Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bibhas Kumar Dey"'
Publikováno v:
PLoS ONE, Vol 13, Iss 11, p e0208309 (2018)
The proposed research contributes to our understanding of incorporating heterogeneity in discrete choice models with respect to exogenous variables and decision rules. Specifically, the proposed latent segmentation based mixed models segment populati
Externí odkaz:
https://doaj.org/article/2f454542ccbc41f3a4a6346688c9ba11
Publikováno v:
Transportation Research Record: Journal of the Transportation Research Board. 2675:139-153
Given the burgeoning growth in transport networking companies (TNC)-based ride hailing systems and their growing adoption for trip making, it is important to develop modeling frameworks to understand TNC ride hailing demand flows at the system level.
Publikováno v:
Transportation Research Part A: Policy and Practice. 144:119-133
Given the burgeoning growth in bikeshare system installations and their growing adoption for trip making, it is important to develop modeling frameworks to understand bikeshare demand flows in the system. The current study examines two choice dimensi
Autor:
Nowreen Keya, Naveen Eluru, Salah Uddin Momtaz, Bibhas Kumar Dey, Sabreena Anowar, S. Frank Tabatabaee, Abdul Rawoof Pinjari
Publikováno v:
Journal of Transportation Engineering, Part A: Systems. 146
A major hurdle in freight demand modeling has always been the lack of adequate data on freight movements for different industry sectors for planning applications. Both Freight Analysis Fram...
Publikováno v:
Transportation Research Part C: Emerging Technologies. 129:103235
The proposed study contributes to our understanding of the ongoing transformation of ridehailing market by examining the New York City Taxi & Limousine Commission data from a fine spatial and temporal resolution. We examine taxi zone based demand dat
Publikováno v:
PLoS ONE, Vol 13, Iss 11, p e0208309 (2018)
PLoS ONE
PLoS ONE
The proposed research contributes to our understanding of incorporating heterogeneity in discrete choice models with respect to exogenous variables and decision rules. Specifically, the proposed latent segmentation based mixed models segment populati