Pengembangan Model Prediksi Kecelakaan Lalu Lintas pada Jalan Tol Purbaleunyi
DOI:
https://doi.org/10.5614/jts.2012.19.3.8Keywords:
Kecelakaan lalu lintas, Model prediksi kecelakaan, Identifikasi dan Pemeringkatan segmeni jalan berbahaya.Abstract
Abstrak. Kondisi keselamatan lalu lintas jalan di Indonesia masih belum baik, kecelakaan lalu lintas masih sering terjadi dan memakan banyak korban jiwa. Salah satu upaya mendasar yang diperlukan untuk meningkatkan kondisi keselamatan lalu lintas jalan adalah dengan cara mengembangkan model prediksi kecelakaan. Model ini menghubungkan frekuensi kecelakaan yang terjadi pada suatu entitas jalan dengan arus lalu lintas dan berbagai faktor lingkungan jalan yang berkontribusi pada terjadinya kecelakaan. Kegunaan model ini adalah untuk mengestimasi dan memprediksi keselamatan suatu entitas jalan, mengidentifikasi lokasi-lokasi jalan berbahaya, dan juga untuk mengevaluasi keefektifan penerapan program penanganan lokasi berbahaya. Makalah ini menyajikan model prediksi kecelakaan pada ruas jalan tol Purwakarta-Bandung-Cileunyi (Purbaleunyi) yang dibangun dengan membandingkan kinerja statistik dari model regresi Poisson, Negatif Binomial (NB), Zero-Inflated Poisson (ZIP), dan Zero-Inflated Negative Binomial (ZINB). Hasil pemodelan mengindikasikan model regresi NB adalah model yang terbaik. Berdasarkan model yang dibangun, frekuensi kecelakaan berkorelasi positif dengan lintas harian rata-rata tahunan, derajat kelengkungan, dan keberadaan median yang tingginya kurang dari 1,75 m dan lebarnya kurang dari 2,5 m. Model yang dibangun kemudian diaplikasikan untuk melakukan identifikasi dan pemeringkatan segmen jalan berbahaya. Hasilnya menunjukkan bahwa KM 92-93 (arah Cileunyi) merupakan segmen yang paling berbahaya pada jalan tol Purbaleunyi.Abstract. Road traffic safety condition in Indonesia still needs improvement that road traffic accidents occur frequently and cause many people died. One way to improve road safety is by developing accident prediction model. The model relates accident frequencies with traffic flow and various roadway geometric/environment characteristics contributing to accident occurrences. The model is useful to estimate and predict safety of a road entity, identify hazardous road locations, and also to evaluate treatment effectiveness applied on hazardous road locations. This paper presents the accident prediction model for Purwakarta-Bandung-Cileunyi (Purbaleunyi) toll road. The model was developed by comparing statistical performances of Poisson, Negatif Binomial (NB), Zero- Inflated Poisson (ZIP), dan Zero-Inflated Negative Binomial (ZINB) regression models. The modeling result indicates that the model which is developed using the NB regression model is the best. Based on the developed model, the accident frequency has positivie correlations with annual average daily traffic, degree of curvature, and presence of median with height less than 1.75 m and width less than 2.5 m. The developed model was subsequently applied to identify and rank hazardous road segments. The result shows that KM 92-93 (direction to Cileunyi) is the most hazardous segment at Purbaleunyi toll road.
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