Abstract

Along with the development of ICT, transportation domain in Jakarta is evolving. The blooming of apps-based transportation has become an interesting alternative transportation mode for the citizens. This mode of transportation is diverting the usage of single occupancy travel to a more occupancy travel, such that it is expected to give positive contributions in reducing the traffic congestion. In this regard, policy intervention to the apps-based transportation ecosystem is being implemented by the government to ensure the conducive situation with the other transportation mode. This study provides an analysis of the policy intervention impact to the traffic congestion in Jakarta. A simulation model capturing the dynamic of the apps-based transportation ecosystem is developed using system dynamic approach. The main aspects considered in the model are including the usage of apps-based transportation, the traffic congestion, and the number of vehicles on the road. The simulation of the model is conducted based on four scenarios of policy intervention, namely, empowering, control, limited, and block. By using the data that are relevant to the situation in Jakarta, the simulation result shows that the traffic congestion level will significantly decline when the policy related to the apps-based transportation is supportive.

Highlights

  • Traffic congestion is one of the major transportation problems in most of the large cities in the world

  • In the transportation ecosystem perspective, the usage of apps-based transportation can improve the efficiency of personal transportation vehicles, such that it is expected to contribute in reducing the traffic congestion (Agatz, Erera, Savelsbergh, & Wang, 2011)

  • This study evaluates the impact of policy intervention on the apps-based transportation ecosystem to the traffic congestion in Jakarta

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Summary

Introduction

Traffic congestion is one of the major transportation problems in most of the large cities in the world. In the transportation ecosystem perspective, the usage of apps-based transportation can improve the efficiency of personal transportation vehicles, such that it is expected to contribute in reducing the traffic congestion (Agatz, Erera, Savelsbergh, & Wang, 2011). This is because the apps-based transportation can divert the trips made in private single occupancy cars or taxis, with more occupancy (Li, Hong, & Zhang, An empirical analysis of on-demand ride-sharing and traffic congestion, 2017).

Model Development
Apps-based Transportation Usage Sub-model
Personal Transportation on the Road Sub-model
Traffic Congestion Sub-model
Model Simulation
Simulation Scenario
Simulation Result
Findings
Conclusions
Full Text
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