This study aims to explore the role of spatial heterogeneity in ridership analysis and examine the relationship between built environment, station attributes and urban rapid transit ridership at the station level.Alth...This study aims to explore the role of spatial heterogeneity in ridership analysis and examine the relationship between built environment, station attributes and urban rapid transit ridership at the station level.Although spatial heterogeneity has been widely acknowledged in spatial data analysis, it has been rarely considered in travel behavior studies.Four models(three global models-ordinary least squares(OLS), spatial lag model(SLM), spatial error model(SEM) and one local model-geographically weighted regression(GWR) model) are estimated separately to explore the relationship between various independent variables and station ridership, and identify the influence of spatial heterogeneity.Using the data of built environment and station characteristics, the results of diagnostic identify evidence the existence of spatial heterogeneity in station ridership for the metro network in Nanjing, China.Results of comparing the various goodness-of-fit indicators show that, the GWR model yields the best fit of the data, performance followed by the SEM, SLM and OLS model.The results also demonstrate that population, number of lines, number of feeder buses, number of exits, road density and proportion residential area have a significant impact on station ridership.Moreover, the study pays special attention to the spatial variation in the coefficients of the independent variables and their statistical significance.It underlines the importance of taking spatial heterogeneity into account in the station ridership analysis and the decision-making in urban planning.展开更多
Supernetworks have long been adopted to address multi-dimensional choice problems, which are thorny to solve for classic singular networks. Originated from combining transport mode and route choice into a multi-modal ...Supernetworks have long been adopted to address multi-dimensional choice problems, which are thorny to solve for classic singular networks. Originated from combining transport mode and route choice into a multi-modal network, supernetworks have been extended into multi-state networks to include activity-travel scheduling, centered around activity-based models of travel demand. A key feature of the network extensions is that multiple choice facets pertaining to conducting a full activity program can be modeled in a consistent and integrative fashion. Thus, interdependencies and constraints between related choice facets can be readily captured. Given this advantage of integrity, the modeling of supernetwork has become an emerging topic in transportation research. This paper summarizes the recent progress in modeling multi-state supernetworks and discusses future prospects.展开更多
Organizing schedules and allocating time to different activities is always a challenge in dual-earner households,especially when they have children.Parents may need to link their schedule to those of their children to...Organizing schedules and allocating time to different activities is always a challenge in dual-earner households,especially when they have children.Parents may need to link their schedule to those of their children to allow them escorting their children to school or to take care or be with their children at home.This paper reports the results of an analysis of the degree of synchronization of home departure and arrival times in dual earner households with children,where the degree of synchronization is defined as the gap between departure and arrival times of a parent and child.Using activity-travel diary data of different household members,a random parameters regression model is estimated to examine differences in time gaps in home departure and arrival times between parents and children as a function of gender,day of the week,age of the youngest child,and other socio-demographic characteristics.The results of the analysis provide insight into factors influencing the degree of synchronization and coordination of double activity-travel scheduling decisions in households with children.Findings indicate that gender,number of children in the household,age of the youngest child,travel within or outside peak hours,day of the week,transport mode used for the work commute and household income level significantly affect time gaps,especially arrival time gaps.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.71771049)the Six Talent Peaks Project in Jiangsu Province(No.2016-JY-003)China Scholarship Council(No.201606090149)
文摘This study aims to explore the role of spatial heterogeneity in ridership analysis and examine the relationship between built environment, station attributes and urban rapid transit ridership at the station level.Although spatial heterogeneity has been widely acknowledged in spatial data analysis, it has been rarely considered in travel behavior studies.Four models(three global models-ordinary least squares(OLS), spatial lag model(SLM), spatial error model(SEM) and one local model-geographically weighted regression(GWR) model) are estimated separately to explore the relationship between various independent variables and station ridership, and identify the influence of spatial heterogeneity.Using the data of built environment and station characteristics, the results of diagnostic identify evidence the existence of spatial heterogeneity in station ridership for the metro network in Nanjing, China.Results of comparing the various goodness-of-fit indicators show that, the GWR model yields the best fit of the data, performance followed by the SEM, SLM and OLS model.The results also demonstrate that population, number of lines, number of feeder buses, number of exits, road density and proportion residential area have a significant impact on station ridership.Moreover, the study pays special attention to the spatial variation in the coefficients of the independent variables and their statistical significance.It underlines the importance of taking spatial heterogeneity into account in the station ridership analysis and the decision-making in urban planning.
文摘Supernetworks have long been adopted to address multi-dimensional choice problems, which are thorny to solve for classic singular networks. Originated from combining transport mode and route choice into a multi-modal network, supernetworks have been extended into multi-state networks to include activity-travel scheduling, centered around activity-based models of travel demand. A key feature of the network extensions is that multiple choice facets pertaining to conducting a full activity program can be modeled in a consistent and integrative fashion. Thus, interdependencies and constraints between related choice facets can be readily captured. Given this advantage of integrity, the modeling of supernetwork has become an emerging topic in transportation research. This paper summarizes the recent progress in modeling multi-state supernetworks and discusses future prospects.
文摘Organizing schedules and allocating time to different activities is always a challenge in dual-earner households,especially when they have children.Parents may need to link their schedule to those of their children to allow them escorting their children to school or to take care or be with their children at home.This paper reports the results of an analysis of the degree of synchronization of home departure and arrival times in dual earner households with children,where the degree of synchronization is defined as the gap between departure and arrival times of a parent and child.Using activity-travel diary data of different household members,a random parameters regression model is estimated to examine differences in time gaps in home departure and arrival times between parents and children as a function of gender,day of the week,age of the youngest child,and other socio-demographic characteristics.The results of the analysis provide insight into factors influencing the degree of synchronization and coordination of double activity-travel scheduling decisions in households with children.Findings indicate that gender,number of children in the household,age of the youngest child,travel within or outside peak hours,day of the week,transport mode used for the work commute and household income level significantly affect time gaps,especially arrival time gaps.
