TY - GEN
T1 - A computational experiment method in ACP framework for complex urban traffic networks
AU - Chen, Yaran
AU - Lin, Shu
AU - Gangxiong,
AU - Kong, Qingjie
AU - Zhu, Fenghua
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/14
Y1 - 2014/11/14
N2 - Urban traffic congestion has already become an urgent problem. Artificial societies, Computational experiments, and Parallel execution (ACP) method is applied to urban traffic problems. In ACP framework, optimization for urban road networks achieves remarkable effect. Optimization for urban road networks is a problem of nonlinear and non-convex programming with typical large-scale continual and integer variables. Due to the complicated urban traffic system, this paper focuses on the ACP-based Computational experiments modeling. It hopes to find an optimization model that is further accord with the practical situation. To this end, we use a mixed integer nonlinear programming problem (MINLP) and an genetic algorithm (GA) for urban road networks optimization. The systemic simulation experiments show that the approach is more effective in improving traffic status and increasing traffic safety.
AB - Urban traffic congestion has already become an urgent problem. Artificial societies, Computational experiments, and Parallel execution (ACP) method is applied to urban traffic problems. In ACP framework, optimization for urban road networks achieves remarkable effect. Optimization for urban road networks is a problem of nonlinear and non-convex programming with typical large-scale continual and integer variables. Due to the complicated urban traffic system, this paper focuses on the ACP-based Computational experiments modeling. It hopes to find an optimization model that is further accord with the practical situation. To this end, we use a mixed integer nonlinear programming problem (MINLP) and an genetic algorithm (GA) for urban road networks optimization. The systemic simulation experiments show that the approach is more effective in improving traffic status and increasing traffic safety.
UR - http://www.scopus.com/inward/record.url?scp=84937119855&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2014.6958154
DO - 10.1109/ITSC.2014.6958154
M3 - Conference Proceeding
AN - SCOPUS:84937119855
T3 - 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
SP - 2894
EP - 2899
BT - 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
Y2 - 8 October 2014 through 11 October 2014
ER -
