Abstract:

With increasing of the vehicles and deteriorating of the environment, controlling the use of vehicle fuel has become one of the important measures in Beijing transport energy saving and emission reduction. The private vehicle energy-consumption cannot count from the whole sample, because there have too large number and the adding oil for the private vehicle is subjective. It only can count from the sampling survey method. Therefore, in order to obtain the reliable data of fuel consumption which accurately reflects the city's private vehicle energy consumption, it is necessary to explore the key factors of energy consumption and design a scientific stratified sampling framework. based on the data of Beijing private vehicle energy consumption survey, this paper constructs a econometric regression model to study the key determinants of energy consumption of private vehicle. This paper proposes the stratified sampling frame and threshold divided model through introducing the dummy variables which uses in econometrics, eventually form a stratified sampling framework.

Key words: urban traffic, stratified sampling survey, econometric model, private vehicle, key influence factors, traffic energy-consumption

摘要：

随着车辆保有量的不断上涨，环境的不断恶化，控制车用燃油已成为北京市交通领域节能减排工作的重要措施之一.私人小客车作为车用燃油的主要用户，由于数量庞大，消费自主性较强，目前无法采用全样统计的方式获取其燃油消耗，仅能依靠抽样的方式，利用样本推算其整体燃油消耗.因此，为获取可靠的燃油消耗样本，准确反映全市私人小客车燃油消耗水平，明确能耗显著影响因素和设计科学的分层抽样框架成为了关键.本文利用北京市现有私人小客车能耗调查数据，通过构建计量回归模型分析私人小客车能耗关键影响因素；利用计量学中引入虚拟变量的处理方法，提出了分层抽样框设计原理和阈值划分模型，最终形成分层抽样框架.

关键词: 城市交通, 分层抽样方法, 经济计量模型, 私人小客车, 关键影响因素, 交通能耗