{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T11:15:05Z","timestamp":1763810105816,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T00:00:00Z","timestamp":1571616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61104166"],"award-info":[{"award-number":["61104166"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>This paper proposes a model predictive control method based on dynamic multi-objective optimization algorithms (MPC_CPDMO-NSGA-II) for reducing freeway congestion and relieving environment impact simultaneously. A new dynamic multi-objective optimization algorithm based on clustering and prediction with NSGA-II (CPDMO-NSGA-II) is proposed. The proposed CPDMO-NSGA-II algorithm is used to realize on-line optimization at each control step in model predictive control. The performance indicators considered in model predictive control consists of total time spent, total travel distance, total emissions and total fuel consumption. Then TOPSIS method is adopted to select an optimal solution from Pareto front obtained from MPC_CPDMO-NSGA-II algorithm and is applied to the VISSIM environment. The control strategies are variable speed limit (VSL) and ramp metering (RM). In order to verify the performance of the proposed algorithm, the proposed algorithm is tested under the simulation environment originated from a real freeway network in Shanghai with one on-ramp. The result is compared with fixed speed limit strategy and single optimization method respectively. Simulation results show that it can effectively alleviate traffic congestion, reduce emissions and fuel consumption, as compared with fixed speed limit strategy and classical model predictive control method based on single optimization method.<\/jats:p>","DOI":"10.3390\/a12100220","type":"journal-article","created":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T11:37:55Z","timestamp":1571657875000},"page":"220","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Freeway Traffic Congestion Reduction and Environment Regulation via Model Predictive Control"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0631-8370","authenticated-orcid":false,"given":"Juan","family":"Chen","sequence":"first","affiliation":[{"name":"SHU-UTS SILC Business School, Shanghai University, Shanghai 201899, China"},{"name":"Smart City Research Institute, Shanghai University, Shanghai 201899, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxuan","family":"Yu","sequence":"additional","affiliation":[{"name":"SHU-UTS SILC Business School, Shanghai University, Shanghai 201899, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Guo","sequence":"additional","affiliation":[{"name":"SHU-UTS SILC Business School, Shanghai University, Shanghai 201899, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.trc.2013.01.002","article-title":"Integrated macroscopic traffic flow, emission, and fuel consumption model for control purposes","volume":"31","author":"Zegeye","year":"2013","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.trc.2014.06.005","article-title":"Hybrid model predictive control for freeway traffic using discrete speed limit signals","volume":"46","author":"Frejo","year":"2014","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1016\/S0005-1098(99)00214-9","article-title":"Constrained model predictive control: Stability and optimality","volume":"36","author":"Mayne","year":"2000","journal-title":"Automatica"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1016\/j.conengprac.2005.03.010","article-title":"Model predictive control for ramp metering of motorway traffic: A case study","volume":"14","author":"Bellemans","year":"2006","journal-title":"Control Eng. Pract."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Frejo, J.R.D., N\u00fanez, A., De Schutter, B., and Camacho, E.F. (2013, January 17\u201319). Model predictive control for freeway traffic using discrete speed limit signals. Proceedings of the 2013 Control Conference (ECC), Zurich, Switzerland.","DOI":"10.23919\/ECC.2013.6669682"},{"key":"ref_6","first-page":"111","article-title":"Coordinated Traffic Control for Urban Expressway Based on Model Predictive Control","volume":"33","author":"Ding","year":"2016","journal-title":"J. Highw. Transp. Res. Dev."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Hu, L., Sun, W., and Wang, H. (2013, January 12\u201314). An extended model predictive control approach to coordinated ramp metering. Proceedings of the 2013 10th IEEE International Conference on Control and Automation (ICCA), Hangzhou, China.","DOI":"10.1109\/ICCA.2013.6564996"},{"key":"ref_8","unstructured":"Long, K.J., Yun, M.P., Zheng, J.L., and Yang, X. (2008, January 16\u201318). Model predictive control for variable speed limit in freeway work zone. Proceedings of the 2008 27th Chinese Control Conference, Kunming, China."