Traffic Prediction and Management Techniques

Poster presented at the Transport Research Arena (TRA) 2026 for the paper 'Semantic Low-Code Data Fusion on the Edge to Support Intelligent Traffic Management' Abstract: Intelligent traffic management applications require integrating data from diverse sources on the road infrastructure like radar sensors, cameras, and…

Poster presented at the Transport Research Arena (TRA) 2026 for the paper 'Semantic Low-Code Data Fusion on the Edge to Support Intelligent Traffic Management' Abstract: Intelligent traffic management applications require integrating data from diverse sources on the road infrastructure like radar sensors, cameras, and…

Urban traffic prediction plays a critical role in improving transportation efficiency and supporting sustainability in smart cities. This study proposes an explainable spatio-temporal machine learning framework that integrates periodic temporal features with graph-based spatial representations. Temporal dynamics are m…

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Energy demand in the transportation sector has become a significant concern due to global economic growth, urbanization, and increased industrial production. This study focuses on the transportation energy demand (TED) problem. The primary dataset includes gross domestic product, population size, and vehicle-kilometer…

This paper investigates temporal and spatial patterns in Istanbul's public transit demand using 96 million hourly passenger records spanning March-October 2024. We develop an analytical pipeline comprising domain driven time window aggregation, predictive modeling, and unsupervised pattern discovery across all major t…

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Abstract. The recent developments in cellular communication technologies, especially the emergence of 6G, have increased the need for accurate and reliable signal path loss prediction models. The accuracy of predictions is reduced because traditional empirical approaches often fail to take into account the complex rel…

Öz Bu çalışma, kentsel toplu taşıma sistemlerinde otobüslerin duraklar arası tahmini varış sürelerini (Estimated Time of Arrival, ETA) daha yüksek doğrulukla öngörebilmek amacıyla karar ağaçları tabanlı makine öğrenmesi algoritmalarının kapsamlı bir karşılaştırmasını sunmaktadır.MBTA tarafından sağlanan "Bus Arrival/D…

Purpose This study addresses the air ticket sales forecasting problem for business-to-business (B2B) travel agencies, a largely unexplored area compared to airlines and business-to-consumer agencies. To meet guarantee deposit requirements and manage financial risk exposure, B2B agencies require accurate demand estimat…

Reliable forecasting of transportation energy demand is important for energy planning, infrastructure investment, and the evaluation of alternative transport-policy pathways. This study develops a leakage-aware temporal benchmarking framework for Türkiye using 39 observations covering 1975–2025, with five-year spacing…