Modeling Bus Capacity for Bus Stops Using Queuing Theory and Diffusion Approximation

被引:3
|
作者
Wang, Chao [1 ,2 ,3 ,4 ]
Chen, Weijie [1 ,2 ,3 ,4 ]
Xu, Yueru [3 ,5 ]
Ye, Zhirui [1 ,2 ,3 ,4 ]
机构
[1] Southeast Univ, Jiangsu Key Lab Urban ITS, Nanjing, Peoples R China
[2] Jiangsu Prov Collaborat Innovat Ctr Modern Urban, Nanjing, Peoples R China
[3] Southeast Univ, Sch Transportat, Nanjing, Peoples R China
[4] Southeast Univ, Natl Demonstrat Ctr Expt Rd & Traff Engn Educ, Nanjing, Peoples R China
[5] Southeast Univ, Intelligent Transportat Syst Res Ctr, Nanjing, Peoples R China
基金
中国国家自然科学基金;
关键词
Bus terminals - Bus transportation - Buses - Diffusion - Highway engineering - Poisson distribution - Queueing networks - Queueing theory - Traffic control;
D O I
10.1177/03611981211030257
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
For bus service quality and line capacity, one critical influencing factor is bus stop capacity. This paper proposes a bus capacity estimation method incorporating diffusion approximation and queuing theory for individual bus stops. A concurrent queuing system between public transportation vehicles and passengers can be used to describe the scenario of a bus stop. For most of the queuing systems, the explicit distributions of basic characteristics (e.g., waiting time, queue length, and busy period) are difficult to obtain. Therefore, the diffusion approximation method was introduced to deal with this theoretical gap in this study. In this method, a continuous diffusion process was applied to estimate the discrete queuing process. The proposed model was validated using relevant data from seven bus stops. As a comparison, two common methods-Highway Capacity Manual (HCM) formula and M/M/S queuing model (i.e., Poisson arrivals, exponential distribution for bus service time, and S number of berths)-were used to estimate the capacity of the bus stop. The mean absolute percentage error (MAPE) of the diffusion approximation method is 7.12%, while the MAPEs of the HCM method and M/M/S queuing model are 16.53% and 10.23%, respectively. Therefore, the proposed model is more accurate and reliable than the others. In addition, the influences of traffic intensity, bus arrival rate, coefficient of variation of bus arrival headway, service time, coefficient of variation of service time, and the number of bus berths on the capacity of bus stops are explored by sensitivity analyses.
引用
收藏
页码:598 / 609
页数:12
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