Abstract

Reliability reflects the level of ease of people and goods to travel. Reliability relates with the variability of travel time, speed, and system usage and transportation system capacity. The higher the capacity of the system and the faster the travel time, the higher the level of reliability of the transportation system, so that it can reduce traffic congestion. Traffic congestion will occur when travel requests exceed road capacity. Our research attempts to provides a comprehensive and objective assessment of improving reliability of transportation systems and its impact to reduce traffic congestion. We utilized system dynamics simulation model to test and evaluate the alternatives of future strategies to increase the reliability of transportation systems and its impact to reduce traffic congestion. Systems dynamics models can be developed at the macroscopic and microscopic levels of transportation systems as well as to evaluate the effects of different transportation policies on traffic congestion. Simulation results show that reliability is determined by several factors such as travel time, headway (the time between two means of transportation to pass a point/place), passenger wait time; access time and egress time (the time needed to get off the vehicle when it arrives at the destination). Transportation systems reliability continues to decline so that in 2017, reliability was only around 41.5%. The improvement scenario of transportation system reliability can be done by conducting several strategies such as increasing road capacity, increasing public vehicle routes around public facilities, as well as increasing the supply of public transportation which has an impact on headway and waiting time. By conducting these strategies, the reliability of transportation systems could be increased to be around 53.3% and a gradual increase in road capacity could be done with a growth of 2.8% per year. Within this condition, the traffic congestion is projected to be around 74.9%-83.6% in the period 2019-2027, and then to be around 83-88% in the period 2028-2035.

Original languageEnglish
Article number12029
JournalJournal of Physics: Conference Series
Volume1196
Issue number1
DOIs
Publication statusPublished - 16 Apr 2019
EventInternational Conference on Information System, Computer Science and Engineering 2018, ICONISCSE 2018 - Palembang, Indonesia
Duration: 26 Nov 201827 Nov 2018

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