基于巢式Logit模型广州市居民车牌选择行为研究
发布时间：2018-11-29 13:28
【摘要】：广州市是全国唯一在汽车限购后没有进行外地车限行的城市。由于这一特殊性,广州市居民选择摇号、竞拍或者外地牌。基于限购数据及基于选项的采样问卷调查数据,分析广州市居民车牌选择行为,建立基于居民车牌选择的巢式Logit模型,将广州居民在周边城市上牌作为选项之一,并利用加权及基于选项的最大似然法(WESML)对模型的参数进行估计,定量分析居民收入、需求迫切度、对本地车牌的认知价值等因素对居民决策产生的影响。结果表明:采用的模型和方法要优于传统的多项Logit模型及一般的极大似然法,能够更加贴切的描述和预测居民的选择行为。
[Abstract]:Guangzhou is the only city in the country after the car purchase restrictions have not been carried out outside the city. As a result of this particularity, Guangzhou residents choose to shake, auction or foreign card. Based on the limited purchase data and the sampling questionnaire data based on options, this paper analyzes the behavior of license plate selection of Guangzhou residents, establishes a nested Logit model based on residents license plate selection, and takes Guangzhou residents as one of the options for listing in neighboring cities. The parameters of the model are estimated by using the weighted and option-based maximum likelihood method (WESML) to quantitatively analyze the influence of residents' income, demand urgency and the cognitive value of local license plate on the residents' decision-making. The results show that the proposed model and method are superior to the traditional multi-item Logit model and the general maximum likelihood method, and can more accurately describe and predict the residents' choice behavior.
【作者单位】： 中山大学工学院广东省智能交通系统(ITS)重点实验室;
【基金】：广东省科技计划项目(2015B010110005)
【分类号】：U491.1
本文编号：2365121
[Abstract]:Guangzhou is the only city in the country after the car purchase restrictions have not been carried out outside the city. As a result of this particularity, Guangzhou residents choose to shake, auction or foreign card. Based on the limited purchase data and the sampling questionnaire data based on options, this paper analyzes the behavior of license plate selection of Guangzhou residents, establishes a nested Logit model based on residents license plate selection, and takes Guangzhou residents as one of the options for listing in neighboring cities. The parameters of the model are estimated by using the weighted and option-based maximum likelihood method (WESML) to quantitatively analyze the influence of residents' income, demand urgency and the cognitive value of local license plate on the residents' decision-making. The results show that the proposed model and method are superior to the traditional multi-item Logit model and the general maximum likelihood method, and can more accurately describe and predict the residents' choice behavior.
【作者单位】： 中山大学工学院广东省智能交通系统(ITS)重点实验室;
【基金】：广东省科技计划项目(2015B010110005)
【分类号】：U491.1
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