TY - JOUR
T1 - The dynamic optimization of the departure times of metro users during rush hour in an agent-based simulation
T2 - A Case study in Shenzhen, China
AU - Xi, Yuliang
AU - Du, Qingyun
AU - He, Biao
AU - Ren, Fu
AU - Zhang, Yu
AU - Ye, Xinyue
N1 - Funding Information:
We thank Tianqi Qiu, Yumiao Wang, Yanjun Qiao, Miss Shanshan Han and Yuan Wei for their help. In addition, this study is supported by the National Key Research and Development Programme of China (2016 YFC 0803106) and the National Natural Science Foundation of China (Project No. 41371427).
Publisher Copyright:
© 2017 by the authors.
PY - 2017/10/25
Y1 - 2017/10/25
N2 - As serious traffic problems have increased throughout the world, various types of studies, especially traffic simulations, have been conducted to investigate this issue. Activity-based traffic simulation models, such as MATSim (Multi-Agent Transport Simulation), are intended to identify optimal combinations of activities in time and space. It is also necessary to examine commuting-based traffic simulations. Such simulations focus on optimizing travel times by adjusting departure times, travel modes or travel routes to present travel suggestions to the public. This paper examines the optimal departure times of metro users during rush hour using a newly developed simulation tool. A strategy for identifying relatively optimal departure times is identified. This study examines 103,637 person agents (passengers) in Shenzhen, China, and reports their average departure time, travel time and travel utility, as well as the numbers of person agents who are late and miss metro trips in every iteration. The results demonstrate that as the number of iterations increases, the average travel time of these person agents decreases by approximately 4 min. Moreover, the latest average departure time with no risk of being late when going to work is approximately 8:04, and the earliest average departure time with no risk of missing metro trips when getting off work is approximately 17:50.
AB - As serious traffic problems have increased throughout the world, various types of studies, especially traffic simulations, have been conducted to investigate this issue. Activity-based traffic simulation models, such as MATSim (Multi-Agent Transport Simulation), are intended to identify optimal combinations of activities in time and space. It is also necessary to examine commuting-based traffic simulations. Such simulations focus on optimizing travel times by adjusting departure times, travel modes or travel routes to present travel suggestions to the public. This paper examines the optimal departure times of metro users during rush hour using a newly developed simulation tool. A strategy for identifying relatively optimal departure times is identified. This study examines 103,637 person agents (passengers) in Shenzhen, China, and reports their average departure time, travel time and travel utility, as well as the numbers of person agents who are late and miss metro trips in every iteration. The results demonstrate that as the number of iterations increases, the average travel time of these person agents decreases by approximately 4 min. Moreover, the latest average departure time with no risk of being late when going to work is approximately 8:04, and the earliest average departure time with no risk of missing metro trips when getting off work is approximately 17:50.
KW - Agent-based simulation
KW - Departure times
KW - Dynamic optimization
KW - Metro
KW - Rush hour
KW - Shenzhen
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U2 - 10.3390/app7111102
DO - 10.3390/app7111102
M3 - Article
AN - SCOPUS:85032476342
SN - 2076-3417
VL - 7
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 11
M1 - 1102
ER -