基于路段交通流状态的车辆燃油消耗的测算与分析

发布时间：2018-01-25 01:18

本文关键词： 车速分布行驶工况仿真分析 k-means聚类线性回归　出处：《合肥工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：近年来随着我国汽车保有量的不断增长,城市化进程的持续加快,交通方面的能耗在社会总能耗所占的比例逐年增高,其中城市快速路承担着日益繁重的交通压力,快速路交通流已经成为重要的燃油消耗和污染排放源头,针对此问题,本文依托于国家自然科学基金“低碳导向型城市交通系统优化与管理”,以合肥市快速路路段为研究对象,确定了路段油耗与速度数据采集的试验方案。本文在大量的路段断面车速与试验车车速、油耗数据的基础上,首先,运用统计学方法对城市快速路的车速分布特征及影响因素进行了分析研究,分别从分布的类型、集中趋势、离散趋势三方面对上述两类(断面车速与路段车速)试验数据进行了分布特征分析及相互关系对比,在此基础上进行了影响因素的研究,研究结果表明,车辆行驶时所处的车道位置以及交通流状态对车速分布特征有着不同程度的影响,在一定的条件下,断面车速与路段车速的分布特征趋于相同;其次,基于断面车速与路段车速的分布特征趋于相同这一原理,采用随机法构建行驶工况,并采用CARSIM仿真软件测得新建工况的油耗数据,接着运用k-means聚类算法和双行驶特征区分路段交通状况,最后采用线性回归方法构建了路段基于交通流状态的油耗预测模型,并对模型进行了验证,得出以下结论:在快速路路段不同交通流状态下,该模型可以作为预测车辆行驶时燃油消耗的有效手段。本文对快速路路段燃油消耗的研究成果丰富了车速理论及燃油经济性的研究内容,将对城市快速路的规划、管理、设计、控制以及评价提供数据支持和理论依据。
[Abstract]:In recent years, with the continuous growth of automobile ownership and the acceleration of urbanization in China, the proportion of energy consumption in transportation in the total social energy consumption is increasing year by year. Among them, the urban expressway is bearing the increasingly heavy traffic pressure, the expressway traffic flow has become an important source of fuel consumption and pollution emissions, aiming at this problem. This paper is based on the National Natural Science Foundation of China "low carbon oriented urban transportation system optimization and management", taking Hefei expressway as the research object. The experimental scheme of fuel consumption and speed data acquisition is determined. Firstly, based on a large number of section speed and vehicle speed and fuel consumption data. The characteristics of the speed distribution and the influencing factors of the urban expressway were analyzed by using the statistical method, respectively from the distribution type, the concentration trend. Discrete trend three aspects of the above two kinds of (cross-section speed and road speed) test data distribution characteristics analysis and correlation comparison, on the basis of the study of influencing factors, the results show that. The driveway position and the traffic flow state of the vehicle have different effects on the speed distribution. Under certain conditions, the distribution characteristics of the cross-section speed tend to be the same as that of the road section. Secondly, based on the principle that the distribution characteristics of cross-section speed and road speed tend to be the same, the random method is used to construct the driving conditions, and the fuel consumption data of the newly built working conditions are measured by CARSIM simulation software. Then we use k-means clustering algorithm and dual driving characteristics to distinguish the traffic conditions of road sections. Finally, we use linear regression method to build the fuel consumption prediction model based on traffic flow state, and verify the model. The following conclusions are drawn: under different traffic flow conditions of expressway section. This model can be used as an effective method to predict the fuel consumption of vehicles. The research results of this paper enrich the speed theory and fuel economy research content. To provide data support and theoretical basis for urban expressway planning, management, design, control and evaluation.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U471.23;U491

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