, the analysis of mobility patterns generally involves large
quantities of datasets with high-dimensional variables recording individual travelers' …
quantities of datasets with high-dimensional variables recording individual travelers' …
Capturing the interaction between travel time reliability and route choice behavior based on the generalized Bayesian traffic model
Travel time reliability plays an important role in travelers' route choice behaviors. Based on a
previously developed generalized Bayesian traffic model, we propose different types of …
previously developed generalized Bayesian traffic model, we propose different types of …
[HTML][HTML] Optimization of multi-type sensor locations for simultaneous estimation of origin-destination demands and link travel times with covariance effects
This paper investigates the multi-type traffic sensor location problem for simultaneous
estimation of origin-destination (OD) demands and link travel times while also considering …
estimation of origin-destination (OD) demands and link travel times while also considering …