Skip to main content

Advertisement

SpringerLink
Log in

Investigating the Effect of Suburban Buses on Traffic Flow and Carbon Monoxide Emission by Aimsun Simulation Software

  • Research Article
  • Published:
Journal of the Indian Society of Remote Sensing Aims and scope Submit manuscript

Abstract

Incorrect placement of use in the urban area can affect the demand pattern of trips, traffic flow between the different districts, and air pollution. Traffic simulators were used to study the impact of this factor on traffic flow and pollutant emission in traffic networks. The purpose of this study was to investigate the effect of the incorrect placement of the Tehran West Terminal on the flow of traffic and the amount of carbon monoxide emission in the network using the Aimsun simulation software. Hence, the suburban bus route was simulated from the West Terminal to the Bakery intersection in the presence and absence of suburban buses. Then parameters were investigated, such as carbon monoxide emissions, fuel consumption, delay time, total travel time, and average speed of traffic flow. The results showed that when suburban buses are present in the network, the average traffic speed rate decreased by 7.6%, and the total travel time and network delay time increased by 11.1% and 9.1%, respectively, which in general indicates a decrease in the quality of the in-network traffic flow. Also, fuel consumption and carbon monoxide emissions increased with suburban bus presence in the network by 13.7% and 9.1%, respectively. The results can confirm that lack of attention to urban development limits and ignoring the importance of sustainable urban management in controlling traffic demand can have negative economic and environmental consequences.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Azlan, N. N. N., & Rohani, M. M. (2018). Overview of application of traffic simulation model. In MATEC Web of Conferences (Vol. 150, p. 03006). EDP Sciences.

  • Barceló, J., Codina, E., Casas, J., Ferrer, J. L., & García, D. (2005). Microscopic traffic simulation: A tool for the design, analysis and evaluation of intelligent transport systems. Journal of Intelligent and Robotic Systems, 41(2–3), 173–203.

    Article  Google Scholar 

  • Bloomberg, L., & Dale, J. (2000). Comparison of VISSIM and CORSIM traffic simulation models on a congested network. Transportation Research Record, 1727(1), 52–60.

    Article  Google Scholar 

  • Chalermwongphan, K., & Upala, P. (2019). Comparing the traffic operation, fuel consumption, and pollutant emission of bike lane pattern design with AIMSUN microscopic simulation model: A case study of Nakhon Sawan municipality in Thailand. The Open Transportation Journal, 13(1), 182–193.

    Article  Google Scholar 

  • Çimen, M., & Soysal, M. (2017). Time dependent green vehicle routing problem with stochastic vehicle speeds: An approximate dynamic programming algorithm. Transportation Research, 54, 82–98.

    Google Scholar 

  • Comert, G., Darko, S., Huynh, N., Elijah, B., & Eloise, Q. (2020). Evaluating the impact of traffic volume on air quality in South Carolina. International Journal of Transportation Science and Technology, 9(1), 29–41.

    Article  Google Scholar 

  • Fellendorf, M., & Vortisch, P. (2010). Microscopic traffic flow simulator VISSIM. Fundamentals of traffic simulation (pp. 63–93). New York: Springer.

    Chapter  Google Scholar 

  • Figueiredo, M., Seco, A., & Silva, A. B. (2014). Calibration of microsimulation models–The effect of calibration parameters errors in the models’ performance. Transportation Research Procedia, 3, 962–971.

    Article  Google Scholar 

  • Ghorani-Azam, A., Riahi-Zanjani, B., & Balali-Mood, M. (2016). Effects of air pollution on human health and practical measures for prevention in Iran. Journal of Research in Medical Sciences: The Official Journal of Isfahan University of Medical Sciences, 21, 65–77.

    Article  Google Scholar 

  • Grylls, T., Le Cornec, C. M., Salizzoni, P., Soulhac, L., Stettler, M. E., & van Reeuwijk, M. (2019). Evaluation of an operational air quality model using large-eddy simulation. Atmospheric Environment, 3, 1–13.

    Google Scholar 

  • Hollander, Y., & Liu, R. (2008). The principles of calibrating traffic microsimulation models. Transportation, 35(3), 347–362.

