Journal of Enterprise and Business Intelligence


Minimizing the Congestion Index and Mode Share of Traffic Congestion in Urban Area



Journal of Enterprise and Business Intelligence

Received On : 20 June 2021

Revised On : 12 August 2021

Accepted On : 18 October 2021

Published On : 05 January 2022

Volume 02, Issue 01

Pages : 024-032


Abstract


Urbanization is heavily influenced by the transportation that becomes fundamental to the mobility of human activities. However, unchecked growth in transportation raises serious concerns about many issues such as congestions, limited parking, and public transit problem. This phenomenon also overwhelms Kuala Lumpur, the capital city of Malaysia that has a high number of car ownership. Consequently, traffic congestion in urban area has affected people living there in terms of lost time on the road and waste of fuel consumption. In this regard, this research aims to minimize the congestion index and mode share in Kuala Lumpur based on the tested of six travel demand strategy variables. The problem was model and optimized using system dynamics (SD) optimization approach. Results of the developed SD optimization model shows that the optimized congestion index is 0.89863 while the mode share is 52.87% in 2030 compared to SD baserun which are only 1.1021 and 21.7% for congestion index and mode share respectively. This finding shows that SD optimization performed a better result in terms of achieving the targeted of congestion index and mode share of < 0.6 and 50% by 2030 compared to SD baserun. From the managerial perspective, this research helps towards achieving the government’s congestion index and mode share targets through strategizing the ways on attracting public transportation and discouraging the usage of private cars in Kuala Lumpur.


Keywords


Congestion index; Mode share; Public transportation; Urban area; System dynamics Optimization.


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Cite this article


Norisma Idris, “Minimizing the Congestion Index and Mode Share of Traffic Congestion in Urban Area”, Journal of Enterprise and Business Intelligence, vol.2, no.1, pp. 024-032, January 2022. doi: 10.53759/5181/JEBI202202004.


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© 2022 Norisma Idris. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.