Managing Artificial Intelligence on Public Transportation (Case Study Jakarta City, Indonesia)

This research aims to study AI management and its implementation in the public transportation sector to accommodate the needs of Jakarta’s citizens. The basic framework used in this research is on analysis of case study transportation in Jakarta. Using a qualitative method with data collection from...

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Veröffentlicht in:IOP conference series. Earth and environmental science 2021-03, Vol.717 (1), p.12021
Hauptverfasser: Solihati, Keisha Dinya, Indriyani, Dian
Format: Artikel
Sprache:eng
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Zusammenfassung:This research aims to study AI management and its implementation in the public transportation sector to accommodate the needs of Jakarta’s citizens. The basic framework used in this research is on analysis of case study transportation in Jakarta. Using a qualitative method with data collection from literature review and observation. Data analysis focuses on challenges and requirements needed to implement AI on public transportation to enhance urban mobility. Along with key AI management aspects discussed on 1) Source funding for AI in Mass Public Transport Project; 2) Reform Traditional Procurement Process; 3) Develop Unbiased AI; 4) Avoid the trap of over-relying on AI; 5) Develop Legal and Policy Framework. The purpose of this research is that it can contribute as a reference and recommendation for local government in making policy on AI and transportation in the future. Based on the research analysis, it is concluded that AI can address transportation problems in traffic management, traffic safety, public transportation, and urban mobility. However, AI implementation in Jakarta needs more improvement to ensure the system is integrated among many types of public transports, and improve its user-friendliness. It is recommended to develop a one-gate integrated application system to access all information on public transportation and to develop a legal and policy framework related to the applications.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/717/1/012021