EFFECT OF AUTOMATED SPEED ENFORCEMENT SYSTEMS ON DRIVING BEHAVIOR AND ATTITUDES ON MOUNTAINOUS ROADS IN THAILAND

Safety driving is one of the issues that always get serious attention is every country. Based on a survey done by ADB-ASEAN on Andrew Ruspali 2014, Indonesia is number 9 out of to 10 in handling the victim’s survival which considered to be very little. According to a research by Agus Aji Samekto (2009) stated that most accident victims in Semarang is 15-21 years old whom generally students and the vehicle involved were motorcycles. The purpose of this research was to know the influence of driving attitude to safety driving behavior. The object of this research was the student of STIMART “AMNI” Semarang.Keywords : Safety Driving Competency, Safety Driving Behavior, Students of STIMART “AMNI” Semarang Keselamatan berkendara merupakan salah satu masalah yang selalu mendapatkan perhatian serius di setiap negara. Kinerja keselamatan lalu lintas jalan di Indonesia dari survei yang dilakukan ADB-ASEAN dalam Andrew Ruspanah tahun 2014, berada pada peringkat ke-9 dari 10 negara. Ini menunjukkan bahwa penanganan masalah keselamatan akibat kecelakaan lalu lintas jalan di Indonesia belum banyak dilakukan. Penelitian Agus Aji Samekto (2009) menyebutkan bahwa jumlah terbesar korban kecelakaan lalu lintas di Kota Semarang dan didominasi oleh kelompok usia 15-21 tahun, pada umumnya adalah pelajar atau mahasiswa. Dimana jumlah kendaraan terbesar yang terlibat dalam kecelakaan lalu lintas adalah sepeda motor. Keselamatan berkendara merupakan salah satu masalah yang selalu mendapatkan perhatian serius di setiap negara. Tujuan penelitian ini adalah untuk mengetahui pengaruh sikap berkendara terhadap perilaku aman berkendara. Pada penelitian ini objek yang diambil adalah semua taruna-taruni STIMART “AMNI” Semarang yang aktif terdaftar.Kata kunci : Perilaku Aman Berkendara, Keterampilan Berkendara

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The Efficiency Evaluation of Automated Speed Enforcement System by Cost-Benefit Analysis

Productivity Review ◽

10.15843/kpapr.23.3.200909.19 ◽

2009 ◽

Vol 23 (3) ◽

pp. 19-43

Author(s):

강수철 ◽

장순희 ◽

Kim, Man Bae

Keyword(s):

Cost Benefit Analysis ◽

Cost Benefit ◽

Efficiency Evaluation ◽

Benefit Analysis ◽

Speed Enforcement

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Driving behavior: traffic risk perception and intentions to commit driving violations in Iran

Proceedings of the 9th Asia Pacific Conference on Transportation & the Environment ◽

10.31705/apte.2014.19 ◽

2014 ◽

Author(s):

Zahra Tabibi ◽

◽

Hoda Hashemi Chahnoeei ◽

Keyword(s):

Risk Perception ◽

Driving Behavior

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Cloning Safe Driving Behavior for Self-Driving Cars using Convolutional Neural Networks

Recent Patents on Computer Science ◽

10.2174/2213275911666181106160002 ◽

2019 ◽

Vol 12 (2) ◽

pp. 120-127 ◽

Cited By ~ 5

Author(s):

Wael Farag

Keyword(s):

Gradient Descent ◽

Autonomous Driving ◽

Driving Behavior ◽

Training Data ◽

Stochastic Gradient Descent ◽

Data Set ◽

Safe Driving ◽

Processing Pipeline ◽

Self Driving Cars ◽

And Training

Background: In this paper, a Convolutional Neural Network (CNN) to learn safe driving behavior and smooth steering manoeuvring, is proposed as an empowerment of autonomous driving technologies. The training data is collected from a front-facing camera and the steering commands issued by an experienced driver driving in traffic as well as urban roads. Methods: This data is then used to train the proposed CNN to facilitate what it is called “Behavioral Cloning”. The proposed Behavior Cloning CNN is named as “BCNet”, and its deep seventeen-layer architecture has been selected after extensive trials. The BCNet got trained using Adam’s optimization algorithm as a variant of the Stochastic Gradient Descent (SGD) technique. Results: The paper goes through the development and training process in details and shows the image processing pipeline harnessed in the development. Conclusion: The proposed approach proved successful in cloning the driving behavior embedded in the training data set after extensive simulations.

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