    Article  Google Scholar 

  • Jereb, B., Kumperščak, S., & Bratina, T. (2018). The impacts of traffic flow on fuel consumption increase in the urban environment. FME Transactions, 46(2), 278–284.

    Article  Google Scholar 

  • Kazemi Fard, A., Moghadas Nejad, F., & Kazemi Fard, S. H. (2016). Traffic condition improvement using Aimsun simulation software. Road Journal, 24(87), 129–142.

    Google Scholar 

  • Kim, S., Suh, W., & Kim, J. (2014). Traffic simulation software: Traffic flow characteristics in CORSIM. In 2014 International Conference on Information Science & Applications (ICISA). Seoul, South Korea, 3 p.

  • Kumar, A., Vijay, S., Kumar, R., Patil, R. S., Dikshit, A. K., & Dhingra, S. L. (2018). Prediction and analysis of pollution and congestion level for present and future scenario on an urban road network India. International Journal for Traffic and Transport Engineering, 8(2), 213–227.

    Article  Google Scholar 

  • Lin, D., Yang, X., & Gao, C. (2013). VISSIM-based simulation analysis on road network of CBD in Beijing, China. Procedia-Social and Behavioral Sciences, 96, 461–472.

    Article  Google Scholar 

  • Lindgren, R. V., & Tantiyanugulchai, S. (2003). Microscopic simulation of traffic at a suburban interchange. In Proceedings of the ITE annual meeting, Seattle, WA, USA.

  • Moridpour, S., Rose, G., Sarvi, M., & Mazloumi, E. (2012). Influence of the surrounding traffic characteristics on lane changing decision of heavy vehicle drivers. Road & Transport Research: A Journal of Australian and New Zealand Research and Practice, 21(3), 19–31.

    Google Scholar 

  • Naghawi, H., Shattal, M. A., & Idewu, W. (2019). Application of Aimsun microscopic simulation model in evaluating side friction impacts on traffic stream performance. World Academy of Science, Engineering and Technology International Journal of Transport and Vehicle Engineering, 3(1), 10–15.

    Google Scholar 

  • Papageorgiou, G., Damianou, P., Pitsillides, A., Aphames, T., & Ioannou, P. (2006). A microscopic traffic simulation model for transportation planning in Cyprus. In International Conference on Intelligent Systems And Computing: Theory And Applications (ISYC).

  • Papageorgiou, G., Damianou, P., Pitsillides, A., Aphamis, T., Charalambous, D., & Ioannou, P. (2009). Modeling and simulation of transportation systems: A scenario planning approach. Automatika: Journal for Control, Measurement, Electronics, Computing & Communications, 50(1–2), 39–50.

  • Park, M., Chung, Y., & Kim, Y. J. (2007). An integrated microscopic simulation model for estimating potential emissions impacts of truck-involved transportation policies. Journal of the Eastern Asia Society for Transportation Studies, 7, 1127–1137.

    Google Scholar 

  • Punzo, V., & Ciuffo, B. (2009). How parameters of microscopic traffic flow models relate to traffic dynamics in simulation: Implications for model calibration. Transportation Research Record, 2124(1), 249–256.

    Article  Google Scholar 

  • Ragab, M., Hashim, I. H., & Asar, G. M. (2017). Impact of road traffic on air emissions: case study Kafr El-Sheikh City. Egypt. International Journal for Traffic & Transport Engineering, 7(3), 391–405.

    Google Scholar 

  • Raheem, S. B., Olawoore, W. A., Olagunju, D. P., & Adeokun, E. M. (2015). The cause, effect and possible solution to traffic congestion on Nigeria Road (A Case Study of Basorun-Akobo Road, Oyo State). International Journal of Engineering Science Invention, 4(9), 10–14.

    Google Scholar 

  • Ratrout, N. T., & Rahman, S. M. (2009). A comparative analysis of currently used microscopic and macroscopic traffic simulation software. The Arabian Journal for Science and Engineering, 34(1B), 121–133.

    Google Scholar 

  • Ronaldo, A., & Ismail, T. (2012). Comparison of the two micro-simulation software Aimsun & Sumo for highway traffic modeling (p. 93). Department of Science and Technology Intelligent Transport System: Linköping University.

