This research presents an analysis of travel mode choice for trips to Ho Chi Minh City metro station. Research methods were inherited through a formula to calculate passenger traffic forecasts to predict passengers, g...This research presents an analysis of travel mode choice for trips to Ho Chi Minh City metro station. Research methods were inherited through a formula to calculate passenger traffic forecasts to predict passengers, going to the station. Based on the collected data of interviews, traffic surveys, and "Irwin & Von Cube" function, forecast the proportion of travel mode, and use to go to the station and leaving from the station. The results of study are used for the purpose of calculating the size of the metro station parking lots and parking layout plan.展开更多
绿色出行引导效果受外部信息及出行者选择偏好影响,需要考虑出行者潜在属性类别的异质性。自我呈现表现为人们通过控制与自己有关的信息来影响他人对自己的印象,体现了信息与选择偏好的交互作用。为定量分析出行者自我呈现意识和环保意...绿色出行引导效果受外部信息及出行者选择偏好影响,需要考虑出行者潜在属性类别的异质性。自我呈现表现为人们通过控制与自己有关的信息来影响他人对自己的印象,体现了信息与选择偏好的交互作用。为定量分析出行者自我呈现意识和环保意识对出行方式选择行为的影响,本文通过问卷调查收集到1382份有效样本,利用潜在类别模型(Latent Class Model,LCM)将出行者划分为高自我呈现组(18.23%)、中自我呈现组(20.26%)和低自我呈现组(61.51%)。离散选择模型的结果表明,出行者在进行方式选择时更关注出行时间和出行方式自身的特性,若不考虑方式特性,会高估出行费用对高自我呈现组的影响。高自我呈现组仅在短距离出行中对公共交通有强烈偏好,对于6~10 km的出行,选择私家车倾向明显。中短距离的出行中,低自我呈现组对骑行的偏好价值可以在一定程度上抵消过长出行时间带来的负效用。构建考虑出行者异质性的方式选择模型,可为政府和相关部门制定更协调、有针对性的交通调控政策及公共交通运营策略提供理论依据。展开更多
文摘This research presents an analysis of travel mode choice for trips to Ho Chi Minh City metro station. Research methods were inherited through a formula to calculate passenger traffic forecasts to predict passengers, going to the station. Based on the collected data of interviews, traffic surveys, and "Irwin & Von Cube" function, forecast the proportion of travel mode, and use to go to the station and leaving from the station. The results of study are used for the purpose of calculating the size of the metro station parking lots and parking layout plan.
文摘绿色出行引导效果受外部信息及出行者选择偏好影响,需要考虑出行者潜在属性类别的异质性。自我呈现表现为人们通过控制与自己有关的信息来影响他人对自己的印象,体现了信息与选择偏好的交互作用。为定量分析出行者自我呈现意识和环保意识对出行方式选择行为的影响,本文通过问卷调查收集到1382份有效样本,利用潜在类别模型(Latent Class Model,LCM)将出行者划分为高自我呈现组(18.23%)、中自我呈现组(20.26%)和低自我呈现组(61.51%)。离散选择模型的结果表明,出行者在进行方式选择时更关注出行时间和出行方式自身的特性,若不考虑方式特性,会高估出行费用对高自我呈现组的影响。高自我呈现组仅在短距离出行中对公共交通有强烈偏好,对于6~10 km的出行,选择私家车倾向明显。中短距离的出行中,低自我呈现组对骑行的偏好价值可以在一定程度上抵消过长出行时间带来的负效用。构建考虑出行者异质性的方式选择模型,可为政府和相关部门制定更协调、有针对性的交通调控政策及公共交通运营策略提供理论依据。