ANALISIS SPASIAL SIGNIFIKAN HUBUNGAN VOLUME DENGAN KECEPATAN KENDARAAN PADA SIMPANG BERSINYAL

Evita Fitrianis Hidiyati (Department of Civil Engineering, Faculty of Engineering, University of Kadiri Selomangleng Street, No. 01, Pojok, Mojoroto, Kediri City, 64115, Indonesia)
Andri Dwi Cahyono (Department of Civil Engineering, Faculty of Engineering, University of Kadiri Selomangleng Street, No. 01, Pojok, Mojoroto, Kediri City, 64115, Indonesia)
Mochammad Danara Indra Pradigta (Department of Civil Engineering, Faculty of Engineering, University of Kadiri Selomangleng Street, No. 01, Pojok, Mojoroto, Kediri City, 64115, Indonesia)
Faiz Muhammad Azhari (Department of Civil Engineering, Faculty of Engineering, University of Kadiri Selomangleng Street, No. 01, Pojok, Mojoroto, Kediri City, 64115, Indonesia)
Nandana Faizal Bahtiar (Department of Civil Engineering, Faculty of Engineering, University of Kadiri Selomangleng Street, No. 01, Pojok, Mojoroto, Kediri City, 64115, Indonesia)
Moh Ali Maftuh (Department of Civil Engineering, Faculty of Engineering, University of Kadiri Selomangleng Street, No. 01, Pojok, Mojoroto, Kediri City, 64115, Indonesia)

Jurnal Pensil : Pendidikan Teknik Sipil
Vol. 15 No. 2 (2026): Jurnal Pensil : Pendidikan Teknik Sipil

In Kediri City, Indonesia this study examines the spatial variations in the correlation between vehicle speed and traffic volume at signalized junctions. Field surveys were conducted during peak-hour periods at eight signalized intersections, with 30 directional approaches used as observation units. The analysis considered four vehicle categories: motorcycles, passenger cars, trucks, and buses. Geographically Weighted Regression (GWR) was utilized to investigate local variation in volume-speed sensiticity, whereas Ordinary Least Squares (OLS) regression served as a global reference model. The results show that higher traffic volume is generally associated with lower vehicle speed, but the strength of this relationship differs by location and vehicle type. Motorcycles have the weakest sensitivity because of their greater maneuverability in mixed traffic. In contrast, trucks and buses show stronger speed reductions due to larger vehicle dimensions, lower acceleration capability, and greater maneuvering-space requirements. Spatially, Alun-Alun and Kemuning intersections show stronger local volume–speed relationships, as indicated by more negative local coefficients and higher Local R² values. The ANOVA-based comparison indicates that GWR provides different levels of improvement over the global model, particularly for heavy vehicles. These findings support the need for signalized intersection management that considers both local traffic conditions and vehicle-type characteristics.