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Musyarofah Musyarofah, Musyarofah
Jurusan Kimia FMIPA Universitas Negeri Semarang Gedung D6 Lantai 2 Kampus Sekaran Gunungpati Semarang, 50229, Telp. (024)8508035
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A Lightweight Interpolation Framework for Real-Time Travel Time Estimation with Incomplete Traffic Observations Syifani, Alya; Musyarofah, Musyarofah; Firdaus, Taufik Ramadhan
International Journal of Technology and Modeling Vol. 4 No. 3 (2025)
Publisher : Etunas Sukses Sistem

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63876/ijtm.v4i3.88

Abstract

Real-time travel time estimation is essential for intelligent transportation systems (ITS), yet operational traffic data streams are often incomplete due to sensor failures, communication delays, and limited coverage. This paper investigates the effectiveness of interpolation techniques for reconstructing temporally continuous travel-time profiles from real-time speed and density observations. Two approaches—linear interpolation and spline interpolation—are implemented and evaluated across varying traffic regimes (normal flow, dense traffic, and extreme congestion). Model performance is assessed using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) against reference travel-time measurements. The results show that interpolation-based methods consistently outperform a conventional baseline relying on average observed speeds, improving estimation accuracy by up to approximately 15%. Linear interpolation yields competitive performance under stable conditions, while spline interpolation achieves lower MAE and RMSE under congestion, indicating stronger robustness to nonlinear traffic dynamics. Additionally, interpolation improves service availability and estimated time of arrival (ETA) reliability with minimal computational overhead, supporting practical deployment in resource-constrained environments. These findings suggest that interpolation provides a lightweight and effective enhancement for real-time travel time estimation and can serve as a reliable preprocessing layer for advanced predictive models in future work.
Co-Authors Agung R, Risa Rahelia Agung R., Risa Rahelia Andrie, Attila Alief Anugrah Anifah, Eka Masrifatus Ardhansyah, Mukti Arfiyanti, Riskha Ariyatun, Ariyatun Bela, Jesica Budi Prayitno Chairunnisa, Regita Cahya Devy Setiorini Sa’adiyah efendi, Irfan Endang Susilaningsih Fachry Abda El Rahman Fadli Robiandi Fajarini, Anindya Fajrin Kurniawan, Fakhri Fauziyah , Nur Aini Febrianto, Ismail Firdaus, Taufik Ramadhan Firmansyah, Feri Hidayatullah Gatut Yudoyono Hayati, Umi henny Siswanti Idhil Ismail, Andi Indarti, M. G. Kentris intan permata sari Ismah, Fatdriatun Joko Waluyo Kamariyah, Nurul Karo, Marni Kartika, Siska Ayu Khumaera, Rahmatia Kunaenih, Kunaenih M. Uswah Pawara Mahera, Adinda Kholif Martanto . Masitoh, anny Rosiana Mohamed, Zakiah Nafisah, Azmia Rizka Nashrullah, Mustaqim Aqib Ningrum, Puji Ni’matus Sholihah Norhidayah, Siti Nuraini , Umi Nuraini, Inas Nurhayati Nurhayati Nurul Inayah Poo-arporn, Yingyot Purba, Livia Br. Puspitaningrum, Diah Puspitasari, Nurrisma Putri, Rezky Meyvia Rahastama, Swastya Rahim, Muhammad Ramadhan, Muhammad Bagus Saputra Reza, Mutia Sapawe, Norzahir Saputra, Dwi Mulia Nur Sastrawan, Febrian Dedi shoodiqin, dian mart Sihaloho, Elisabeth Romanauli Silalahi, Hanna Rosita Simanjuntak, Cristovel Sirait, Maria Diva Yuniar Siregar, Renince Sri Susilogati Sumarti Subaweh, Ahmad Maskur Suhaimi, Firdaus Sumual, Theofilus Ariel Syifani, Alya Tajalla, Gusti Umindya Nur Tanaka, Isao Triwikantoro Triwikantoro Utomo, Zinedine Zidane Wardani, Refangga Cendikia Zein, Firly Annisa'