TY - JOUR
T1 - Collective human mobility pattern from taxi trips in urban area
AU - Peng, Chengbin
AU - Jin, Xiaogang
AU - Wong, Ka Chun
AU - Shi, Meixia
AU - Liò, Pietro
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2012/4/18
Y1 - 2012/4/18
N2 - We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workplace to workplace, and others such as leisure activities. Therefore, traffic flow in one area or between any pair of locations can be approximated by a linear combination of three basis flows, corresponding to the three purposes respectively. We name the coefficients in the linear combination as traffic powers, each of which indicates the strength of each basis flow. The traffic powers on different days are typically different even for the same location, due to the uncertainty of the human motion. Therefore, we provide a probability distribution function for the relative deviation of the traffic power. This distribution function is in terms of a series of functions for normalized binomial distributions. It can be well explained by statistical theories and is verified by empirical data. These findings are applicable in predicting the road traffic, tracing the traffic pattern and diagnosing the traffic related abnormal events. These results can also be used to infer land uses of urban area quite parsimoniously. 2012 Peng et al.
AB - We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workplace to workplace, and others such as leisure activities. Therefore, traffic flow in one area or between any pair of locations can be approximated by a linear combination of three basis flows, corresponding to the three purposes respectively. We name the coefficients in the linear combination as traffic powers, each of which indicates the strength of each basis flow. The traffic powers on different days are typically different even for the same location, due to the uncertainty of the human motion. Therefore, we provide a probability distribution function for the relative deviation of the traffic power. This distribution function is in terms of a series of functions for normalized binomial distributions. It can be well explained by statistical theories and is verified by empirical data. These findings are applicable in predicting the road traffic, tracing the traffic pattern and diagnosing the traffic related abnormal events. These results can also be used to infer land uses of urban area quite parsimoniously. 2012 Peng et al.
UR - http://hdl.handle.net/10754/325304
UR - https://dx.plos.org/10.1371/journal.pone.0034487
UR - http://www.scopus.com/inward/record.url?scp=84859945418&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0034487
DO - 10.1371/journal.pone.0034487
M3 - Article
C2 - 22529917
SN - 1932-6203
VL - 7
SP - e34487
JO - PLoS ONE
JF - PLoS ONE
IS - 4
ER -