    Google Scholar 

  • Rumana, H. S., Sharma, R. C., Beniwal, V., & Sharma, A. K. (2014). A retrospective approach to assess human health risks associated with growing air pollution in urbanized area of Thar Desert, Western Rajasthan, India. Journal of Environmental Health Science and Engineering, 12(1), 12–23.

    Article  Google Scholar 

  • Saidallah, M., El Fergougui, A., & Elalaoui, A. E. (2016). A comparative study of urban road traffic simulators. In MATEC Web of Conferences (Vol. 81, p. 05002). EDP Sciences.

  • Smit, R., Brown, A. L., & Chan, Y. C. (2008). Do air pollution emissions and fuel consumption models for roadways include the effects of congestion in the roadway traffic flow? Journal of Environmental Modeling & Software, 23, 1262–1270.

    Article  Google Scholar 

  • Smit, R., Ntziachristos, L., & Boulter, P. (2010). Validation of road vehicle and traffic emission models—A review. Atmospheric Environment, 44(25), 2943–2953.

    Article  Google Scholar 

  • Tian, Z., Jia, L., Dong, H., Su, F., & Zhang, Z. (2016). Analysis of urban road traffic network based on complex network. Procedia Engineering, 137, 537–546.

    Article  Google Scholar 

  • Transportation and Traffic Deputy of Tehran Municipality. (2012). Calibration of traffic engineering software based on traffic conditions in Tehran. Tehran: Ava Fahim Press.

    Google Scholar 

  • Transport Simulation system (TSS). (2014). Aimsun 8 dynamic simulators users’ manual. 508 p.

  • Tüccar, G., & Uludamar, E. (2017). Optimization of traffic signalization timings to reduce queue length and vehicle delays: A case study in Çukurova University. European Mechanical Science, 1(3), 89–92.

    Article  Google Scholar 

  • Wen, L., Kenworthy, J., Guo, X., & Marinova, D. (2019). Solving traffic congestion through street renaissance: A perspective from dense Asian Cities. Urban Science, 3(1), 18–39.

    Article  Google Scholar 

  • Wesseling, J. P., Hollander, J. C., Teeuwisse, S., Keuken, M. P., Gense, R., Vander Burgwal, E., Hermans, L., Voerman, J., Kummu, P. J., & Elshout, J. V. (2003). Research on the effects of 80 km/h on air quality in Overschie near the A13 motorway (in Dutch). TNO Report 2003-R0258. Utrecht, the Netherlands: TNO.

  • Yamamoto, S. S., Phalkey, R., & Malik, A. A. (2014). A systematic review of air pollution as a risk factor for cardiovascular disease in South Asia: Limited evidence from India and Pakistan. International Journal of Hygiene and Environmental Health, 217(2–3), 133–144.

    Article  Google Scholar 

  • Yun, S., White, W. W., Lamb, D. R., & Wu, Y. (2005). Accounting for the impact of heavy truck traffic in volume-delay functions in transportation planning models. Transportation Research Record, 1931(1), 8–17.

    Article  Google Scholar 

  • Zhang, K., & Batterman, S. (2013). Air pollution and health risks due to vehicle traffic. Science of the Total Environment, 450, 307–316.

    Article  Google Scholar 

  • Zhang, W., Qian, C. N., & Zeng, Y. X. (2014). Air pollution: A smoking gun for cancer. Chinese Journal of Cancer, 33(4), 173–178.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Environmental Sciences, Malayer University, Malayer, Iran

    Sahar Abedian & Mir Mehrdad Mirsanjari

  2. Department of Environmental Sciences, Gorgan University of Agricultural Science and Natural Resources, Gorgan, Iran

    Abdolrassoul Salmanmahiny

Authors
  1. Sahar Abedian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mir Mehrdad Mirsanjari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Abdolrassoul Salmanmahiny
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sahar Abedian.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abedian, S., Mirsanjari, M.M. & Salmanmahiny, A. Investigating the Effect of Suburban Buses on Traffic Flow and Carbon Monoxide Emission by Aimsun Simulation Software. J Indian Soc Remote Sens 49, 1319–1330 (2021). https://doi.org/10.1007/s12524-020-01289-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12524-020-01289-z

Keywords

Search

Navigation