TY - JOUR
T1 - Crowded urban traffic
T2 - co-evolution among land development, population, roads and vehicle ownership
AU - Li, Rong
AU - Wu, Jianjun
AU - Liu, Hao
AU - Gao, Ziyou
AU - Sun, Huijun
AU - Ding, Rui
AU - Tang, Tieqiao
N1 - Publisher Copyright:
© 2019, Springer Nature B.V.
PY - 2019/3/1
Y1 - 2019/3/1
N2 - Crowded urban traffic is one of mankind’s greatest past, present, and future challenges, attracting interests from urban planning, urban geography, urban economics and other related disciplines. Although these fields provide some insight into the problem, our understanding of the basic laws determining urban traffic systems’ evolutionary trajectory remains limited given that we do not fully understand the general co-evolutionary mechanisms underlying their complex dynamics. Therefore, a better understanding of the dynamics of urban traffic systems is necessary. The evolution of urban traffic systems appears to be accessible through mathematical descriptions, which involves land development, population, road and motor vehicle subsystems. In this paper, a four-level co-evolution dynamics model is developed to capture the growth trajectory of urban traffic systems. Our aim is to determine the driving force of urban traffic growth, the interactions among the studied subsystems, and whether the “disease” of urban crowding can be effectively predicted. Stability analysis indicates that this model is convergent. Taking two typical Chinese cities (Beijing and Shenzhen) as case studies, it is found that this model can be used to capture the observed co-evolution characteristics and to predict the future development of crowded urban traffic, thus benefitting all cities’ planning and control processes.
AB - Crowded urban traffic is one of mankind’s greatest past, present, and future challenges, attracting interests from urban planning, urban geography, urban economics and other related disciplines. Although these fields provide some insight into the problem, our understanding of the basic laws determining urban traffic systems’ evolutionary trajectory remains limited given that we do not fully understand the general co-evolutionary mechanisms underlying their complex dynamics. Therefore, a better understanding of the dynamics of urban traffic systems is necessary. The evolution of urban traffic systems appears to be accessible through mathematical descriptions, which involves land development, population, road and motor vehicle subsystems. In this paper, a four-level co-evolution dynamics model is developed to capture the growth trajectory of urban traffic systems. Our aim is to determine the driving force of urban traffic growth, the interactions among the studied subsystems, and whether the “disease” of urban crowding can be effectively predicted. Stability analysis indicates that this model is convergent. Taking two typical Chinese cities (Beijing and Shenzhen) as case studies, it is found that this model can be used to capture the observed co-evolution characteristics and to predict the future development of crowded urban traffic, thus benefitting all cities’ planning and control processes.
KW - Co-evolution dynamics model
KW - Crowded urban traffic
KW - Traffic carrying capacity
UR - https://www.scopus.com/pages/publications/85059335708
U2 - 10.1007/s11071-018-4722-z
DO - 10.1007/s11071-018-4722-z
M3 - 文章
AN - SCOPUS:85059335708
SN - 0924-090X
VL - 95
SP - 2783
EP - 2795
JO - Nonlinear Dynamics
JF - Nonlinear Dynamics
IS - 4
ER -