摘要
为克服传统车道边容量评估方法应用于多航站楼机场时数据采集困难的问题,基于数据采
集容易、计算精度高的原则,利用时空消耗理论建立了车道边容量模型。首先,建立了单一车型
运行下的容量模型;其次,分析了混合车流运行情况,通过参数标定,建立了基于时空消耗理论
的多航站楼车道边容量模型;再次,利用现场调查数据,将模型应用于天津机场T1 和T2 航站楼
车道边,结果表明,目前天津机场车道边流量仅为其容量的1/3 左右,大量资源处于闲置状态;
最后,依据实际情况给出几点车道边容量提升策略。利用该模型能够在仅利用基础设施的基础数
据的情况下,快速、准确地计算出多航站楼机场车道边的总容量,并能够根据时空消耗理论证明
公共交通的运载能力远大于私家车或出租车,机场相关部门可据此采取相应措施。
Abstract
When traditional curbside capacity evaluation method is applied to multiple terminals air⁃
port, the problem of data acquisition comes. In order to overcome the problem, based on the principle of
easily getting data and getting high calculation precision, the curbside capacity evaluation model was es⁃
tablished by using the theory of space and time consumption. Firstly, evaluation model under the opera⁃
tion of single vehicle was established. Secondly, the mixed traffic running situation was analyzed and ca⁃
pacity evaluation model of multiple terminals curbside was established through the parameter calibra⁃
tion. Thirdly, the model was applied in T1 and T2 terminal curbside of Tianjin airport with field survey
data. The results show that the flow rate in Tianjin airport curbside is only about a third of its capacity,
which means vast resource is being wasted. Finally, some capacity improvement strategies were given ac⁃
cording to the actual situation. Using this model, the terminal curbside capacity could be calculated
more quickly and accurately on the basis of infrastructure data only. And that the capacity of public
transportation is larger than private car or taxi could be proved from the view of space and time consump⁃
tion theory. All above reminds that related departments should take corresponding measures accordingly.
关键词
机场 /
车道边 /
容量评估 /
航站楼 /
时空消耗理论
Key words
airport /
curbside /
capacity evaluation /
terminal /
time and space consumption theory
王茹.
基于时空消耗理论的多航站楼机场车道边
容量评估[J]. 交通运输研究. 2016, 2(2): 53-58
WANG Ru.
Capacity Evaluation on Curbside of Multiple Terminals Airport
Based on Theory of Time and Space Consumption[J]. Transport Research. 2016, 2(2): 53-58
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