Bus Capacity Estimation using Stochastic Queuing Models for Isolated Bus Stops in China Academic Article uri icon


  • National Academy of Sciences: Transportation Research Board 2018. When serving passengers at a bus stop, a dwelling bus may cause a bottleneck that constrains traffic flow near the bus stop. A major element in bus system capacity is bus stop capacity (veh/h). Therefore, this study proposes a method estimating the capacity of bus stops isolated from the influences of traffic signals and other bus stops. Data collected for the seven most common bus stop configurations in China were used to validate the proposed model. The results indicated that the arrival process obeys a Poisson distribution and the service times fit a lognormal distribution. Stochastic queuing models for both single-berth and multi-berth stops were developed to estimate bus stop capacity and bus delay time. To enable comparison, the Highway Capacity Manual (HCM) model for bus stop capacity estimation was also used. The results showed that the proposed method was more accurate and reliable, with a mean absolute percentage error (MAPE) of 8.44% compared with a MAPE of 17.42% from the HCM method. In addition, the proposed method reduced root mean squared error (RMSE) by 58.8%, mean absolute error (MAE) by 57.9%, and variance of absolute percentage error (VAPE) by 52.6% compared with the values from the HCM model. Sensitivity analyses were also conducted to investigate the effects of bus arrival rate, bus service time, and the number of bus berths on the capacity of bus stops. The results indicated that the proposed method can be used as a guide for designing bus stop facilities under specified conditions.

published proceedings

  • Transportation Research Record Journal of the Transportation Research Board

author list (cited authors)

  • Wang, C., Ye, Z., Fricker, J. D., Zhang, Y., & Ukkusuri, S. V.

citation count

  • 10

complete list of authors

  • Wang, Chao||Ye, Zhirui||Fricker, Jon D||Zhang, Yunlong||Ukkusuri, Satish V

publication date

  • December 2018