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Study on the Social Perspectives of Traffic Congestion in Sri Lanka Through Agent-Based Modeling and Simulation: Lessons Learned and Future Prospects

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Innovative Approaches in Agent-Based Modelling and Business Intelligence

Part of the book series: Agent-Based Social Systems ((ABSS,volume 12))

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Abstract

Traffic congestion is bringing in severe disadvantages to the economy of Sri Lanka. Fuel cost and wastage, air pollution, loss of productivity, as well as unpleasant sights in major cities are among key negative consequences. Lots of short- and long-term measures have been taken by the government through various controls and infrastructure development, but the problem seems to be remaining unsolved if not becoming worse. Alternatively, we propose to study the traffic congestion from a social perspective pertaining to the lifestyles and decision-making patterns of urban and suburban communities as well as the behaviors of drivers and pedestrians. We present the details of an agent-based simulation model developed to study the impact of seepage behavior, which means the smaller vehicles moving forward through the gaps between larger vehicles without following the lanes in the traffic congestion. We further discuss a prospective future research along the same direction, which aims at predicting the impact of the growing motor-biking culture on the urban traffic congestion in Sri Lanka.

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Notes

  1. 1.

    Bicycle is not a popular mode of short-distance personal transportation among the middle class in Sri Lanka unlike in countries like Japan.

  2. 2.

    There is some evidence of a hesitation to accept “raising a child” as a problem.

  3. 3.

    Receiving private tuition is popular among students taking competitive exams at various levels of primary and secondary education in Sri Lanka.

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Correspondence to Chathura Rajapakse .

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Rajapakse, C., Amarasinghe, L., Ratnayake, K. (2018). Study on the Social Perspectives of Traffic Congestion in Sri Lanka Through Agent-Based Modeling and Simulation: Lessons Learned and Future Prospects. In: Kurahashi, S., Takahashi, H. (eds) Innovative Approaches in Agent-Based Modelling and Business Intelligence. Agent-Based Social Systems, vol 12. Springer, Singapore. https://doi.org/10.1007/978-981-13-1849-8_3

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  • DOI: https://doi.org/10.1007/978-981-13-1849-8_3

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