Short, Mid and Long Term Traffic Flow Forecasting and Data Visualization Tool

Abstract

The number of people and vehicles that are increasing day by day brings a serious traffic density to İstanbul. In order to eliminate or control this vehicle density, historical data should be interpreted well. All speed data that were measured in the provincial borders of Istanbul were recorded numerically by Istanbul Metropolitan Municipality. However, it is very difficult to evaluate these numerical data efficiently. Visualization is a frequently used method to infererence from numerical data and evaluation of it. In this study, a tool that analyzes and visualizes traffic density and estimates speed in the short, medium and long term has been developed. In the analysis part, the speed data received from the sensors at many points within the borders of Istanbul are customized according to a specific region, time and location and a visual content is presented to the user on their demands. Relevant information was marked on the map or numerical graphics were used in order to present visual content. In order to peroform traffic forecasting, three different methods based on regression and basic statistical data were employed and the obtained results were compared. Developed system can predict up to 1 week with a 21.8% Mean Absolute Percentage Error and 8.5 Mean Absolute Error by exploiting regression models that are generated for diffrent time slots of a whole day.

Keywords

• Traffic Flow Forecasting
• Traffic Flow Analysis
• Data Visualization
• Regression

Kısa, Orta ve Uzun Vadeli Trafik Akış Hızı Tahmini ve Görselleştirilme Aracı

Abstract

İstanbul içerisinde her geçen gün artan insan ve araç sayısı beraberinde ciddi bir trafik yoğunluğu getirmektedir. Oluşan bu araç yoğunluğunun giderilmesi veya kontrol edilebilmesi için eldeki verilerin iyi yorumlanması gerekmektedir. İstanbul il sınırları içerisinde ölçümleri yapılan tüm hız verileri İstanbul Büyükşehir Belediyesi tarafından kayıt altına alınmaktadır. Fakat bu verilerin sayılar üzerinden yorumlanması oldukça güçtür. Görselleştirme, sayısal verilerden anlam çıkarılması ve yorum yapılabilmesi için sıkça başvurulan bir yöntemdir. Bu çalışmada trafik yoğunluğunu analiz ederek görselleştiren, kısa, orta ve uzun vadede hız tahmini yapan bir araç geliştirilmiştir. Analiz kısmında İstanbul sınırları içerisinde birçok noktadaki sensörden alınan hız verileri belli bölge, zaman ve lokasyona göre özelleştirilmiş ve kullanıcıya talepleri doğrultusunda görsel bir içerik sunulmuştur. İçerik hazırlanırken ilgili bilgiler harita üzerinde işaretlenmiş veya sayısal grafiklerden yararlanılmıştır. Trafik tahmini yapabilmek için regresyon ve temel istatistiksel veriye dayalı üç farklı yöntem denenmiş ve elde edilen sonuçlar karşılaştırılmıştır. Geliştirilen sistem günün farklı zaman dilimleri için çıkarılan regresyon modellerini kullanarak %21.8 Ortalama Mutlak Yüzde Hatası ve 8.5 Ortalama Mutlak Hata ile 1 hafta sonraya kadar trafik akışı tahmini yapabilmektedir.

Keywords

• Trafik Akış Hızı Tahmini
• Trafik Akış Analizi
• Veri Görselleştirme
• Regresyon

References

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