A computational experiment method in ACP framework for complex urban traffic networks

Yaran Chen; Shu Lin; Gangxiong; Qingjie Kong; Fenghua Zhu

doi:10.1109/ITSC.2014.6958154

A computational experiment method in ACP framework for complex urban traffic networks

Yaran Chen
, Shu Lin
, Gangxiong
, Qingjie Kong
, Fenghua Zhu

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

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.

Original language	English
Title of host publication	2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2894-2899
Number of pages	6
ISBN (Electronic)	9781479960781
DOIs	https://doi.org/10.1109/ITSC.2014.6958154
Publication status	Published - 14 Nov 2014
Externally published	Yes
Event	2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 - Qingdao, China Duration: 8 Oct 2014 → 11 Oct 2014

Publication series

Name	2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014

Conference

Conference	2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
Country/Territory	China
City	Qingdao
Period	8/10/14 → 11/10/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities

Access to Document

10.1109/ITSC.2014.6958154

Cite this

Chen, Y., Lin, S., Gangxiong, Kong, Q., & Zhu, F. (2014). A computational experiment method in ACP framework for complex urban traffic networks. In 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 (pp. 2894-2899). Article 6958154 (2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2014.6958154

Chen, Yaran ; Lin, Shu ; Gangxiong et al. / A computational experiment method in ACP framework for complex urban traffic networks. 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 2894-2899 (2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014).

@inproceedings{2d742735cfca4384ad7e6126bc39dbb8,

title = "A computational experiment method in ACP framework for complex urban traffic networks",

abstract = "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.",

author = "Yaran Chen and Shu Lin and Gangxiong and Qingjie Kong and Fenghua Zhu",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 ; Conference date: 08-10-2014 Through 11-10-2014",

year = "2014",

month = nov,

day = "14",

doi = "10.1109/ITSC.2014.6958154",

language = "English",

series = "2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2894--2899",

booktitle = "2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014",

}

Chen, Y, Lin, S, Gangxiong, Kong, Q & Zhu, F 2014, A computational experiment method in ACP framework for complex urban traffic networks. in 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014., 6958154, 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014, Institute of Electrical and Electronics Engineers Inc., pp. 2894-2899, 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014, Qingdao, China, 8/10/14. https://doi.org/10.1109/ITSC.2014.6958154

A computational experiment method in ACP framework for complex urban traffic networks. / Chen, Yaran; Lin, Shu; Gangxiong et al.
2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2894-2899 6958154 (2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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

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 - https://www.scopus.com/pages/publications/84937119855

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M3 - Conference Proceeding

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T3 - 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014

SP - 2894

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ER -

Chen Y, Lin S, Gangxiong, Kong Q, Zhu F. A computational experiment method in ACP framework for complex urban traffic networks. In 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 2894-2899. 6958154. (2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014). doi: 10.1109/ITSC.2014.6958154

A computational experiment method in ACP framework for complex urban traffic networks

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