Departure Time and Mode Choice for the Morning Commute in a Highway/Railway Network

2009 ◽  
Author(s):  
Wen-Xiang Wu ◽  
Hai-Jun Huang
Keyword(s):  
Mode Choice ◽  
Railway Network ◽  
Departure Time ◽  
Morning Commute

A mixed Bayesian network for two-dimensional decision modeling of departure time and mode choice

2017 ◽  
Vol 45 (5) ◽  
pp. 1499-1522 ◽  
Author(s):  
Zheng Zhu ◽  
Xiqun Chen ◽  
Chenfeng Xiong ◽  
Lei Zhang
Keyword(s):  
Bayesian Network ◽  
Mode Choice ◽  
Decision Modeling ◽  
Two Dimensional ◽  
Departure Time

scholarly journals A Departure Time Choice for Morning Commute Considering Train Capacity of a Rail Transit Line

2013 ◽  
Vol 5 ◽  
pp. 582703 ◽  
Author(s):  
Jia Feng ◽  
Baohua Mao ◽  
Zhijie Chen ◽  
Yun Bai ◽  
Minggao Li
Keyword(s):  
Rail Transit ◽  
Departure Time ◽  
Departure Time Choice ◽  
Morning Commute

scholarly journals Joint Analysis of the Commuting Departure Time and Travel Mode Choice: Role of the Built Environment

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Xiaolei Ma ◽  
Jie Yang ◽  
Chuan Ding ◽  
Jianfeng Liu ◽  
Quan Zhu
Keyword(s):  
Built Environment ◽  
Socioeconomic Factors ◽  
Public Transit ◽  
Mode Choice ◽  
Joint Analysis ◽  
Mobile Source ◽  
Travel Mode ◽  
Study Region ◽  
Travel Mode Choice ◽  
Departure Time

This paper aims to conduct an empirical study to evaluate the influence of built environment features and socioeconomic factors on commuters’ simultaneous choice of departure time and travel mode. Using Kunming, China, as the study region, the 2015 Regional Household Travel Survey and 2016 Point of Interest data are used in the analysis. The results show that, in addition to socioeconomic factors, built environment, such as the density of residential building, employment, and service facility are correlated with joint choice behavior. Moreover, there exist differences regarding the influence of built environment and socioeconomic factors on departure time and travel mode choice. The dissimilarity parameters show that commuters prefer to shift travel mode than departure time generally when travel condition alters. In order to examine the policy measures’ potential performance, the paper conducts simulation tests based on the Monte Carlo method. The simulation results show that congestion pricing of car travel during peak hours can reduce the number of commuting trips, and reducing travel time of public transit would be a better strategy to attract more passengers during peak hours. Moreover, reasonable land use planning, such as building more bus stops around commuters’ home location, would be a long term and fundamental approach to reduce mobile-source emissions and attract more public transit passengers.

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