Reducing traffic congestion and increasing sustainability in special urban areas through one-way traffic reconfiguration

Abstract

In the contemporary sustainable urban set up, one of the critical issues adversely affecting the quality of life in urban areas and inflicting immense costs on cities is traffic congestion. Traffic congestion is an outgrowth of increased traffic flow in certain locations of large cities. Recently, urban decision-makers and transportation planners resort to one-way traffic system as an effective traffic management strategy, which has a profound effect on reducing traffic congestion and improving traffic flow, leading to urban sustainability. In the present paper, the authors endeavored to develop a novel methodological framework based on optimization techniques in order to mitigate traffic congestion through one-way traffic network reconfiguration. To test the efficacy of the proposed methodological framework, two cases were analyzed and evaluated: the Sioux Falls transportation network as a medium-sized one and a real-world large-scale transportation network of the city of Isfahan in Iran. Through the first instance, it can be seen that the proposed method can effectively reduce the total travel time in the area of interest by approximately 9%. The numerical results for the transportation network of Isfahan, justified the practical value of the model and solution method through converting proper links to one-way. As the calculation results of two cases have demonstrated, the solution can effectively reduce the total travel time of travelers in a certain congested urban area.

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References

  1. Das, I.: On characterizing the “knee” of the Pareto curve based on normal-boundary intersection. Struct. Optim. 18(2–3), 107–115 (1999). https://doi.org/10.1007/BF01195985

    Article  Google Scholar 

  2. Deb, K.: Multi-Objective Optimization Using Evolutionary Algorithms, vol. 16. Wiley, New York (2001)

    Google Scholar 

  3. De Palma, A., Lindsey, R., Proost, S.: Research challenges in modelling urban road pricing: an overview. Transp. Policy 13(2), 97–105 (2006). https://doi.org/10.1016/j.tranpol.2005.11.006

    Article  Google Scholar 

  4. Drezner, Z., Salhi, S.: Selecting a good configuration of one-way and two-way routes using tabu search. Control Cybern. 29(3), 725–740 (2000)

    Google Scholar 

  5. Drezner, Z., Wesolowsky, G.O.: Selecting an optimum configuration of one-way and two-way routes. Transp. Sci. 31(4), 386–394 (1997). https://doi.org/10.1287/trsc.31.4.386

    Article  Google Scholar 

  6. Drezner, Z., Wesolowsky, G.O.: Network design: selection and design of links and facility location. Transp. Res. Part A Policy Pract. 37(3), 241–256 (2003). https://doi.org/10.1016/S0965-8564(02)00014-9

    Article  Google Scholar 

  7. Farahani, R.Z., Miandoabchi, E., Szeto, W.Y., Rashidi, H.: A review of urban transportation network design problems. Eur. J. Oper. Res. 229(2), 281–302 (2013). https://doi.org/10.1016/j.ejor.2013.01.001

    Article  Google Scholar 

  8. Feng, S.H.I., Huang, E., Qun, C.H.E.N., Yingzi, W.A.N.G.: Optimization of one-way traffic organization for urban microcirculation transportation network. J. Transp. Syst. Eng. Inf. Technol. 9(4), 30–35 (2009). https://doi.org/10.1016/S1570-6672(08)60070-7

    Article  Google Scholar 

  9. Ghadirifaraz, B., Vaziri, M., Safa, A., Barikrou, N.: A Statistical Appraisal of Bus Rapid Transit Based on Passengers Satisfaction and Priority Case Study: Isfahan City, Iran (No. 17-05108) (2017). https://trid.trb.org/view/1438990

  10. Hua, J., Ren, G., Cheng, Y., Ran, B.: An integrated contraflow strategy for multimodal evacuation. Mathe. Problem. Eng. (2014). https://doi.org/10.1155/2014/159473

    Article  Google Scholar 

  11. Iniestra, J.G., Gutiérrez, J.G.: Multicriteria decisions on interdependent infrastructure transportation projects using an evolutionary-based framework. Appl. Soft Comput. 9(2), 512–526 (2009). https://doi.org/10.1016/j.asoc.2008.07.006

