Probabilistic model for remain passenger queues at subway station platform
来源期刊：中南大学学报(英文版)2013年第3期
论文作者：XU Xin-yue(许心越) LIU Jun(刘军) 李海鹰 ZHOU Yan-fang(周艳芳)
文章页码：837 - 844
Key words：subway; platform; remain passenger; queuing theory; probabilistic theory; Markov chain
Abstract: The remain passenger problem at subway station platform was defined initially, and the period variation of remain passenger queues at platform was investigated through arriving and boarding analyses. Taking remain passenger queues at platform as dynamic stochastic process, a new probabilistic queuing method was developed based on probabilistic theory and discrete time Markov chain theory. This model can calculate remain passenger queues while considering different directions. Considering the stable or variable train arriving period and different platform crossing types, a series of model deformation research was carried out. The probabilistic approach allows to capture the cyclic behavior of queues, measures the uncertainty of a queue state prediction by computing the evolution of its probability in time, and gives any temporal distribution of the arrivals. Compared with the actual data, the deviation of experimental results is less than 20%, which shows the efficiency of probabilistic approach clearly.
XU Xin-yue(许心越)1,2, LIU Jun(刘军) 2, LI Hai-ying(李海鹰) 1, ZHOU Yan-fang(周艳芳)2
(1. State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University, Beijing 100044, China;
2. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)
Abstract:The remain passenger problem at subway station platform was defined initially, and the period variation of remain passenger queues at platform was investigated through arriving and boarding analyses. Taking remain passenger queues at platform as dynamic stochastic process, a new probabilistic queuing method was developed based on probabilistic theory and discrete time Markov chain theory. This model can calculate remain passenger queues while considering different directions. Considering the stable or variable train arriving period and different platform crossing types, a series of model deformation research was carried out. The probabilistic approach allows to capture the cyclic behavior of queues, measures the uncertainty of a queue state prediction by computing the evolution of its probability in time, and gives any temporal distribution of the arrivals. Compared with the actual data, the deviation of experimental results is less than 20%, which shows the efficiency of probabilistic approach clearly.
Key words:subway; platform; remain passenger; queuing theory; probabilistic theory; Markov chain