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zheng, T., Wu, G., Liu, G.H., and Ling, Q. (2010). Multi-Objective Nonlinear Model Predictive Control: Lexicographic Method. Model Predictive Control, InTechOpen.","DOI":"10.5772\/9919"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zegeye, S.K., De Schutter, B., Hellendoorn, H., and Breunesse, E. (2009, January 10\u201312). Reduction of travel times and traffic emissions using model predictive control. Proceedings of the American Control Conference, St. Louis, MO, USA.","DOI":"10.1109\/ACC.2009.5159942"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1109\/TITS.2016.2573306","article-title":"Model Predictive Control for Freeway Networks Based on Multi-Class Traffic Flow and Emission Models","volume":"18","author":"Liu","year":"2017","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"10703","DOI":"10.3182\/20110828-6-IT-1002.01546","article-title":"Nonlinear MPC for the improvement of dispersion of freeway traffic emissions","volume":"44","author":"Zegeye","year":"2011","journal-title":"IFAC Proc. Vol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.trd.2016.08.013","article-title":"Real-time route diversion control in a model predictive control framework with multiple objectives: Traffic efficiency, emission reduction and fuel economy","volume":"48","author":"Luo","year":"2016","journal-title":"Transp. Res. Part D Transp. Environ."},{"key":"ref_14","unstructured":"Li, G., and Xie, B.L. (2017). Intelligent Integrated Control System of Expressway Based on MPC, China Public Security. Academy Edition."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/4235.996017","article-title":"A fast and elitist multiobjective genetic algorithm: NSGA-II","volume":"6","author":"Deb","year":"2002","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.procs.2013.10.028","article-title":"Dynamic multiobjective optimization using evolutionary algorithm with Kalman filter","volume":"24","author":"Muruganantham","year":"2013","journal-title":"Procedia Comput. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Hatzakis, I., and Wallace, D. (2006, January 8\u201312). Dynamic multi-objective optimization with evolutionary algorithms: A forward-looking approach. Proceedings of the Conference on Genetic and Evolutionary Computation, Washington, DC, USA.","DOI":"10.1145\/1143997.1144187"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zhou, A., Jin, Y., and Zhang, Q. (2007). Prediction-Based Population Re-Initialization for Evolutionary Dynamic Multi-Objective Optimization. Evolutionary Multi-Criterion Optimization, Springer.","DOI":"10.1007\/978-3-540-70928-2_62"},{"key":"ref_19","first-page":"677","article-title":"Predictive multiobjective genetic algorithm for dynamic multiobjective problmes","volume":"28","author":"Wu","year":"2013","journal-title":"Control Decis."},{"key":"ref_20","first-page":"56","article-title":"A Dynamic Multi-Objective Evolutionary Algorithm Based on Cluster Prediction Model","volume":"37","author":"Zhou","year":"2014","journal-title":"J. Nat. Sci. Hunan Norm. Univ."},{"key":"ref_21","unstructured":"Xu, Z.S. (2004). Uncertain Multiple Attribute Decision Making: Methods and Applications, Tsinghua University Press."},{"key":"ref_22","unstructured":"Ahn, K., Trani, A.A., Rakha, H., and Van Aerde, M. (1999, January 10\u201314). Microscopic fuel consumption and emission models. Proceedings of the 78th Annual Meeting of the Transportation Research Board, Washington, DC, USA. CD-ROM."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1021\/ed085p218","article-title":"Using the Relationship between Vehicle Fuel Consumption and CO2 Emissions to Illustrate Chemical Principles","volume":"85","author":"Pinto","year":"2008","journal-title":"J. Chem. Educ."},{"key":"ref_24","first-page":"313","article-title":"Dynamic Multi-Objective Optimization Algorithm Based on Reference Point Prediction","volume":"43","author":"Jin","year":"2017","journal-title":"Acta Autom. Sin."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ishibuchi, H., Masuda, H., Tanigaki, Y., and Nojima, Y. (2015, January 9\u201312). Difficulties in specifying reference points to calculate the inverted generational distance for many-objective optimization problems. Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM), Orlando, FL, USA.","DOI":"10.1109\/MCDM.2014.7007204"},{"key":"ref_26","first-page":"221","article-title":"Variable Speed Limit for Freeway under Rain Weather Based on Cell Transmission Model","volume":"14","author":"Zhang","year":"2014","journal-title":"J. Transp. Syst. Eng. Inf. Technol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"648","DOI":"10.1049\/iet-its.2013.0131","article-title":"Online evaluation of an integrated control strategy at on-ramp bottleneck for urban expressways in Shanghai","volume":"8","author":"Sun","year":"2014","journal-title":"IET Intell. Transp. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/S0045-7825(99)00389-8","article-title":"An efficient constraint handling method for genetic algorithms","volume":"186","author":"Deb","year":"2000","journal-title":"Comput. Methods Appl. Mech. Eng."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/12\/10\/220\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:28:11Z","timestamp":1760189291000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/12\/10\/220"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,21]]},"references-count":28,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2019,10]]}},"alternative-id":["a12100220"],"URL":"https:\/\/doi.org\/10.3390\/a12100220","relation":{},"ISSN":["1999-4893"],"issn-type":[{"type":"electronic","value":"1999-4893"}],"subject":[],"published":{"date-parts":[[2019,10,21]]}}}