    Article  Google Scholar 

  12. Karimi, H., Shetab-Boushehri, S.N., Ghadirifaraz, B.: Sustainable approach to land development opportunities based on both origin-destination matrix and transportation system constraints, case study: central business district of Isfahan, Iran. Sustain. Cities Soc. 45, 499–507 (2019). https://doi.org/10.1016/j.scs.2018.12.002

    Article  Google Scholar 

  13. Kaddoura, I., Nagel, K.: Simultaneous internalization of traffic congestion and noise exposure costs. Transportation 45(5), 1579–1600 (2018). https://doi.org/10.1007/s11116-017-9776-0

    Article  Google Scholar 

  14. Karoonsoontawong, A., Lin, D.Y.: Time-varying lane-based capacity reversibility for traffic management. Comput-Aided Civil Infrastruct. Eng. 26(8), 632–646 (2011). https://doi.org/10.1111/j.1467-8667.2011.00722.x

    Article  Google Scholar 

  15. LeBlanc, L.J.: An algorithm for the discrete network design problem. Transp. Sci. 9(3), 183–199 (1975). https://doi.org/10.1287/trsc.9.3.183

    Article  Google Scholar 

  16. Li, M., Hu, Y., Shang, H.: The application of origin-based algorithm on route flows of ambiguous path problem in expressway network tolling system. In ICCTP 2011: Towards Sustainable Transportation Systems (pp. 598–605) (2011)

  17. Lertworawanich, P., Kuwahara, M., Miska, M.: A new multiobjective signal optimization for oversaturated networks. IEEE Trans. Intell. Transp. Syst. 12(4), 967–976 (2011). https://doi.org/10.1109/TITS.2011.2125957

    Article  Google Scholar 

  18. Litman, T.: Planning principles and practices. Victoria Transport Policy Institute, 1-35 (2013). Website: www.vtpi.org

  19. Magnanti, T.L., Wong, R.T.: Network design and transportation planning: models and algorithms. Transp. Sci. 18(1), 1–55 (1984). https://doi.org/10.1287/trsc.18.1.1

    Article  Google Scholar 

  20. Meng, Q., Khoo, H.L., Cheu, R.L.: Microscopic traffic simulation model-based optimization approach for the contraflow lane configuration problem. J. Transp. Eng. 134(1), 41–49 (2008). https://doi.org/10.1061/(ASCE)0733-947X(2008)134:1(41)

    Article  Google Scholar 

  21. Miandoabchi, E., Farahani, R.Z.: Optimizing reserve capacity of urban road networks in a discrete network design problem. Adv. Eng. Softw. 42(12), 1041–1050 (2011). https://doi.org/10.1016/j.advengsoft.2011.07.005

    Article  Google Scholar 

  22. Miandoabchi, E., Farahani, R.Z., Dullaert, W., Szeto, W.Y.: Hybrid evolutionary metaheuristics for concurrent multi-objective design of urban road and public transit networks. Netw. Spatial Econ. 12(3), 441–480 (2012). https://doi.org/10.1007/s11067-011-9163-x

    Article  Google Scholar 

  23. Ortigosa, J., Gayah, V.V., Menendez, M.: Analysis of one-way and two-way street configurations on urban grid networks. Transportmetrica B Transport Dyn. 7(1), 61–81 (2017). https://doi.org/10.1080/21680566.2017.1337528

    Article  Google Scholar 

  24. Ortigosa, J., Menendez, M.: Traffic performance on quasi-grid urban structures. Cities 36, 18–27 (2014). https://doi.org/10.1016/j.cities.2013.08.006

    Article  Google Scholar 

  25. Peng, Z., Guan, F., Wang, K., Li, T., Yao, B.: Simulation-optimization model for one-way traffic reconfiguration. Simulation 92(7), 627–635 (2016). https://doi.org/10.1177/0037549715621400

    Article  Google Scholar 

  26. Rasekh, A., Brumbelow, K.: A dynamic simulation–optimization model for adaptive management of urban water distribution system contamination threats. Appl. Soft Comput. 32, 59–71 (2015). https://doi.org/10.1016/j.asoc.2015.03.021

    Article  Google Scholar 

  27. Ren, G., Huang, Z., Cheng, Y., Zhao, X., Zhang, Y.: An integrated model for evacuation routing and traffic signal optimization with background demand uncertainty. J. Adv. Transp. 47(1), 4–27 (2013). https://doi.org/10.1002/atr.1211

    Article  Google Scholar 

  28. Salavati, A., Haghshenas, H., Ghadirifaraz, B., Laghaei, J., Eftekhari, G.: Applying AHP and Clustering Approaches for Public Transportation Decisionmaking: a Case Study of Isfahan City. J. Public Transp. 19(4), 3 (2016). https://doi.org/10.5038/2375-0901.19.4.3

    Article  Google Scholar 

  29. Salcedo-Sanz, S., Manjarres, D., Pastor-Sánchez, Á., Del Ser, J., Portilla-Figueras, J.A., Gil-Lopez, S.: One-way urban traffic reconfiguration using a multi-objective harmony search approach. Expert Syst. Appl. 40(9), 3341–3350 (2013). https://doi.org/10.1016/j.eswa.2012.12.043

    Article  Google Scholar 

  30. Shi, J., Bian, W., Tao, L.: Quantitative analysis of one-way street effects in urban central district. In: 2009 International Conference on Management and Service Science (pp. 1–4) (2009, September). IEEE. https://doi.org/10.1109/ICMSS.2009.5303320

  31. Nations, U.: World urbanization prospects: The 2014 revision, highlights. department of economic and social affairs. Population Division, United Nations, 32 (2014). http://esa.un.org/unpd/wup/Highlights/WUP2014-Highlights.pdf

  32. Nations, U.: World urbanization prospects: The 2014 revision. New York: Department of Economic and Social Affairs (2015). http://esa.un.org/unpd/wup/Publications/Files/WUP2014-Report.pdf

  33. Xi, X., Sioshansi, R., Marano, V.: Simulation–optimization model for location of a public electric vehicle charging infrastructure. Transp. Res. Part D Transport Environ. 22, 60–69 (2013). https://doi.org/10.1016/j.trd.2013.02.014

    Article  Google Scholar 

  34. Yu, B., Li, T., Kong, L., Wang, K., Wu, Y.: Passenger boarding choice prediction at a bus hub with real-time information. Transp. B Transport Dyn. 3(3), 192–221 (2015). https://doi.org/10.1080/21680566.2015.1007400

    Article  Google Scholar 

  35. Zhao, X., Ren, G., Huang, Z.F.: Optimizing one-way traffic network reconfiguration and lane-based non-diversion routing for evacuation. J. Adv. Transp. 50(4), 589–607 (2016). https://doi.org/10.1002/atr.1362

    Article  Google Scholar 

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Acknowledgements

The authors wish to thank the Transportation and Traffic Department of Isfahan Municipality and Isfahan University of Technology for their supports.

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Authors

Contributions

HK: Conceiving of the presented idea, designing the model and the computational framework, writing parts of the manuscript. BG: Literature search and review, manuscript writing and preparation, analysis and interpretation of results, making critical revisions and checking the references. SNSB: Supervised the research, making the simulations, and acts as corresponding author. S-MH: Developing the theory, solving the multi objective decision making problem, writing parts of the manuscript. NR: Designing and performing the experiments, data collection, writing parts of manuscript. All authors provided feedback and helped shape the research and approved the final version of the manuscript.

Corresponding author

Correspondence to Seyed Nader Shetab Boushehri.

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Appendix

Appendix

See Tables 2 and 3.

Table 2 Link importance measure index for Sioux Falls network
Table 3 List of non-dominated scenarios for Sioux Falls network

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Karimi, H., Ghadirifaraz, B., Shetab Boushehri, S.N. et al. Reducing traffic congestion and increasing sustainability in special urban areas through one-way traffic reconfiguration. Transportation (2021). https://doi.org/10.1007/s11116-020-10162-4

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Keywords

  • Traffic management policy
  • Urban planning, Sustainable city
  • Traffic congestion
  • One-way traffic network reconfiguration
  • Multi-objective decision-making